Unprocessed aerial imagery from 28 August 2022 coastal survey of Washington.
This is a set of 4116 oblique aerial photogrammetric images and their derivatives, collected from Salish Sea with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 4 August 2020 coastal survey of Washington.
This is a set of 645 oblique aerial photogrammetric images and their derivatives, collected from Elwha river mouth to Ediz Hook CG with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 19 April 2023 thomas-fire survey of Southern California.
This is a set of 3086 vertical aerial photogrammetric images and their derivatives, collected from Montecito with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 23 January 2018 Thomas-fire survey of Southern California.
This is a set of 4838 oblique aerial photogrammetric images and their derivatives, collected from Montecito with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 18 March 2024 coastal survey of Southern California.
This is a set of 2076 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 23 February 2024 coastal survey of Southern California.
This is a set of 2371 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 12 February 2024 coastal survey of Southern California.
This is a set of 2032 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 5 January 2024 coastal survey of Southern California.
This is a set of 2061 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 12 October 2023 coastal survey of Southern California.
This is a set of 2013 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Port Hueneme with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 8 March 2023 coastal survey of Southern California.
This is a set of 2006 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 2 October 2022 coastal survey of Southern California.
This is a set of 1108 oblique aerial photogrammetric images and their derivatives, collected from Santa Rosa Island with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by ... |
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Unprocessed aerial imagery from 28 September 2022 coastal survey of Southern California.
This is a set of 2032 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 2 March 2022 coastal survey of Southern California.
This is a set of 2212 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 18 September 2020 coastal survey of Southern California.
This is a set of 1968 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 6 May 2020 coastal survey of Southern California.
This is a set of 2167 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 13 September 2018 coastal survey of Southern California.
This is a set of 2062 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 27 December 2017 coastal survey of Southern California.
This is a set of 2392 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Santa Barbara with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 1 March 2017 coastal survey of Southern California.
This is a set of 2979 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Ventura with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 28 September 2016 coastal survey of Southern California.
This is a set of 2671 oblique aerial photogrammetric images and their derivatives, collected from ptConception to Ventura with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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PCMSC PlaneCam – Field data from periodic and event-response surveys of the U.S. West Coast.
This is an ongoing collection of aerial oblique and near-nadir images, ancillary data, and derivatives, from aerial surveys of coastal and near-coastal environments with a crewed light aircraft using the "PCMSC PlaneCam," a mounted fixed-lens DSLR camera with an attached consumer-grade GPS for time-keeping and approximate position, and a Global Navigation Satellite System (GNSS) for precise positioning. Data are collected and produced primarily for coastal monitoring using structure-from-motion ... |
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Unprocessed aerial imagery from 1 June 2023 coastal survey of Oregon and Washington.
This is a set of 10139 oblique aerial photogrammetric images and their derivatives, collected from Salish Sea WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 29 August 2022 coastal survey of Oregon and Washington.
This is a set of 2413 oblique aerial photogrammetric images and their derivatives, collected from Taholah WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 3 September 2020 coastal survey of Oregon and Washington.
This is a set of 2158 oblique aerial photogrammetric images and their derivatives, collected from NW WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 3 August 2020 coastal survey of Oregon and Washington.
This is a set of 2324 oblique aerial photogrammetric images and their derivatives, collected from Taholah WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 28 September 2017 coastal survey of Oregon and Washington.
This is a set of 2060 oblique aerial photogrammetric images and their derivatives, collected from OR-WA border to Nestucca River OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 25 September 2016 coastal survey of Oregon and Washington.
This is a set of 1712 oblique aerial photogrammetric images and their derivatives, collected from Cape Falcon to Cascade Head with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 19 April 2024 coastal survey of Northern California to Washington.
This is a set of 14032 oblique aerial photogrammetric images and their derivatives, collected from Hoh Head to Cape Mendocino with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 13 October 2018 coastal survey of Northern California to Washington.
This is a set of 11805 oblique aerial photogrammetric images and their derivatives, collected from OR-WA border to Mussel Rock CA with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 29 March 2018 coastal survey of Central and southern California.
This is a set of 1160 oblique aerial photogrammetric images and their derivatives, collected from Mud Creek Slide to Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera ... |
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Unprocessed aerial imagery from 23 February 2017 landslides survey of Central California.
This is a set of 5954 oblique aerial photogrammetric images and their derivatives, collected from San Francisco Bay area with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 26 January 2017 landslides survey of Central California.
This is a set of 4889 oblique aerial photogrammetric images and their derivatives, collected from San Francisco Bay area with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 4-5 November 2020 CZU-fire survey of Central California.
This is a set of 11776 near-nadir aerial photogrammetric images and their derivatives, collected from CZU fire with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 12 January 2023 coastal-landslides survey of Central California.
This is a set of 11207 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 6 January 2023 coastal-landslides survey of Central California.
This is a set of 8762 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 18 August 2024 coastal survey of Central California.
This is a set of 2003 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 17 June 2024 coastal survey of Central California.
This is a set of 5140 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 6 April 2024 coastal survey of Central California.
This is a set of 2286 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 7 March 2024 coastal survey of Central California.
This is a set of 2161 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 24 February 2024 coastal survey of Central California.
This is a set of 3059 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 23 February 2024 coastal survey of Central California.
This is a set of 2323 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 9 February 2024 coastal survey of Central California.
This is a set of 4787 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 12 January 2024 coastal survey of Central California.
This is a set of 1965 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 1 January 2024 coastal survey of Central California.
This is a set of 2876 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 29 December 2023 coastal survey of Central California.
This is a set of 1821 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 23 December 2023 coastal survey of Central California.
This is a set of 4772 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 26 October 2023 coastal survey of Central California.
This is a set of 2869 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 11 October 2023 coastal survey of Central California.
This is a set of 4930 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 10 October 2023 coastal survey of Central California.
This is a set of 3929 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 8 June 2023 coastal survey of Central California.
This is a set of 2123 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 6 April 2023 coastal survey of Central California.
This is a set of 2374 vertical aerial photogrammetric images and their derivatives, collected from Half Moon Bay to Santa Cruz with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 17 March 2023 coastal survey of Central California.
This is a set of 2077 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 16 March 2023 coastal survey of Central California.
This is a set of 2915 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 13 March 2023 coastal survey of Central California.
This is a set of 2195 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 3 March 2023 coastal survey of Central California.
This is a set of 2758 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 2 March 2023 coastal survey of Central California.
This is a set of 1839 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 8 February 2023 coastal survey of Central California.
This is a set of 1939 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 1 February 2023 coastal survey of Central California.
This is a set of 2943 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 23 January 2023 coastal survey of Central California.
This is a set of 5039 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 16 January 2023 coastal survey of Central California.
This is a set of 2763 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 5 January 2023 coastal survey of Central California.
This is a set of 2105 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 1 January 2023 coastal survey of Central California.
This is a set of 2076 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 12-13 September 2022 coastal survey of Central California.
This is a set of 3661 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 9 June 2022 coastal survey of Central California.
This is a set of 4595 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 12 March 2022 coastal survey of Central California.
This is a set of 2098 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 4 February 2022 coastal survey of Central California.
This is a set of 2269 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 20 January 2022 coastal survey of Central California.
This is a set of 2066 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 18 December 2021 coastal survey of Central California.
This is a set of 4722 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 8 September 2021 coastal survey of Central California.
This is a set of 2678 oblique aerial photogrammetric images and their derivatives, collected from PigeonPt to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 26 March 2021 coastal survey of Central California.
This is a set of 5626 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 3 March 2021 coastal survey of Central California.
This is a set of 2049 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 29 January 2021 coastal survey of Central California.
This is a set of 4919 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 11 January 2021 coastal survey of Central California.
This is a set of 3796 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 10 January 2021 coastal survey of Central California.
