Lidar point clouds (LPC), elevation models, GPS data, image mosaics, and aerial images from thermal infra-red (TIR) and natural color (RGB) cameras collected during UAS operations at Lower Darby Creek, Darby Township, Pennsylvania, March 13 to 17, 2024

Metadata also available as - [Outline] - [Parseable text] - [XML]

Frequently anticipated questions:

What does this data set describe?

Title:
Lidar point clouds (LPC), elevation models, GPS data, image mosaics, and aerial images from thermal infra-red (TIR) and natural color (RGB) cameras collected during UAS operations at Lower Darby Creek, Darby Township, Pennsylvania, March 13 to 17, 2024
Abstract:
The U.S. Geological Survey deployed small uncrewed aircraft systems (sUAS) to collect aerial remote sensing data across sites within the Lower Darby Creek Superfund Site and the adjacent John Heinz National Wildlife Refuge (JHNWR) ~5 miles outside of Philadelphia, PA in March and August of 2024. March datasets include aerial images from natural color (RGB) and thermal infra-red (TIR) sensors across the JHNWR and adjacent tributaries as well as the nearby Clearview Landfill within the superfund site. August datasets include aerial images from natural color (RGB), thermal-infrared (TIR), multispectral sensors, and raw lidar over the Clearview Landfill only. These datasets were processed to produce high resolution digital elevation models (DEM), image mosaics, and lidar point clouds (LPC). Black and white cross-coded ground control points (GCPs) were surveyed using Real Time Kinematic (RTK) GPS and RTK-GPS enabled AeroPoints to georeference the model and orthomosaics during post-processing. The elevation and imagery products were produced to help partners at the Environmental Protection Agency (EPA) and U.S. Fish and Wildlife Service (USFWS) acquire accurate elevation data for target sites during the winter "leaf-off" period (March) and monitor changes in vegetation cover during peak growing season (August) building a baseline conditions dataset starting in August 2023. The March field collection included more baseline lidar data for additional large swaths of the National Wildlife Refuge as well as the thermal imagery dataset, which is the only planned thermal survey, and as a result took several days to complete. Although lidar was collecting during the August field effort, the focus was for vegetation at the Clearview Landfill and so only required one day of surveying. Future data collections are planned to support long-term monitoring of landscape change resulting from remediation efforts and potential storm impacts.
Supplemental_Information:
These data were collected by the USGS Coastal and Marine Hazards and Resources Program under USGS field activity number 2024-006-FA. The field activity webpage (https://cmgds.marine.usgs.gov/services/activity.php?fan=2024-006-FA) contains additional information regarding the field activity.
  1. How might this data set be cited?
    Cramer, Jennifer M., Brosnahan, Sandra M., Ackerman, Seth D., Over, Jin-Si R., Millo, Amit, Gazoorian, Christopher L., and Kelley, David J., 20250710, Lidar point clouds (LPC), elevation models, GPS data, image mosaics, and aerial images from thermal infra-red (TIR) and natural color (RGB) cameras collected during UAS operations at Lower Darby Creek, Darby Township, Pennsylvania, March 13 to 17, 2024: data release DOI:10.5066/P134HU3Y, U.S. Geological Survey, Coastal and Marine Hazards and Resources Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:

    This is part of the following larger work.

    Cramer, Jennifer M., Brosnahan, Sandra M., Ackerman, Seth D., Over, Jin-Si R., Millo, Amit, Gazoorian, Christopher L., and Kelley, David J., 2025, Topographic data, aerial imagery, and GPS data collected during uncrewed aircraft system (UAS) operations at Lower Darby Creek, Darby Township, Pennsylvania, March to August 2024: data release DOI:10.5066/P134HU3Y, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    Cramer, J.M., Brosnahan, S.M., Ackerman, S.D., Over, J.R., Millo, A., Gazoorian, C.L., and Kelley, D.J., 2025, Topographic data, aerial imagery, and GPS data collected during uncrewed aircraft system (UAS) operations at Lower Darby Creek, Darby Township, Pennsylvania, March to August 2024: U.S. Geological Survey data release, https://doi.org/10.5066/P134HU3Y
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -75.29640196
    East_Bounding_Coordinate: -75.24956276
    North_Bounding_Coordinate: 39.90817160
    South_Bounding_Coordinate: 39.87326301
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/676446dcd34e5335adadf37a?name=2024006FA_March_browse.jpg&allowOpen=true (JPEG)
    Landscape view of the Clearview Landfill in the Darby Creek Superfund Site in March 2024.
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 13-Mar-2024
    Ending_Date: 17-Mar-2024
    Currentness_Reference:
    Ground condition
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: digital image, point cloud, raster, and tabular digital data
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
    2. What coordinate system is used to represent geographic features?
      Grid_Coordinate_System_Name: Universal Transverse Mercator
      Universal_Transverse_Mercator:
      UTM_Zone_Number: 18
      Transverse_Mercator:
      Scale_Factor_at_Central_Meridian: 0.999600
      Longitude_of_Central_Meridian: -75.000000
      Latitude_of_Projection_Origin: 0.000000
      False_Easting: 500000.000000
      False_Northing: 0.000000
      Planar coordinates are encoded using row and column
      Abscissae (x-coordinates) are specified to the nearest 0.001
      Ordinates (y-coordinates) are specified to the nearest 0.001
      Planar coordinates are specified in meters
      The horizontal datum used is North American Datum of 1983 (National Spatial Reference System 2011).
      The ellipsoid used is GRS_1980.
      The semi-major axis of the ellipsoid used is 6378137.0.
      The flattening of the ellipsoid used is 1/298.257222101.
      Vertical_Coordinate_System_Definition:
      Altitude_System_Definition:
      Altitude_Datum_Name: North American Vertical Datum of 1988
      Altitude_Resolution: 0.001
      Altitude_Distance_Units: meters
      Altitude_Encoding_Method:
      Explicit elevation coordinate included with horizontal coordinates
  7. How does the data set describe geographic features?
    2024006FA_Clearview_Mar2024_YSMP_ImageLocs.csv
    The CSV file contains the approximate position of the YSMP images at the moment of each capture based on post-processed UAS integrated GPS. (Source: producer defined)
    SourceFile
    File names of individual images, see the Process Description for file naming convention. (Source: USGS) Character string.
    PreservedFileName
    File names copied from the SourceFile tag to preserve the original file name once image is uploaded to the Imagery Data System (IDS). (Source: USGS) Character string.
    GPSMapDatum
    The EPSG code for the coordinate system of the images. (Source: Processor defined) Character string.
    GPSLatitude
    Latitude (x) in WGS84 of camera based on time of each image capture. Positive values represent north coordinates. (Source: USGS)
    Range of values
    Minimum:39.89850
    Maximum:39.90766
    Units:decimal degrees
    GPSLongitude
    Longitude (y) in WGS84 of camera based on time of each image capture. Negative values represent west coordinates. (Source: USGS)
    Range of values
    Minimum:-75.25779
    Maximum:-75.25015
    Units:decimal degrees
    Map Datum (UTM)
    The geographic coordinate system of the image locations transformed to NAD83(2011) UTM coordinates. (Source: Processor defined) Character string.
    Easting
    Easting coordinate in NAD83(2011) / UTM zone 18N of the image in meters. (Source: USGS)
    Range of values
    Minimum:477964.0382
    Maximum:478618.6638
    Units:meter
    Northing
    Northing coordinate in NAD83(2011) / UTM zone 18N of the image in meters. (Source: USGS)
    Range of values
    Minimum:4416521.5990
    Maximum:4417537.6750
    Units:meter
    2024006FA_Darby_Mar2024_XT2_ImageLocs.csv
    The CSV file contains the approximate position of the XT2 images at the moment of each capture based on camera-integrated GPS. (Source: producer defined)
    SourceFile
    File names of individual images, see the Process Description for file naming convention. (Source: USGS) Character string.
    PreservedFileName
    File names copied from the SourceFile tag to preserve the original file name once image is uploaded to the Imagery Data System (IDS). (Source: USGS) Character string.
    GPSMapDatum
    The EPSG code for the coordinate system of the images. (Source: Processor defined) Character string.
    GPSLatitude
    Latitude (x) in WGS84 of camera based on time of each image capture. Positive values represent north coordinates. (Source: USGS)
    Range of values
    Minimum:39.87803
    Maximum:39.89853
    Units:decimal degrees
    GPSLongitude
    Longitude (y) in WGS84 of camera based on time of each image capture. Negative values represent west coordinates. (Source: USGS)
    Range of values
    Minimum:-75.29668
    Maximum:-75.25533
    Units:decimal degrees
    Map Datum (UTM)
    The geographic coordinate system of the image locations transformed to NAD83(2011) UTM coordinates. (Source: Processor defined) Character string.