This is a set of 1896 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 15 October 2020 coastal survey of Central California.
This is a set of 1982 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 30 September 2020 coastal survey of Central California.
This is a set of 3862 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 5 July 2020 coastal survey of Central California.
This is a set of 1890 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 19 April 2020 coastal survey of Central California.
This is a set of 2889 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 19 March 2020 coastal survey of Central California.
This is a set of 4835 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 9 March 2020 coastal survey of Central California.
This is a set of 1979 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 25 January 2020 coastal survey of Central California.
This is a set of 1880 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 20 January 2020 coastal survey of Central California.
This is a set of 3072 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 30 November 2019 coastal survey of Central California.
This is a set of 1444 oblique aerial photogrammetric images and their derivatives, collected from Davenport to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 29 November 2019 coastal survey of Central California.
This is a set of 1782 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Davenport with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 31 October 2019 coastal survey of Central California.
This is a set of 1911 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 15 October 2019 coastal survey of Central California.
This is a set of 3777 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 10 June 2019 coastal survey of Central California.
This is a set of 5042 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 11 March 2019 coastal survey of Central California.
This is a set of 1967 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 4 March 2019 coastal survey of Central California.
This is a set of 2541 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 23 February 2019 coastal survey of Central California.
This is a set of 4734 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 10 September 2018 coastal survey of Central California.
This is a set of 5846 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 5 June 2018 coastal survey of Central California.
This is a set of 1533 oblique aerial photogrammetric images and their derivatives, collected from Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 28 May 2018 coastal survey of Central California.
This is a set of 3550 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 7 March 2018 coastal survey of Central California.
This is a set of 5355 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 29 January 2018 coastal survey of Central California.
This is a set of 5365 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 21 December 2017 coastal survey of Central California.
This is a set of 2072 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 18 December 2017 coastal survey of Central California.
This is a set of 2948 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 26 June 2017 coastal survey of Central California.
This is a set of 5069 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 13 June 2017 coastal survey of Central California.
This is a set of 757 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 31 May 2017 coastal survey of Central California.
This is a set of 410 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 27 May 2017 coastal survey of Central California.
This is a set of 642 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 19 May 2017 coastal survey of Central California.
This is a set of 3164 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 17 May 2017 coastal survey of Central California.
This is a set of 3045 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 12 May 2017 coastal survey of Central California.
This is a set of 628 oblique aerial photogrammetric images and their derivatives, collected from SeaCliff Beach to Fort Ord with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 8 May 2017 coastal survey of Central California.
This is a set of 1975 oblique aerial photogrammetric images and their derivatives, collected from Pedro Point to Sunset Beach with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 5 April 2017 coastal survey of Central California.
This is a set of 5044 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Cape San Martin with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 8 March 2017 coastal survey of Central California.
This is a set of 5642 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 22 February 2017 coastal survey of Central California.
This is a set of 4808 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Lucia with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 25 January 2017 coastal survey of Central California.
This is a set of 4521 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Cape San Martin with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 20 December 2016 coastal survey of Central California.
This is a set of 3036 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 1 December 2016 coastal survey of Central California.
This is a set of 3234 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 26 September 2016 coastal survey of Central California.
This is a set of 1569 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ano Nuevo with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 15 September 2016 coastal survey of Central California.
This is a set of 1600 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 8 March 2016 coastal survey of Central California.
This is a set of 2753 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 2 March 2016 coastal survey of Central California.
This is a set of 1309 oblique aerial photogrammetric images and their derivatives, collected from Santa Cruz to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 5 February 2016 coastal survey of Central California.
This is a set of 3494 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 26 January 2016 coastal survey of Central California.
This is a set of 1836 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 9 December 2015 coastal survey of Central California.
This is a set of 1132 oblique aerial photogrammetric images and their derivatives, collected from Capitola to Pajaro Dunes with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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CMECS geoform, CMECS substrate, and surficial geology offshore of Eureka, California
This substrate, geomorphic, and geologic attributed polygon shapefile in the Offshore of Eureka, California, map area is part of USGS Data Series 781 (Golden and Cochrane, 2019). The map area is one of 83 map areas of the California State Waters Map Series. The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification ... |
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Census counts of the non-indigenous benthic foraminifera Trochammina hadai Uchio obtained in 1983-2010 in San Francisco Bay, California
This data release provides census counts of the non-indigenous benthic foraminifera Trochammina hadai Uchio in surface sediment samples obtained in San San Francisco Bay, California from 1983-2010. |
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CMECS geoform, CMECS substrate, and surficial geology offshore of Point Buchon (ver. 1.1, January 2024)
This shapefile has substrate, geomorphic, and geologic attributed polygons in the Offshore of Point Buchon, California, map area, one of 83 map areas of the California State Waters Map Series, USGS Data Series 781 (Golden and Cochrane, 2019). The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification Standard (CMECS; ... |
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CMECS geoform, CMECS substrate, and surficial geology offshore of Morro Bay (ver. 1.1, January 2024)
This part of USGS Data Series 781 presents substrate, geomorphic, and geologic attributed polygons in the Offshore of Morro Bay, California, map area, one of 83 map areas of the California State Waters Map Series. The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data ... |
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CMECS geoform, CMECS substrate, and surficial geology offshore of Point Estero (ver. 1.1, November 2023)
This substrate, geomorphic, and geologic attributed polygon shapefile in the Offshore of Eureka, California, map area is part of USGS Data Series 781 (Golden and Cochrane, 2019). The map area is one of 83 map areas of the California State Waters Map Series. The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification ... |
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CMECS geoform, CMECS substrate, and surficial geology offshore of Cape Mendocino
This shapefile has substrate, geomorphic, and geologic attributed polygons in the Offshore of Cape Mendocino, California, map area, one of 83 map areas of the California State Waters Map Series, USGS Data Series 781 (Golden, 2019). The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification Standard (CMECS; Federal ... |
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CMECS geoform, CMECS substrate, and surficial geology offshore of the Eel River
This part of USGS Data Series 781 presents substrate, geomorphic, and geologic attributed polygons in the Offshore of the Eel River, California, map area, one of 83 map areas of the California State Waters Map Series. The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data ... |
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Radiocarbon age dating of biological material from cores collected off central California in 1999, 2006, and 2019
Results of radiocarbon age dating of planktic and benthic foraminifera collected from cores obtained in 1999, 2006, and 2019 offshore central California in the vicinity of Morro Bay. |
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Census counts of palynomorphs from core 721-1 obtained in 2002 off San Francisquito Creek in South San Francisco Bay
This data release provides census counts of palynomorphs in sediments of a core obtained off San Francisquito Creek in South San Francisco Bay. |
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Anthropogenic metals and other elements from core 721-1 obtained in 2002 off San Francisquito Creek in South San Francisco Bay
This data release provides the measurement of anthropogenic metals and other elements in sediments of a core obtained off San Francisquito Creek in South San Francisco Bay. |