    Easting
    Easting coordinate in NAD83(2011) / UTM zone 18N of the image in meters. (Source: USGS)
    Range of values
    Minimum:474630.9266
    Maximum:478172.7649
    Units:meter
    Northing
    Northing coordinate in NAD83(2011) / UTM zone 18N of the image in meters. (Source: USGS)
    Range of values
    Minimum:4414260.4970
    Maximum:4416525.3460
    Units:meter
    2024006FA_Heinz_Henderson_Mar2024_YSMP_ImageLocs.csv
    The CSV file contains the approximate position of the XT2 images at the moment of each capture based on camera-integrated GPS. (Source: producer defined)
    SourceFile
    File names of individual images, see the Process Description for file naming convention. (Source: USGS) Character string.
    PreservedFileName
    File names copied from the SourceFile tag to preserve the original file name once image is uploaded to the Imagery Data System (IDS). (Source: USGS) Character string.
    GPSMapDatum
    The EPSG code for the coordinate system of the images. (Source: Processor defined) Character string.
    GPSLatitude
    Latitude (x) in WGS84 of camera based on time of each image capture. Positive values represent north coordinates. (Source: USGS)
    Range of values
    Minimum:39.87354
    Maximum:39.88534
    Units:decimal degrees
    GPSLongitude
    Longitude (y) in WGS84 of camera based on time of each image capture. Negative values represent west coordinates. (Source: USGS)
    Range of values
    Minimum:-75.29598
    Maximum:-75.26828
    Units:decimal degrees
    Map Datum (UTM)
    The geographic coordinate system of the image locations transformed to NAD83(2011) UTM coordinates. (Source: Processor defined) Character string.
    Easting
    Easting coordinate in NAD83(2011) / UTM zone 18N of the image in meters. (Source: USGS)
    Range of values
    Minimum:474689.5813
    Maximum:475416.4908
    Units:meter
    Northing
    Northing coordinate in NAD83(2011) / UTM zone 18N of the image in meters. (Source: USGS)
    Range of values
    Minimum:4413762.2450
    Maximum:4414604.3660
    Units:meter
    2024006FA_Heinz_LowerImpoundment_Mar2024_YSMP_ImageLocs.csv
    The CSV file contains the approximate position of the XT2 images at the moment of each capture based on camera-integrated GPS. (Source: producer defined)
    SourceFile
    File names of individual images, see the Process Description for file naming convention. (Source: USGS) Character string.
    PreservedFileName
    File names copied from the SourceFile tag to preserve the original file name once image is uploaded to the Imagery Data System (IDS). (Source: USGS) Character string.
    GPSMapDatum
    The EPSG code for the coordinate system of the images. (Source: Processor defined) Character string.
    GPSLatitude
    Latitude (x) in WGS84 of camera based on time of each image capture. Positive values represent north coordinates. (Source: USGS)
    Range of values
    Minimum:39.87709
    Maximum:39.89517
    Units:decimal degrees
    GPSLongitude
    Longitude (y) in WGS84 of camera based on time of each image capture. Negative values represent west coordinates. (Source: USGS)
    Range of values
    Minimum:-75.26600
    Maximum:-75.25375
    Units:decimal degrees
    Map Datum (UTM)
    The geographic coordinate system of the image locations transformed to NAD83(2011) UTM coordinates. (Source: Processor defined) Character string.
    Easting
    Easting coordinate in NAD83(2011) / UTM zone 18N of the image in meters. (Source: USGS)
    Range of values
    Minimum:477317.4036
    Maximum:478303.0604
    Units:meter
    Northing
    Northing coordinate in NAD83(2011) / UTM zone 18N of the image in meters. (Source: USGS)
    Range of values
    Minimum:4414147.7490
    Maximum:4414989.1950
    Units:meter
    2024006FA_Heinz_TurkeyFoot_Mar2024_YSMP_ImageLocs.csv
    The CSV file contains the approximate position of the XT2 images at the moment of each capture based on camera-integrated GPS. (Source: producer defined)
    SourceFile
    File names of individual images, see the Process Description for file naming convention. (Source: USGS) Character string.
    PreservedFileName
    File names copied from the SourceFile tag to preserve the original file name once image is uploaded to the Imagery Data System (IDS). (Source: USGS) Character string.