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Census counts of benthic foraminifera from core 721-1 obtained in 2002 off San Francisquito Creek in South San Francisco Bay
This data release provides census counts of benthic foraminifera in sediments of a core obtained off San Francisquito Creek in South San Francisco Bay. |
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Census counts of diatoms from core 721-1 obtained in 2002 off San Francisquito Creek in South San Francisco Bay
This data release provides census counts of diatoms in sediments of a core obtained off San Francisquito Creek in South San Francisco Bay. |
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Eelgrass and substrate characteristics in Bellingham Bay, Washington, July 2019
Eelgrass (Zostera marina) characteristics, sediment grain size distributions, sediment total organic carbon contents (TOC), carbon isotope ratios of sediment organic matter, and total carbon to total nitrogen ratios were measured at four lower intertidal sites in Bellingham Bay, Washington, July 2-5, 2019. |
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Coast Train--Labeled imagery for training and evaluation of data-driven models for image segmentation
Coast Train is a library of images of coastal environments, annotations, and corresponding thematic label masks (or ‘label images’) collated for the purposes of training and evaluating machine learning (ML), deep learning, and other models for image segmentation. It includes image sets from both geospatial satellite, aerial, and UAV imagery and orthomosaics, as well as non-geospatial oblique and nadir imagery. Images include a diverse range of coastal environments from the U.S. Pacific, Gulf of Mexico, ... |
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Habitat--Offshore of Ventura, California
This part of DS 781 presents habitat data in the Offshore of Ventura map area, California. The vector data file is included in "Habitat_OffshoreVentura.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreVentura/data_catalog_OffshoreVentura.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Seitz, G.G., Gutierrez, C.I., Sliter, R.W., Erdey ... |
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Habitat--Offshore of Santa Barbara, California
This part of DS 781 presents data for the habitat map of the Offshore of Santa Barbara map area, California. The vector data file is included in "Habitat_OffshoreSantaBarbara.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSantaBarbara/data_catalog_OffshoreSantaBarbara.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B.E., Endris, C.A., ... |
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Habitat--Offshore of Refugio Beach, California
This part of DS 781 presents the habitat map of the Offshore of Refugio Beach map area, California. The vector data file is included in "Habitat_RefugioBeach.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreRefugioBeach/data_catalog_OffshoreRefugioBeach.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Krigsman, L.M., Dieter, B.E., Conrad, J.E., Greene, H.G., Seitz, G.G., Endris, C.A., Sliter ... |
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Habitat--Offshore of Fort Ross, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Fort Ross map area, California. The polygon shapefile is included in "Habitat_OffshoreFortRoss.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreFortRoss/data_catalog_OffshoreFortRoss.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, ... |
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Habitat--Offshore of Coal Oil Point, California
This part of DS 781 presents the habitat map of the Offshore of Coal Oil Point map area, California. The vector data file is included in "Habitat_OffshoreCoalOilPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad, J.E., Lorenson, T.D., Krigsman, L.M., Greene, ... |
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Habitat--Offshore of Carpinteria, California
This part of DS 781 presents habitat data in the Offshore of Carpinteria map area, California. The vector data file is included in "Habitat_OffshoreCarpinteria.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCarpinteria/data_catalog_OffshoreCarpinteria.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.D., Wong, F.L ... |
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Habitat--Offshore of Tomales Point, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Tomales Point map area, California. The polygon shapefile is included in "Habitat_OffshoreTomalesPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M.W., ... |
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Habitat--Offshore of Point Reyes Map Map Area, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Point Reyes map area, California. The vector data file is included in "Habitat_PointReyes.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_OffshorePointReyes.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, ... |
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CMECS geoform, substrate, and biotopes offshore of Tacoma, Washington
This part of USGS Data Series 935 (Cochrane, 2014) presents substrate, geomorphic, and biotope data in the Offshore of Tacoma, Washington, map area, a part of the Southern Salish Sea Habitat Map Series. Given the variable bathymetric resolution, the complex geologic history of the region, and the lack of acoustic backscatter data, automated and semi-automated classification schemes of classifying seafloor substrate and geoform were deemed to have very low accuracy. Instead, classification of these ... |
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Habitat--Offshore Santa Cruz, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Santa Cruz map area, California. The vector data file is included in "Habitat_OffshoreSantaCruz.zip," which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., Sliter, R.W., Maier ... |
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Habitat--Offshore of Aptos, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Aptos map area, California. The vector data file is included in "Habitat_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R.W., ... |
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Habitat--Offshore of San Gregorio, California
This part of SIM 3306 presents data for the habitat map of the Offshore of San Gregorio map area, California. The vector data file is included in "Habitat_OffshoreSanGregorio.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanGregorio/data_catalog_OffshoreSanGregorio.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Watt, J.T., Golden, N.E., Endris, C.A., Phillips, E.L., Hartwell, S.R., Johnson, S.Y., Kvitek, R.G., Erdey, M.D., Bretz, C ... |
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Habitat--Offshore of San Francisco, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of San Francisco map area, California. The vector data file is included in "Habitat_SanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R.W., Kvitek, R.G. ... |
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Habitat--Offshore of Salt Point, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Salt Point map area, California. The vector data file is included in "Habitat_OffshoreSaltPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., ... |
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Habitat--Offshore of Half Moon Bay, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Half Moon Bay map area, California. The polygon shapefile is included in "Habitat_OffshoreHalfMoonBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreHalfMoonBay/data_catalog_OffshoreHalfMoonBay.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Johnson, S.Y., Golden, N.E., Hartwell, S.R., Dieter, B.E., Manson, M.W., Sliter, R.W., Ross, S.L., Watt, J ... |
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Habitat--Offshore of Bolinas, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Bolinas map area, California. The vector data file is included in "Habitat_OffshoreBolinas.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, S.L., ... |
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Habitat--Offshore of Pacifica, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Pacifica map area, California. The vector data file is included in "Habitat_OffshorePacifica.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePacifica/data_catalog_OffshorePacifica.html. These data accompany the pamphlet and map sheets of Edwards, B.D., Phillips, E.L., Dartnell, P., Greene, H.G., Bretz, C.K., Kvitek, R.G., Hartwell, S.R., Johnson, S.Y., Cochrane, G.R., Dieter, B.E., Sliter, R.W., Ross ... |
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Radiocarbon age dating of biological material from cores collected off British Columbia, Canada and southeastern Alaska, U.S. along the Queen Charlotte-Fairweather fault zone
Results of radiocarbon age dating of planktic foraminifera, benthic foraminifera, and pelecypod shell fragments collected from piston cores, trigger weight cores, and IKU grab samples obtained in 2015 and 2017 offshore British Columbia, Canada and southeastern Alaska, U.S. along the Queen Charlotte-Fairweather fault zone. |
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CMECS geoform, substrate, and biotopes offshore of Seattle, Washington
This part of USGS Data Series 935 (Cochrane, 2014) presents substrate, geomorphic, and biotope data in the Offshore of Seattle, California, map area, a part of the Southern Salish Sea Habitat Map Series. Given the variable bathymetric resolution, the complex geologic history of the region, and the lack of acoustic backscatter data, automated and semi-automated classification schemes of classifying seafloor substrate and geoform were deemed to have very low accuracy. Instead, classification of these ... |
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CMECS geoform, substrate, and biotopes offshore of Burien, Washington
This part of USGS Data Series 935 (Cochrane, 2014) presents substrate, geomorphic, and biotope data in the Offshore of Burien, Washington, map area, a part of the Southern Salish Sea Habitat Map Series. Given the variable bathymetric resolution, the complex geologic history of the region, and the lack of acoustic backscatter data, automated and semi-automated classification schemes of classifying seafloor substrate and geoform were deemed to have very low accuracy. Instead, classification of these ... |
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Habitat--Offshore of Bodega Head, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Bodega Head map area, California. The vector data file is included in "Habitat_OffshoreBodegaHead.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E. ... |
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Accelerator Mass Spectrometry (AMS) 14C radiocarbon analysis of authigenic carbonates collected offshore the U.S. Mid- and South Atlantic
Results are presented from Accelerator Mass Spectrometry (AMS) carbon-14 radiocarbon dating of carbonate rock samples collected from seep fields offshore the U.S. Mid- and South Atlantic in 2018 and 2019. Samples were collected as a fingerprint to past hydrocarbon seep activity, fluid source, and depositional environment. |
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Geochemical and mineralogic analysis of authigenic carbonates collected offshore the U.S. Mid- and South Atlantic
Geochemical and mineralogic analysis of selected carbonate rock samples collected from seep fields on the RB1903 and AT41 research expeditions in the U.S. Mid- and South Atlantic.Samples were collected as a fingerprint to past hydrocarbon seep activity, fluid source, and depositional environment. Analyses include: Wavelength-dispersive X-ray Fluorescence (WDXRF) major element, Inductively Coupled Optical Emission Spectroscopy/Mass Spectroscopy (ICPOES-MS) major and minor element, and x-ray diffractrometry ... |
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Results from isotope analysis of authigenic carbonates collected offshore the U.S. Mid- and South Atlantic
Geochemical analysis of carbonate rock samples collected from seep fields on the RB1903 and AT41 research expeditions in the U.S. Mid- and South Atlantic. Samples were collected as a fingerprint to past hydrocarbon seep activity, fluid source, and depositional environment. |
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CMECS geoform, CMECS substrate, and surficial geology offshore of Arcata, California
This substrate, geomorphic, and geologic attributed polygon shapefile in the Offshore of Arcata, California, map area is part of USGS Data Series 781 (Golden and Cochrane, 2019). The map area is one of 83 map areas of the California State Waters Map Series. The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification ... |
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Eelgrass distributions derived from a towed underwater video survey of the Nisqually River delta, 2017
This portion of the USGS data release presents eelgrass distributions derived from towed underwater video surveys of the Nisqually River delta, Washington in 2017 (USGS Field Activity Number 2017-614-FA). Eelgrass data were collected from the R/V George Davidson equipped with a towed underwater video system and global navigation satellite system (GNSS) receiver. The underwater video system consisted of a Splashcam standard definition video camera connected to a Sony GV-D1000 video monitor and tape recorder. ... |
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Eelgrass distributions derived from a towed underwater video survey of the Nisqually River delta, 2014
This portion of the USGS data release presents eelgrass distributions derived from towed underwater video surveys of the Nisqually River delta, Washington in 2014 (USGS Field Activity Number D-01-14-PS). Eelgrass data were collected from the R/V George Davidson equipped with a towed underwater video system and global navigation satellite system (GNSS) receiver. The underwater video system consisted of a Splashcam standard definition video camera connected to a Sony GV-D1000 video monitor and tape recorder. ... |
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Eelgrass distributions derived from a towed underwater video survey of the Nisqually River delta, 2012
This portion of the USGS data release presents eelgrass distributions derived from towed underwater video surveys of the Nisqually River delta, Washington in 2012 (USGS Field Activity Number D-01-12-PS). Eelgrass data were collected from the R/V George Davidson equipped with a towed underwater video system and global navigation satellite system (GNSS) receiver. The underwater video system consisted of a Splashcam standard definition video camera connected to a Sony GV-D1000 video monitor and tape recorder. ... |
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Vegetation biomass and density from three locations in the Sacramento-San Joaquin Delta, California, 2017 to 2018
Vegetation type and density data were collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at three locations in the Sacramento-San Joaquin Delta. Data were collected in Lindsey Slough in April 2017, and Middle River and the Mokelumne River in March 2018. Vegetation samples were collected by divers, and used to determine dry biomass density. These data were collected as part of a cooperative project, with the USGS California Water Science Center and the California ... |
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Swath bathymetric data from three locations in the Sacramento-San Joaquin Delta, California, 2017 to 2018
This part of the data release contains high-resolution swath bathymetry data collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at three locations in the Sacramento-San Joaquin Delta. Data were collected in Lindsey Slough in April 2017, Middle River in March 2018, and Mokelumne River in March 2018 using an interferometric bathymetric sidescan sonar systems mounted to the USGS R/V Parke Snavely. Data are provided in 1-m resolution GeoTIFF formats. These data were ... |
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Suspended particle size distribution data from three locations in the Sacramento-San Joaquin Delta, California, 2017 to 2018
These data present suspended particle size distributions collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at three locations in the Sacramento-San Joaquin Delta. Data were collected in Lindsey Slough on April 4 and April 18, 2017, and near the mouth of the Mokelumne River and in Middle River on March 14, 2018 by deploying a Sequoia Scientific Laser In-situ Scattering and Transmissometry instrument (LISST 100x) from a small vessel during the deployment of the ... |
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Hydrodynamic time-series data from three locations in the Sacramento-San Joaquin Delta, California, 2017 to 2018
Hydrodynamic and sediment transport time-series data, including water depth, velocity, turbidity, conductivity, and temperature, were collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at three locations in the Sacramento-San Joaquin Delta. Data were collected in Lindsey Slough in April 2017, and Middle River and the Mokelumne River in March 2018. Data files are grouped by location. At each of the three sites, data were collected at stations outside and within patches ... |
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Acoustic-backscatter data from three locations in the Sacramento-San Joaquin Delta, California, 2017 to 2018
This part of the data release contains high-resolution acoustic-backscatter data collected by the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center at three study locations in the Sacramento-San Joaquin Delta, California. Data were collected in Lindsey Slough in April 2017, Middle River in March 2018, and Mokelumne River in March 2018, using an interferometric bathymetric sidescan sonar systems mounted to the USGS R/V Parke Snavely. Data are provided in 1-m resolution GeoTIFF formats. ... |
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Seawater carbonate chemistry, Kahekili, west Maui
Time-series of seawater carbonate chemistry variables, including salinity, dissolved inorganic nutrients, pH, total alkalinity, and dissolved inorganic carbon from sites along Kahekili Beach Park, west Maui near submarine groundwater seeps and living coral reefs. Samples for seawater were collected by pumping bottom water from the seafloor using a peristaltic pump and collecting discrete water samples every 4-hrs over a 6-day period. |
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Coral growth parameters, Kahekili, west Maui
Surface runoff and submarine groundwater discharge in particular are known vectors to the coastal ocean of elevated nutrients and contaminants leading to eutrophication, algal overgrowth, and coral disease. Freshwater discharging directly from submarine groundwater vents off of Kahekili Beach Park, Kaanapali, in West Maui contains elevated nutrient concentrations and lower pH values. Coral cores were collected in July 2013 from the shallow reef at Kahekili in Kaanapali, West Maui, Hawaii from ... |
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Fish abundance in the Elwha River estuary, Washington, from 2006 to 2014
This portion of the data release presents fish abundance data from samples collected in the Elwha River estuary, Washington, in 2006, 2007, 2013, and 2014 (no associated USGS Field Activities numbers because data were collected predominantly by biologists from the Lower Elwha Klallam Tribe). We used the Puget Sound beach seining protocol (Simenstad and others, 1991) to sample fish populations in the Elwha River estuary complex. The beach seine was 38 m long x 2 m deep, with a 2 m x 2 m bag in the center of ... |
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Mammal Observations-Oregon OCS Floating Wind Farm Site
This part of the Oregon OCS Data Release presents marine mammal observations from U.S. Geological Survey (USGS) field activity 2014-607-FA in the Oregon Outer continental Shelf (OCS)Floating Wind Farm survey area. The survey was conducted using 12 hour day operations out of Charleston Harbor near Coos Bay, Oregon. The cruise plan consisted of 23 days on site split between sonar mapping and video ground truth surveying. Activities parsed out to nine days of sonar mapping, three days of video surveying, eight ... |
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Coastal Marine Geology Program Video and Photograph Portal
Access to the U.S. Geological Survey (USGS) Coastal and Marine Geology Program’s (CMGP) vast collection of unique and valuable seafloor and coastal imagery is made available in the CMGP Video and Photograph Portal. The portal provides a single location for data discovery and viewing. The CMGP and our research partners invest immense resources collecting, processing, and archiving seafloor and oblique coastal video and photographs. Until the publication of the CMGP Video and Photograph Portal in 2015, only ... |
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Terrestrial invertebrate abundance in the Elwha River estuary, Washington, in 2007 and 2013.