    GPSMapDatum
    The EPSG code for the coordinate system of the images. (Source: Processor defined) Character string.
    GPSLatitude
    Latitude (x) in WGS84 of camera based on time of each image capture. Positive values represent north coordinates. (Source: USGS)
    Range of values
    Minimum:39.87649
    Maximum:39.88956
    Units:decimal degrees
    GPSLongitude
    Longitude (y) in WGS84 of camera based on time of each image capture. Negative values represent west coordinates. (Source: USGS)
    Range of values
    Minimum:-75.27892
    Maximum:-75.26188
    Units:decimal degrees
    Map Datum (UTM)
    The geographic coordinate system of the image locations transformed to NAD83(2011) UTM coordinates. (Source: Processor defined) Character string.
    Easting
    Easting coordinate in NAD83(2011) / UTM zone 18N of the image in meters. (Source: USGS)
    Range of values
    Minimum:476151.9587
    Maximum:477242.6832
    Units:meter
    Northing
    Northing coordinate in NAD83(2011) / UTM zone 18N of the image in meters. (Source: USGS)
    Range of values
    Minimum:4414083.9320
    Maximum:4415396.5280
    Units:meter
    2024006FA_Clearview_Mar2024_AeroPoint.csv
    Ground control point positions, elevations, and attributes (Source: USGS)
    FAN
    USGS Field Activity Number (Source: USGS)
    ValueDefinition
    2024-006-FAYear, USGS ID, and Field Activity
    Date
    Calendar date of collection (Source: USGS)
    ValueDefinition
    20240315YYYYMMDD
    Point ID
    Unique point identification number. (Source: Processor defined)
    Range of values
    Minimum:1
    Maximum:10
    Attributes
    Unique identifier for individual AeroPoints. (Source: producer defined) Character string.
    Latitude NAD83[2011]
    Post-processed latitude of AeroPoint position (NAD83[2011]). (Source: USGS)
    Range of values
    Minimum:39.89955115
    Maximum:39.90604844
    Units:decimal degrees
    Longitude NAD83[2011]
    Post-processed longitude of AeroPoint position (NAD83[2011]). (Source: None)
    Range of values
    Minimum:-75.25712478
    Maximum:-75.25208233
    Units:decimal degrees
    Ellipsoid NAD83[2011]
    Post-processed height in meters of AeroPoint in relation to the NAD83(2011) reference ellipsoid. (Source: None)
    Range of values
    Minimum:-29.865
    Maximum:-1.520
    Units:meters
    Northing 18N
    Post-processed interpolated Y-coordinate of AeroPoint in NAD83(2011)/UTM Zone 18N. (Source: USGS)
    Range of values
    Minimum:4416639.530
    Maximum:4417360.165
    Units:meters
    Easting 18N
    Post-processed interpolated X-coordinate of AeroPoint in NAD83(2011)/UTM Zone 18N. (Source: USGS)
    Range of values
    Minimum:478020.646
    Maximum:478452.156
    Units:meters
    Orthometric NAVD88
    Post-processed Z-coordinate of AeroPoint using NAVD88 with Geoid 18 applied. (Source: USGS)
    Range of values
    Minimum:3.098
    Maximum:31.445
    Units:meters
    Xvar mm
    Internal variance in the X-coordinate from post-processing. No data value is NaN. (Source: producer defined)
    Range of values
    Minimum:2.0
    Maximum:5.1
    Units:millimeters
    Yvar mm
    Internal variance in the Y-coordinate from post-processing. No data value is NaN. (Source: producer defined)
    Range of values
    Minimum:2.4
    Maximum:4.5
    Units:millimeters
    Zvar mm
    Internal variance in the Z-coordinate from post-processing. No data value is NaN. (Source: producer defined)
    Range of values
    Minimum:2.6
    Maximum:6.0
    Units:millimeters
    Baseline distance km
    Distance to from the AeroPoint to the correcting base. (Source: producer defined)
    Range of values
    Minimum:0.08
    Maximum:3.99
    Units:kilometers
    2024006FA_Mar2024_Darby_SP80.csv
    SP80 RTK-GPS check point positions, elevations, and attributes. (Source: USGS)
    FAN
    USGS Field Activity Number (Source: USGS)
    ValueDefinition
    2024-006-FAYear, USGS ID, and Field Activity
    Date
    Calendar date of collection (Source: USGS)
    ValueDefinition
    20240317YYYYMMDD
    Point ID
    Unique point identification number. (Source: Processor defined)
    Range of values
    Minimum:1
    Maximum:75
    Attributes
    Identifies check point location. Heinz is the overall location, which is John Heinz National Wildlife Refuge, and a more specific location following the hyphen. (Source: producer defined) Character string.