This portion of the data release presents terrestrial invertebrate abundance data from samples collected in emergent and shrub vegetation along the edge of the Elwha River estuary, Washington, in 2007 and 2013 (no associated USGS Field Activities numbers because data were collected predominantly by biologists from the Lower Elwha Klallam Tribe). We deployed terrestrial insect fallout traps at ten locations in the east estuary, five replicates each in shrub and emergent (littoral) vegetation habitats. Clear, ... |
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Diet of Chinook and coho salmon in the Elwha River estuary, Washington, before and during dam removal
This portion of the data release presents fish diet data from Chinook and coho salmon collected in the Elwha River estuary, Washington, in 2006, 2007, 2013, and 2014 (there are no associated USGS Field Activities numbers because data were collected predominantly by biologists from the Lower Elwha Klallam Tribe). Fish were collected using a beach seine at six locations throughout the estuary. Fish were transferred to buckets containing aerated ambient water and kept cool until handling. We anesthetized fish ... |
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Aquatic invertebrate abundance in the Elwha River estuary, Washington, in 2007 and 2013
This portion of the data release presents aquatic invertebrate abundance data from samples collected in the Elwha River estuary, Washington, in 2007 and 2013 (no associated USGS Field Activities numbers because data were collected predominantly by biologists from the Lower Elwha Klallam Tribe). Replicate benthic samples were collected at 18 locations throughout the estuary complex using a petite Ponar grab sampler (appx. 2400 mL sample) and sorted through a 500-micron sieve. Samples were fixed in 10 percent ... |
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Physical, environmental, and biotic observations derived from underwater video collected offshore of south-central California in support of the Bureau of Ocean Energy Management Cal DIG I offshore alternative energy project
Physical, environmental, and biotic observations were derived from underwater video collected by the Monterey Bay Aquarium Research Institute (MBARI) using remotely operated vehicles (ROVs) offshore of Morro Bay, California. The data were acquired during three separate surveys in 2019 in support of the U.S. Geological Survey (USGS)/Bureau of Ocean Energy Management (BOEM) California Deepwater Investigations and Groundtruthing I (Cal DIG I) project. Transect information developed to analyze the data for ... |
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Benthic habitats of the coral reef ecosystem off the coast of Pu'uhonua O Honaunau (PUHO) National Historical Park
A benthic habitat polygon coverage has been created of the coral reef ecosystem off the coast of Pu'uhonua O Honaunau (PUHO) National Historical Park on the Kona Coast of Hawai'i. Polygons were hand-digitized from visual interpretation of aerial photography and SHOALS bathymetry data. We also utilized in situ knowledge from towed instruments, underwater photography and videography, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate, ... |
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Benthic habitats of the coral reef ecosystem off the coast of Kaloko-Honokohau (KAHO) National Historical Park
A benthic habitat polygon coverage has been created of the coral reef ecosystem within and adjacent to Kaloko-Honokohau (KAHO) National Historical Park on the Kona Coast of Hawai'i. Polygons were hand-digitized from visual interpretation of aerial photography and SHOALS bathymetry data. We also utilized in situ knowledge from towed instruments, underwater photography and videography, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate ... |
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Benthic habitats of the coral reef ecosystem off the coast of Pu'ukohola Heiau (PUHE) National Historic Site
A benthic habitat polygon coverage has been created of the coral reef ecosystem off the coast of Pu'ukohola Heiau (PUHE) National Historic Site on the Kona Coast of Hawai'i. Polygons were hand-digitized from visual interpretation of aerial photography and SHOALS bathymetry data. We also utilized in situ knowledge from towed instruments, underwater photography and videography, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate, Major ... |
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Benthic habitat map of the U.S. Coral Reef Task Force Watershed Partnership Initiative Kaanapali priority study area and the State of Hawaii Kahekili Herbivore Fisheries Management Area, west-central Maui, Hawaii
A benthic habitat polygon coverage has been created of the coral reef ecosystem within the U.S. Coral Reef Task Force Watershed Partnership Initiative Kaanapali priority study area and the State of Hawaii Kahekili Herbivore Fisheries Management Area, West-Central Maui, Hawaii. Polygons were hand-digitized from visual interpretation of QuickBird-2 satellite imagery (2005), and SHOALS bathymetry data. We also utilized in situ knowledge from underwater photography and videography (2002-2011), side-scan sonar ... |
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Benthic habitats of the coral reef ecosystem on the south shore of Moloka'i
A benthic habitat polygon coverage has been created of the coral reef ecosystem on the south shore of Moloka'i. Polygons were hand-digitized from visual interpretation of aerial photography and SHOALS bathymetry data. We also utilized in situ knowledge from towed instruments, underwater photography and videography, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate, Major Biological Cover, Percent of Major Biological Cover, Reef Zone ... |
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Habitat--Offshore Scott Creek, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Scott Creek map area, California. The vector data file is included in "Habitat_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., ... |
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Habitat--Offshore Pigeon Point, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Pigeon Point map area, California. The vector data file is included in "Habitat_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., ... |
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Habitat--Offshore of Monterey, California
This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Monterey map area, California. The vector data file is included in "Habitat_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds. ... |
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Habitat--Hueneme Canyon and Vicinity, California
This part of DS 781 presents data for the habitat map of the seafloor of the Hueneme Canyon and Vicinity map area, California. The vector data file is included in "Habitat_HuenemeCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter ... |
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Habitat--Drakes Bay and Vicinity, California
This part of DS 781 presents data for the habitat map of the seafloor of the Drakes Bay and Vicinity map area, California. The vector data file is included in "Habitat_DrakesBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., ... |
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Projected flooding extents and depths based on 10-, 50-, 100-, and 500-year wave-energy return periods for the Territory of the U.S. Virgin Islands for current and potentially restored coral reefs
This part of the data release presents projected flooding extent polygon (flood masks) shapefiles based on wave-driven total water levels for the Territory of the U.S. Virgin Islands. There are 16 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the current scenario (base) and each of the restoration scenarios (structural_25, structural_05, and ecological_25). |
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Projected flooding extents and depths based on 10-, 50-, 100-, and 500-year wave-energy return periods for the Commonwealth of Puerto Rico for current and potentially restored coral reefs
This part of the data release presents projected flooding extent polygon (flood masks) shapefiles based on wave-driven total water levels for the Commonwealth of Puerto Rico. There are 16 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the current scenario (base) and each of the restoration scenarios (structural_25, structural_05, and ecological_25). |
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Projected flooding extents and depths based on 10-, 50-, 100-, and 500-year wave-energy return periods for the State of Florida for current and potentially restored coral reefs
This part of the data release presents projected flooding extent polygon (flood masks) shapefiles based on wave-driven total water levels for the State Florida (the Florida Peninsula and the Florida Keys). There are 16 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the current scenario (base) and each of the restoration scenarios (structural_25, structural_05, and ecological_25). |
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Census counts of benthic foraminifera, environmental parameters (temperature, salinity, and oxygen concentration), and radiocarbon measurements from cores obtained under and near a whale-fall off western Vancouver Island, British Columbia, Canada
This data release provides census counts of benthic foraminifera (in percent for the total fauna and as raw counts for just the living specimens) as well as environmental parameters (temperature, salinity, and oxygen concentration) at the sampling sites, and radiocarbon measurements from selected push core samples obtained under and near a whale-fall off western Vancouver Island, British Columbia, Canada. |
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Coral geochemistry time series from Kahekili, west Maui
Geochemical analysis (including stable boron, boron:calcium ratio, and carbon and oxygen isotopes) were measured from coral cores collected in July 2013 from the shallow reef at Kahekili in Kaanapali, west Maui, Hawaii from scleractinian Porites lobata. |
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Radiocarbon dating of deep-sea black corals collected off the southeastern United States
Results of radiocarbon dating of deep-sea (500 m to 700 m) black corals are presented. These corals were collected off the southeastern United States as part of the Southeastern United States Deep-Sea Corals (SEADESC) Initiative. |
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Projected flood extent polygons and flood depth points based on 10-, 50-, 100-, and 500-year wave-energy return periods, with and without coral reefs, for the Territory of the U.S. Virgin Islands (the islands of Saint Croix, Saint John, and Saint Thomas)
This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for the Territory of the U.S. Virgin Islands (the islands of Saint Croix, Saint John, and Saint Thomas). For each island there are 8 associated flood mask and flood depth shapefiles: one for each four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of ... |
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Projected flooding extents and depths based on 10-, 50-, 100-, and 500-year wave-energy return periods, with and without coral reefs, for the States of Hawaii and Florida, the Territories of Guam, American Samoa, Puerto Rico, and the U.S. Virgin Islands, and the Commonwealth of the Northern Mariana Islands
This data release provides flooding extent polygons (flood masks) and depth values (flood points) based on wave-driven total water levels for 22 locations within the States of Hawaii and Florida, the Territories of Guam, American Samoa, Puerto Rico, and the U.S. Virgin Islands, and the Commonwealth of the Northern Mariana Islands. For each of the 22 locations there are eight associated flood mask polygons and flood depth point files: one for each four nearshore wave energy return periods (rp; 10-, 50-, 100- ... |
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Projected flood extent polygons and flood depth points based on 10-, 50-, 100-, and 500-year wave-energy return periods, with and without coral reefs, for the Territory of Puerto Rico (the islands of Culebra, Puerto Rico, and Vieques)
This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for the Territory of Puerto Rico (the islands of Culebra, Puerto Rico, and Vieques). For each island there are 8 associated flood mask and flood depth shapefiles: one for each four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of coral reefs. Flooding ... |
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Projected flood extent polygons and flood depth points based on 10-, 50-, 100-, and 500-year wave-energy return periods, with and without coral reefs, for the State of Hawaii (the islands of Hawaii, Kahoolawe, Kauai, Lanai, Maui, Molokai, Niihau, and Oahu)
This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for the State of Hawaii (the islands of Hawaii, Kahoolawe, Kauai, Lanai, Maui, Molokai, Niihau, and Oahu). For each island there are 8 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of ... |
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Projected flood extent polygons and flood depth points based on 10-, 50-, 100-, and 500-year wave-energy return periods, with and without coral reefs, for the Territory of Guam
This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for the Territory of Guam. There are 8 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of coral reefs. Flooding depth point data are also presented as a comma-separated value (.csv) ... |
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Projected flood extent polygons and flood depth points based on 10-, 50-, 100-, and 500-year wave-energy return periods, with and without coral reefs, for the State Florida (the Florida Peninsula and the Florida Keys)
This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for the State Florida (the Florida Peninsula and the Florida Keys). For each island there are 8 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of coral reefs. Flooding depth point data ... |
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Projected flood extent polygons and flood depth points based on 10-, 50-, 100-, and 500-year wave-energy return periods, with and without coral reefs, for the Commonwealth of the Northern Mariana Islands (the islands of Saipan and Tinian)
This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for Commonwealth of the Northern Mariana Islands (the islands of Saipan and Tinian). For each island there are 8 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of coral reefs. |
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Projected flood extent polygons and flood depth points based on 10-, 50-, 100-, and 500-year wave-energy return periods, with and without coral reefs, for American Samoa (the islands of Tutuila, Ofu-Olosega, and Tau)
This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for American Samoa (the islands of Tutuila, Ofu-Olosega, and Tau). For each island there are 8 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of coral reefs. Flooding depth point data ... |
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Invertebrate remains from the Dominican University of California archaeological site MRN-CA-254, Marin County, California
This data release indicates faunal presence or absence of shelly artifacts (invertebrate remains) from the Dominican University of California archaeological site MRN-CA-254, Marin County, California. |
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Projected flooding extents and depths based on 10-, 50-, 100-, and 500-year wave-energy return periods for the Commonwealth of Puerto Rico before and after Hurricanes Irma and Maria due to the storms' damage to the coral reefs
This part of the data release presents projected flooding extent polygon (flood masks) shapefiles based on wave-driven total water levels for Commonwealth of Puerto Rico. There are eight associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the pre-storm scenario (base) and the post-storm scenarios. |
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Projected flooding extents and depths based on 10-, 50-, 100-, and 500-year wave-energy return periods for the State of Florida before and after Hurricanes Irma and Maria due to the storms' damage to the coral reefs
This part of the data release presents projected flooding extent polygon shapefiles based on wave-driven total water levels for the State Florida (the Florida Peninsula and the Florida Keys). There are eight associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the pre-storm scenario (base) and the post-storm scenarios. |
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Geochemistry time series and growth parameters from Tutuila, American Samoa coral record
Geochemical analysis (including age-corrected radiocarbon stable isotopes, and elemental composition) and growth parameters (including calcification rate, density, and extension information) were measured from a coral core collected from a reef off the southern side of Tutuila, American Samoa. The core was collected near Matautuloa Point on 8 April 2012 in collaboration with the Ecosystem Sciences Division, Pacific Islands Fisheries Science Center, National Oceanic and Atmospheric Administration (NOAA), ... |
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Flooding extent polygons for modelled wave-driven water levels in Florida with and without projected coral reef degradation
This data release presents projected flooding extent polygon (flood masks) shapefiles based on wave-driven total water levels for the State Florida (the Florida Peninsula and the Florida Keys). There are 12 associated flood mask shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the current scenario (base) and each of the degradation scenarios (Mean Elevation and Mean Erosion). |
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Geophysical properties, geochronologic, and geochemical data of sediment cores collected from San Pablo Bay, California, October 17-20, 2016
Geophysical properties (P-wave velocity, gamma ray density, and magnetic susceptibility), geochronologic (radiocarbon, excess Lead-210, and Cesium-137), and geochemical data (organic carbon content and 60 element contents) are reported for select vibracores collected aboard the S/V Retriever October 17-20, 2016, in San Pablo Bay, California. Geophysical properties were measured with a Geotek Multi-Sensor Core Logger (MSCL). Radiocarbon was measured by accelerator mass spectrometry (AMS). Excess Lead-210 and ... |
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Acoustic-backscatter data collected in the Cache Slough Complex and the Sacramento River Deep Water Ship Channel, California, during field activity 2018-684-FA
Acoustic-backscatter data were collected during a 2018 swath survey in the Cache Slough Complex and the Sacramento River Deep Water Ship Channel, California. Data were collected by the U.S. Geological Survey (USGS) during USGS field activity 2018-684-FA, using interferometric bathymetric sidescan sonar systems mounded to the USGS R/V San Lorenzo and the R/V Kelpfly. The backscatter data are provided as GeoTIFF images. |
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Still-image frame grabs and benthic habitat interpretation of underwater video footage, March 2014, Faga`alu Bay, American Samoa
Underwater video was collected in March 2014 in the nearshore waters of Faga`alu Bay on the island of Tutuila, American Samoa, as part of the U.S. Geological Survey Coastal and Marine Geology Program's Pacific Coral Reefs Project. This dataset includes 2,119 still images extracted from the video footage every 10 seconds and an Environmental Systems Research Institute (ESRI) shapefile of individual still-image locations with benthic habitat interpretations for each image. |
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Geochemical analysis of authigenic carbonates and chemosynthetic mussels at Atlantic Margin seeps (ver. 2.0, March 2019)
Isotopic analyses of authigenic carbonates and methanotrophic deep-sea mussels, Bathymodiolus sp., was performed on samples collected from seep fields in the Baltimore and Norfolk Canyons on the north Atlantic margin. Samples were collected using remotely operated underwater vehicles (ROVs) during three different research cruises in 2012, 2013, and 2015. Analyses were performed by several different laboratories, and the results are presented in spreadsheet format. |
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Seafloor photographs and location data, West Hawaii, 2010-2011