    Latitude NAD83[2011]
    Real-time Kinematic latitude of GPS point (NAD83[2011]). (Source: USGS)
    Range of values
    Minimum:39.87541619
    Maximum:39.88010030
    Units:decimal degrees
    Longitude NAD83[2011]
    Real-time Kinematic longitude of GPS point (NAD83[2011]). (Source: None)
    Range of values
    Minimum:-75.29509387
    Maximum:-75.27530855
    Units:decimal degrees
    Ellipsoid NAD83[2011]
    Real-time Kinematic vertical position of GPS point in relation to the NAD83(2011) reference ellipsoid. (Source: None)
    Range of values
    Minimum:-33.224
    Maximum:-28.783
    Units:meters
    Easting 18N
    Real-time kinematic X-coordinate of GPS point in NAD83(2011)/UTM Zone 18N. (Source: USGS)
    Range of values
    Minimum:474765.1960
    Maximum:476457.7373
    Units:meters
    Northing 18N
    Real-time kinematic Y-coordinate of GPS point in NAD83(2011)/UTM Zone 18N. (Source: USGS)
    Range of values
    Minimum:4413969.6710
    Maximum:4414486.4070
    Units:meters
    Orthometric NAVD88
    Real-time kinematic Z-coordinate of GPS point relative to NAVD88 with Geoid 18 applied. (Source: USGS)
    Range of values
    Minimum:-0.251
    Maximum:4.181
    Units:meters
    XYvar m
    Internal variance in the XY-coordinate from post-processing. No data value is NaN. (Source: USGS)
    Range of values
    Minimum:0.007
    Maximum:0.386
    Units:millimeters
    Zvar m
    Internal variance in the Z-coordinate from post-processing. No data value is NaN. (Source: producer defined)
    Range of values
    Minimum:0.013
    Maximum:0.450
    Units:millimeters
    2024006FA_Clearview_Mar2024_YSMP_LPC.laz
    YSMP lidar point cloud in .laz file format from flights over the Clearview Landfill. This georeferenced point cloud was colorized using the natural color RGB orthomosaic and has classified ground points. Total point count is 98,854,481. The point density is 306.68 points per square meter, and point spacing is 0.057 m. (Source: producer defined)
    Elevation
    Surface elevation orthometric height NAVD88 (m) using Geoid 18 in NAD83(2011)/UTM Zone 18N. (Source: YellowScan CloudStation)
    Range of values
    Minimum:-0.406
    Maximum:34.644
    Units:meters
    Intensity
    Lidar intensity is recorded as the return strength of a laser beam during data collection. (Source: YellowScan CloudStation)
    Range of values
    Minimum:0
    Maximum:65,025
    2024006FA_Heinz_Henderson_Mar2024_YSMP_LPC.laz
    YSMP lidar point cloud in .laz file format from the westernmost area of the John Heinz National Wildlife Refuge. This georeferenced point cloud was colorized using the natural color RGB orthomosaic and has classified ground points. Total point count is 530,030,997. The point density is 490.68 points per square meter, and point spacing is 0.045 m. (Source: producer defined)
    Elevation
    Surface elevation orthometric height NAVD88 (m) using Geoid 18 in NAD83(2011)/UTM Zone 18N. (Source: YellowScan CloudStation)
    Range of values
    Minimum:-1.332
    Maximum:32.345
    Units:meters
    Intensity
    Lidar intensity is recorded as the return strength of a laser beam during data collection. (Source: YellowScan CloudStation)
    Range of values
    Minimum:0
    Maximum:65,025
    2024006FA_Heinz_TurkeyFoot_Mar2024_YSMP_LPC.laz
    YSMP lidar point cloud in .laz file format from the middle area of the John Heinz National Wildlife Refuge. This georeferenced point cloud was colorized using the natural color RGB orthomosaic and has classified ground points. Total point count is 720,272,716. The point density is 568.02 points per square meter, and point spacing is 0.042 m. (Source: producer defined)
    Elevation
    Surface elevation orthometric height NAVD88 (m) using Geoid 18 in NAD83(2011)/UTM Zone 18N. (Source: YellowScan CloudStation)
    Range of values
    Minimum:-0.488
    Maximum:35.000
    Units:meters
    Intensity
    Lidar intensity is recorded as the return strength of a laser beam during data collection. (Source: YellowScan CloudStation)
    Range of values
    Minimum:0
    Maximum:65,025
    2024006FA_Heinz_LowerImpoundment_Mar2024_YSMP_LPC.laz
    YSMP lidar point cloud in .laz file format from the eastern and northernmost area of the John Heinz National Wildlife Refuge. This georeferenced point cloud was colorized using the natural color RGB orthomosaic and has classified ground points. Total point count is 286,874,585. The point density is 617.08 points per square meter, and point spacing is 0.040 m. (Source: producer defined)
    Elevation
    Surface elevation orthometric height NAVD88 (m) using Geoid 18 in NAD83(2011)/UTM Zone 18N. (Source: YellowScan CloudStation)
    Range of values
    Minimum:-3.051
    Maximum:34.802
    Units:meters
    Intensity
    Lidar intensity is recorded as the return strength of a laser beam during data collection. (Source: YellowScan CloudStation)
    Range of values
    Minimum:0
    Maximum:65,025
    2024006FA_Clearview_Mar2024_YSMP_DSM_5cm_cog.tif
    A cloud-optimized digital surface model gridded from the "2024006FA_Clearview_Mar2024_YSMP_LPC" lidar point cloud with encoded elevation values. Pixel resolution is 5 cm. (Source: USGS)
    Value
    Surface elevation orthometric height NAVD88 (m) using Geoid 2018 in NAD83(2011) UTM Zone 18N. (Source: producer defined)
    Range of values
    Minimum:-0.406
    Maximum:34.644
    Units:meters
    2024006FA_Clearview_Mar2024_YSMP_DTM_5cm_cog.tif
    A cloud-optimized digital terrain model gridded from the "2024006FA_Clearview_Mar2024_YSMP_LPC" lidar point cloud ground classified points with encoded elevation values. Pixel resolution is 5 cm. (Source: USGS)
    Value
    Surface elevation orthometric height NAVD88 (m) using Geoid 2018 in NAD83(2011) UTM Zone 18N. (Source: producer defined)
    Range of values
    Minimum:-0.154
    Maximum:32.059
    Units:meters
    2024006FA_Heinz_Henderson_Mar2024_YSMP_DSM_5cm_cog.tif
    A cloud-optimized digital surface model gridded from the "2024006FA_Heinz_Henderson_Mar2024_YSMP_LPC" lidar point cloud with encoded elevation values. Pixel resolution is 5 cm. (Source: USGS)
    Value
    Surface elevation orthometric height NAVD88 (m) using Geoid 2018 in NAD83(2011) UTM Zone 18N. (Source: producer defined)
    Range of values
    Minimum:-1.305
    Maximum:32.345
    Units:meters
    2024006FA_Heinz_Henderson_Mar2024_YSMP_DTM_5cm_cog.tif
    A cloud-optimized digital terrain model gridded from the "2024006FA_Heinz_Henderson_Mar2024_YSMP_LPC" lidar point cloud ground classified points with encoded elevation values. Pixel resolution is 5 cm. (Source: USGS)
    Value
    Surface elevation orthometric height NAVD88 (m) using Geoid 2018 in NAD83(2011) UTM Zone 18N. (Source: producer defined)
    Range of values
    Minimum:-1.332
    Maximum:20.259
    Units:meters
    2024006FA_Heinz_TurkeyFoot_Mar2024_YSMP_DSM_5cm_cog.tif
    A cloud-optimized digital surface model gridded from the "2024006FA_Heinz_TurkeyFoot_Mar2024_YSMP_LPC" lidar point cloud with encoded elevation values. Pixel resolution is 5 cm. (Source: USGS)
    Value
    Surface elevation orthometric height NAVD88 (m) using Geoid 2018 in NAD83(2011) UTM Zone 18N. (Source: producer defined)
    Range of values
    Minimum:-0.488
    Maximum:35.000
    Units:meters
    2024006FA_Heinz_TurkeyFoot_Mar2024_YSMP_DTM_5cm_cog.tif
    A cloud-optimized digital terrain model gridded from the "2024006FA_Heinz_TurkeyFoot_Mar2024_YSMP_LPC" lidar point cloud ground classified points with encoded elevation values. Pixel resolution is 5 cm. (Source: USGS)
    Value
    Surface elevation orthometric height NAVD88 (m) using Geoid 2018 in NAD83(2011) UTM Zone 18N. (Source: producer defined)
    Range of values
    Minimum:-0.488
    Maximum:13.905
    Units:meters
    2024006FA_Heinz_LowerImpoundment_Mar2024_YSMP_DSM_5cm_cog.tif
    A cloud-optimized digital surface model gridded from the "2024006FA_Heinz_LowerImpoundment_Mar2024_YSMP_LPC" lidar point cloud with encoded elevation values. Pixel resolution is 5 cm. (Source: USGS)