Seafloor photographs were collected by SCUBA divers along pre-determined transects using an underwater digital camera following benthic survey protocols developed by the National Park Service (NPS) at Kaloko-Honokohau National Historical Park (Marrack and others, 2014; Weijerman and others, 2014) and modeled after the U.S. Geological Survey (USGS) and NPS coral reef survey protocols (Rogers and others, 2001; Brown and others, 2011). This dataset includes seafloor photographs in jpg format, the locations of ... |
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Coral Point Count (CPCe) summary data by transect, West Hawaii, 2010-2011
Coral Point Count with Excel extensions (CPCe; Kohler and Gill, 2006) was used to help calculate percent of coral cover or other benthic substrates from a randomly selected subset of seafloor photographs collected on the west Hawaii Island coast. |
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Coral species and size data by transect, West Hawaii, 2011
Observations of coral species and size were documented by scuba divers along pre-determined transects and are presented here in comma-separated format. |
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Coral disease data by transect, West Hawaii, 2011
Observations of coral disease and health indicators were documented by scuba divers along pre-determined transects and are presented here in comma-separated format. Included in the table are coral species observed, colony size, types and number of indicators observed, and a size range of indicators observed. |
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Coral bleaching data by site, West Hawaii, 2010-2011
Observations of bleached coral were documented by scuba divers along pre-determined transects and are presented here in comma-separated format. Included in the table are coral species observed, colony size, size of bleached area on colony, and seawater temperature. |
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Shorelines of the Western Beaufort Sea, Alaska coastal region (Colville River to Point Barrow) used in shoreline change analysis
This dataset includes shorelines from 65 years ranging from 1947 to 2012 for the north coast of Alaska between the Colville River and Point Barrow. Shorelines were compiled from topographic survey sheets (T-sheets; National Oceanic and Atmospheric Administration (NOAA)), aerial orthophotographs (U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA), and lidar elevation data(USGS). Historical shoreline positions serve as easily understood features that can be used to describe ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term Linear Regression Rate Calculations for the Sheltered West Beaufort Sea coast of Alaska between the Colville River and Point Barrow
This dataset consists of short-term (~33 years) shoreline change rates for the north coast of Alaska between the Colville River and Point Barrow. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2012. A reference baseline was used as the ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Sheltered West Beaufort Sea coast of Alaska between the Colville River and Point Barrow
This dataset consists of long-term (~65 years) shoreline change rates for the north coast of Alaska between the Colville River and Point Barrow. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2012. A reference baseline was used as the ... |
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Offshore baseline for the sheltered West Beaufort Sea, Alaska coastal region (Colville River to Point Barrow) generated to calculate shoreline change rates
This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the sheltered north coast of Alaska coastal region between the Colville River and Point Barrow for the time period 1947 to 2012. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates. |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term Linear Regression Rate Calculations for the Exposed West Beaufort Sea coast of Alaska between the Colville River and Point Barrow
This dataset consists of short-term (~33 years) shoreline change rates for the north coast of Alaska between the Colville River and Point Barrow. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2012. A reference baseline was used as the ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Exposed West Beaufort Sea coast of Alaska between the Colville River and Point Barrow
This dataset consists of long-term (~65 years) shoreline change rates for the north coast of Alaska between the Colville River and Point Barrow. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2012. A reference baseline was used as the ... |
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Offshore baseline for the exposed West Beaufort Sea, Alaska coastal region (Colville River to Point Barrow) generated to calculate shoreline change rates
This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the exposed north coast of Alaska coastal region between the Colville River and Point Barrow for the time period 1947 to 2012. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates. |
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Shorelines of the Eastern Chukchi Sea, Alaska coastal region (Point Barrow to Icy Cape) used in shoreline change analysis
This dataset includes shorelines from 65 years ranging from 1947 to 2012 for the north coast of Alaska between Point Barrow and Icy Cape. Shorelines were compiled from topographic survey sheets and Nautical Charts (T-sheet, Nautical Chart; National Oceanic and Atmospheric Administration (NOAA)), aerial orthophotographs (U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA), satellite imagery (State of Alaska), and lidar elevation data (USGS). Historical shoreline positions ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term End Point Rate Calculations for the Sheltered East Chukchi Sea coast of Alaska between Point Barrow and Icy Cape
This dataset consists of short-term (~33 years) shoreline change rates for the north coast of Alaska between Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using an end point rate-of-change method based on available shoreline data between 1979 and 2012. A reference baseline was used as the originating point ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Sheltered East Chukchi Sea coast of Alaska between Point Barrow and Icy Cape
This dataset consists of long-term (~65 years) shoreline change rates for the north coast of Alaska between Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2012. A reference baseline was used as the originating ... |
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Offshore baseline for the sheltered Eastern Chukchi Sea, Alaska coastal region (Point Barrow to Icy Cape) generated to calculate shoreline change rates
This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the sheltered north coast of Alaska coastal between Point Barrow and Icy Cape for the time period 1947 to 2012. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates. |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term Linear Regression Rate Calculations for the Exposed East Chukchi Sea coast of Alaska between the Point Barrow and Icy Cape
This dataset consists of short-term (~31 years) shoreline change rates for the north coast of Alaska between the Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2010. A reference baseline was used as the ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term End Point Rate Calculations for the Exposed East Chukchi Sea coast of Alaska between Point Barrow and Icy Cape
This dataset consists of short-term (~32 years) shoreline change rates for the north coast of Alaska between Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using an end point rate-of-change method based on available shoreline data between 1979 and 2011. A reference baseline was used as the originating point ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Exposed East Chukchi Sea coast of Alaska between Point Barrow and Icy Cape
This dataset consists of long-term (~65 years) shoreline change rates for the north coast of Alaska between Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2012. A reference baseline was used as the originating ... |
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Offshore baseline for the exposed Eastern Chukchi Sea, Alaska coastal region (Point Barrow to Icy Cape) generated to calculate shoreline change rates
This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the exposed north coast of Alaska coastal region between Point Barrow and Icy Cape for the time period 1947 to 2012. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates. |
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Shorelines of the Eastern Beaufort Sea, Alaska coastal region (U.S. Canadian Border to the Hulahula River) used in shoreline change analysis
This dataset includes shorelines from 63 years ranging from 1947 to 2010 for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Shorelines were compiled from topographic survey sheets (T-sheets; National Oceanic and Atmospheric Administration (NOAA)), aerial orthophotographs (U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA), satellite imagery (U.S. Fish and Wildlife Service (USFWS), State of Alaska), and lidar elevation data (USGS). ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term Linear Regression Rate Calculations for the Sheltered East Beaufort Sea coast of Alaska between the U.S. Canadian Border and the Hulahula River
This dataset consists of short-term (~32 years) shoreline change rates for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1978 and 2010. A reference baseline was ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Sheltered East Beaufort Sea coast of Alaska between the U.S. Canadian Border and the Hulahula River
This dataset consists of long-term (~63 years) shoreline change rates for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2010. A reference baseline was ... |
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Offshore baseline for the sheltered East Beaufort Sea, Alaska coastal region (U.S. Canadian Border to the Hulahula River) generated to calculate shoreline change rates
This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the sheltered north coast of Alaska coastal region between the U.S. Canadian Border to the Hulahula River for the time period 1947 to 2010. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates. |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term Linear Regression Rate Calculations for the Exposed East Beaufort Sea coast of Alaska between the U.S. Canadian Border and the Hulahula River