    Value
    Surface elevation orthometric height NAVD88 (m) using Geoid 2018 in NAD83(2011) UTM Zone 18N. (Source: producer defined)
    Range of values
    Minimum:-2.245
    Maximum:34.802
    Units:meters
    2024006FA_Heinz_LowerImpoundment_Mar2024_YSMP_DTM_5cm_cog.tif
    A cloud-optimized digital terrain model gridded from the "2024006FA_Heinz_LowerImpoundment_Mar2024_YSMP_LPC" lidar point cloud ground classified points with encoded elevation values. Pixel resolution is 5 cm. (Source: USGS)
    Value
    Surface elevation orthometric height NAVD88 (m) using Geoid 2018 in NAD83(2011) UTM Zone 18N. (Source: producer defined)
    Range of values
    Minimum:-3.051
    Maximum:14.329
    Units:meters
    2024006FA_Clearview_Mar2024_YSMP_Ortho_5cm_cog.tif
    natural color (RGB) cloud optimized orthomosaic made from the YSMP images over the Clearview Landfill. (Source: USGS)
    Band_1
    Red wavelength band (Source: Agisoft Metashape)
    Range of values
    Minimum:0
    Maximum:255
    Band_2
    Green wavelength band (Source: Agisoft Metashape)
    Range of values
    Minimum:0
    Maximum:255
    Band_3
    Blue wavelength band (Source: Agisoft Metashape)
    Range of values
    Minimum:0
    Maximum:255
    2024006FA_Clearview_Mar2024_XT2c_Ortho_5cm_cog.tif
    natural color (RGB) cloud optimized orthomosaic made from the XT2 natural color (RGB) images over the Clearview Landfill within the Lower Darby Creek Superfund Site (Source: USGS)
    Band_1
    Red wavelength band (Source: Agisoft Metashape)
    Range of values
    Minimum:0
    Maximum:255
    Band_2
    Green wavelength band (Source: Agisoft Metashape)
    Range of values
    Minimum:0
    Maximum:255
    Band_3
    Blue wavelength band (Source: Agisoft Metashape)
    Range of values
    Minimum:0
    Maximum:255
    2024006FA_Clearview_Mar2024_XT2t_Ortho_5cm_cog.tif
    Thermal infra-red cloud optimized orthomosaic made from the XT2 thermal infra-red (TIR) images over the Clearview Landfill within the Lower Darby Creek Superfund Site. Pixel values are in units of degrees fahrenheit. (Source: USGS)
    Band_1
    Thermal infra-red (TIR) wavelength band (Source: Agisoft Metashape)
    Range of values
    Minimum:-27.874
    Maximum:61.035
    2024006FA_Heinz_Mar2024_XT2c_Ortho_5cm_cog.tif
    natural color (RGB) cloud optimized orthomosaic made from the XT2 natural color (RGB) images over the Darby Creek channel and tributaries within the John Heinz National Wildlife Refuge. (Source: USGS)
    Band_1
    Red wavelength band (Source: Agisoft Metashape)
    Range of values
    Minimum:0
    Maximum:255
    Band_2
    Green wavelength band (Source: Agisoft Metashape)
    Range of values
    Minimum:0
    Maximum:255
    Band_3
    Blue wavelength band (Source: Agisoft Metashape)
    Range of values
    Minimum:0
    Maximum:255
    2024006FA_Heinz_Mar2024_XT2t_Ortho_5cm_cog.tif
    Thermal infra-red (TIR) cloud optimized orthomosaic made from the XT2 TIR images over the Darby Creek channel and tributaries within the John Heinz National Wildlife Refuge. Pixel values are in units of degrees Fahrenheit. (Source: USGS)
    Band_1
    Thermal infra-red (TIR) wavelength band (Source: Agisoft Metashape)
    Range of values
    Minimum:-27.874
    Maximum:61.035
    Entity_and_Attribute_Overview:
    The filenames are formatted as "FAN_Location_MonthYear_Sensor_Product_Resolution_cog.*", where FAN is the USGS field activity number, location is the specific location the data represents; sensor includes the YellowScan Mapper Plus (YSMP), the DJI Zenmuse XT2 (XT2), the Spectra-Precision 80 RTK-GPS (SP80), and AeroPoints; products include structure from motion (SfM) orthomosaics (ortho), digital surface models (DSM), and lidar point cloud (LPC). The horizontal coordinate reference system for all products is NAD83(2011)/UTM18N, the vertical coordinate reference system (VCRS) is NAVD88 using Geoid 18. Image location coordinate reference systems are specific to the sensor and can be viewed in the image locations CSV files.