This dataset consists of short-term (~32 years) shoreline change rates for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1978 and 2010. A reference baseline was ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Exposed East Beaufort Sea coast of Alaska between the U.S. Canadian Border and the Hulahula River
This dataset consists of long-term (~63 years) shoreline change rates for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2010. A reference baseline was ... |
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Offshore baseline for the exposed East Beaufort Sea, Alaska coastal region (U.S. Canadian Border to the Hulahula River) generated to calculate shoreline change rates
This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the exposed north coast of Alaska coastal region between the U.S. Canadian Border to the Hulahula River for the time period 1947 to 2010. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates. |
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Shorelines of the Central Beaufort Sea, Alaska coastal region (Hulahula River to the Colville River) used in shoreline change analysis
This dataset includes shorelines from 63 years ranging from 1947 to 2010 for the north coast of Alaska between the Hulahula River and the Colville River. Shorelines were compiled from topographic survey sheets (T-sheets; National Oceanic and Atmospheric Administration (NOAA)), aerial orthophotographs (U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA), Conoco-Philips (CP), British Petroleum Alaska (BPXA)), satellite imagery (State of Alaska), and lidar elevation data (USGS). ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term Linear Regression Rate Calculations for the Sheltered Central Beaufort Sea coast of Alaska between the Hulahula River and the Colville River
This dataset consists of short-term (~31 years) shoreline change rates for the north coast of Alaska between the Hulahula River and the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2010. A reference baseline was used as ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Sheltered Central Beaufort Sea coast of Alaska between the Hulahula River and the Colville River
This dataset consists of long-term (~63 years) shoreline change rates for the north coast of Alaska between the Hulahula River and the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2010. A reference baseline was used as ... |
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Offshore baseline for the sheltered Central Beaufort Sea, Alaska coastal region (Hulahula River to the Colville River) generated to calculate shoreline change rates
This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the sheltered north coast of Alaska coastal region between the Hulahula River and the Colville River for the time period 1947 to 2010. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates. |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term Linear Regression Rate Calculations for the Exposed Central Beaufort Sea coast of Alaska between the Hulahula River and the Colville River
This dataset consists of short-term (~31 years) shoreline change rates for the north coast of Alaska between the Hulahula River and the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2010. A reference baseline was used as ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Exposed Central Beaufort Sea coast of Alaska between the Hulahula River and the Colville River
This dataset consists of long-term (~63 years) shoreline change rates for the north coast of Alaska between the Hulahula River and the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2010. A reference baseline was used as ... |
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Offshore baseline for the exposed Central Beaufort Sea, Alaska coastal region (Hulahula River to the Colville River) generated to calculate shoreline change rates
This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the exposed north coast of Alaska coastal region between the Hulahula River and the Colville River for the time period 1947 to 2010. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates. |
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Water temperature time-series data from nearshore coral reef and anchialine pool locations along the west coast of Hawaii Island (2010-2013)
Time-series data of water temperature were collected at 33 locations along the west coast of the Island of Hawaii, including within Kaloko-Honokohau National Historical Park (KAHO), and Puu o Honaunau National Historical Park (PUHO) between 2010 and 2013 in nearshore coral reef and anchialine pool settings. Temperature sensors were attached to fossil limestone, rock or dead coral within otherwise healthy coral reef settings spanning water depths of 0.1 to 8.84 m (0.3 to 29.0 ft). Continuous measurements ... |
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Water level, temperature, and salinity time-series data from nearshore coral reef locations along the west coast of Hawaii Island (2010-2011)
Time-series data of water level, water temperature, and salinity were collected at 10 locations along west Hawaii Island between 2010 and 2011 in nearshore coral reef settings. Conductivity-temperature-depth sensors were attached to fossil limestone, rock, or dead coral within otherwise healthy coral reef settings spanning water depths of 8 to 23 ft. Continuous measurements were made every 10 or 20 minutes. |
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Surface-water temperature, salinity, pH, dissolved oxygen, and turbidity data from nearshore coral reef locations along the west coast of Hawaii Island (2010-2013)
Spatial measurements of water temperature, specific conductance, salinity, pH, dissolved oxygen, and turbidity between 0.25 and 0.50 m water depth were collected every 10-seconds along and across shore at 12 principal study areas along west and east Hawaii Island. Measurements were made between 2010 and 2013 during different seasons and tide states over the course of 1.0 to 2.5 hours to evaluate the spatial and temporal extent of water properties that influence coral reef health and coral reef habitat ... |
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Conductivity, temperature, and depth (CTD) data from nearshore coral reef locations along the west coast of Hawaii Island (2010-2014)
Conductivity-Temperature-Depth (CTD) profile data were collected along transects across study areas of west and east Hawaii Island between 2010 and 2014. Measurements were made over a range of tide and weather conditions and help characterize the spatial extent and variability in estuarine conditions across the reef when grouped by 1 to 2-hour survey period or by season. Sites of cold and warm groundwater discharge along east Hawaii were characterized for comparison. |
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Underwater video footage, March 2014, Faga'alu Bay, Tutuila Island, American Samoa
Underwater video imagery was collected in March 2014 in the nearshore waters of Faga'alu Bay on the Island of Tutuila, American Samoa, as part of the U.S. Geological Survey Coastal and Marine Geology Program's Pacific Coral Reefs Project. Included here are 40 video files in .mpg format and an Environmental Systems Research Institute (ESRI) shapefile with location (navigation) points every two seconds. |
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GNSS locations of lakebed images collected near Dollar Point, Lake Tahoe, CA, March 10 and 11, 2021
This text file (2021-607-FA_Image_Locations.txt) provides the GNSS antenna location for underwater images collected near Dollar Point, Lake Tahoe, CA, using a recently developed towed-surface vehicle with multiple downward-looking underwater cameras. The GNSS antenna location for the time of each image capture is presented with greater precision than is stored in the individual image’s EXIF header due to decimal place limitations of the EXIF format. |
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CMECS substrate, geoform, and biotic component polygons derived from multibeam echosounder data and underwater video observations collected offshore of south-central California in support of the Bureau of Ocean Energy Management Cal DIG I, offshore alternative energy project
These metadata describe Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data Committee, 2012) attributed polygons derived from multibeam echosounder acoustic bathymetry and backscatter intensity data, and from underwater video collected offshore of Morro Bay, California from 2016 to 2020. The polygons have CMECS substrate, geoform and biotic component attributes. Most of the data were collected in support of the U.S. Geological Survey (USGS)/Bureau of Ocean Energy Management ... |
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Substrate properties for invertebrate comparisons in Bellingham Bay, Washington, July 2019 and July-August 2020
Sediment grain-size distributions and total organic carbon contents were measured at four intertidal sites and three subtidal sites along the urban waterfront (east shore) of Bellingham Bay, Washington, July 3-11, 2019 and June 6-August 31, 2020. Intertidal substrate was sampled in eelgrass beds, and subtidal substrate was sampled inside and outside of the deep edge of eelgrass beds. |
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Survey of sites for the presence of the nonindigenous benthic foraminifera Trochammina hadai along the west coast of North America from 1930 to 2022
Results of a survey of samples collected from 1930 to 2022 along the west coast of the United States from Alaska to San Diego, California as well as Honolulu, Hawaii for the presence of the Asian nonindigenous benthic foraminifera Trochammina hadai. |
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Unprocessed aerial imagery from 31 August 2024 coastal survey of Washington.
This is a set of 6976 oblique aerial photogrammetric images and their derivatives, collected from Juan de Fuca Strait to Grays Harbor with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 6 July 2024 coastal survey of Washington.
This is a set of 7809 oblique aerial photogrammetric images and their derivatives, collected from Salish Sea with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 29 August 2022 coastal survey of Washington.
This is a set of 4281 oblique and near nadir aerial photogrammetric images and their derivatives, collected from Elwha river mouth to Ediz Hook CG with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the ... |
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