    Entity_and_Attribute_Detail_Citation: USGS Field Activity 2024-006-FA

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Jennifer M. Cramer
    • Sandra M. Brosnahan
    • Seth D. Ackerman
    • Jin-Si R. Over
    • Amit Millo
    • Christopher L. Gazoorian
    • David J. Kelley
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    Jennifer M. Cramer
    U.S. Geological Survey, Northeast Region, Woods Hole Coastal and Marine Science Center
    Geographer
    384 Woods Hole Rd.
    Woods Hole, MA

    508-548-8700 x2314 (voice)
    jcramer@usgs.gov

Why was the data set created?

Lidar data were collected to penetrate vegetation canopy and provide accurate digital terrain models (DTMs) during the winter "leaf-off" period. Aerial imagery was collected with appropriate resolution and overlap to permit high-quality photogrammetry and generation of digital surface models (DSM) and orthoimagery. TIR imagery was collected over channels within the Wildlife Refuge to identify potential groundwater seeps.

How was the data set created?

  1. From what previous works were the data drawn?
  2. How were the data generated, processed, and modified?
    Date: 17-Mar-2024 (process 1 of 8)
    RTK-GPS Base Station and Rover: A Spectra Precision model SP80 GNSS base station receiving real-time differential corrections from the satellites was set up to collect positions in Receiver Independent Exchange (RINEX) format at 1 hz on a known point prior to and for the duration of lidar data surveys. The base station was operating every day of field collection between 3/13/2024 - 3/17/2024. A SP80 rover receiving real-time differential corrections from the Pennsylvania CORS network was used to survey points across the field area, including ground position validation points on 3/17/2024. The RTK receivers for both the base and rover are linked via Bluetooth to a handheld data collector (Carlson CHC LT30 Handheld Terminal running Carlson SurvCE v. 4.06 software under Windows Mobile v. 6.1 Professional operating system). Rover antennas were mounted on 2 m survey rods with bubble levels and 5 cm (2 inch) sand feet. Conversions from satellite coordinates to NAD83(2011) UTM zone 18N (EPSG::6347) and NAVD88 (EPSG::5703) were made by Carlson SurvCE software in the data collector.
    Date: 15-Mar-2024 (process 2 of 8)
    Ground control: AeroPoint targets were emplaced on flat, stable surfaces, with clear view of the sky and left undisturbed, collecting data for at least 2 hours. AeroPoint data was uploaded via a WiFi connection to a user defined account on propelleraero.com. The raw data are processed by Propeller and exported to a CSV file in NAD83(2011) UTM zone 18N (EPSG::6347) for horizontal and NAVD88 (geoid 18) (EPSG::5703) for vertical.
    Date: 17-Mar-2024 (process 3 of 8)
    Lidar System: A YellowScan Mapper Plus (YSMP) high-density lidar system containing a lidar sensor and natural color (RGB) camera module was mounted to a DJI Matrice 600 (M600) uncrewed aircraft system (UAS) to collect low-altitude aerial lidar point cloud (LPC) data and simultaneous overlapping natural color (RGB) images. Lidar flights occurred between 3/13/2024 and 3/17/2024. A configuration text file (CONFIG.TXT) is pre-loaded onto the lidar USB thumb drive and was edited to control lidar and camera module settings, including the camera triggering height, the camera triggering interval, and the lidar scan pattern. For this field area over marsh and forested terrain, a point density of ~300 points per square meter (ppsqm) was targeted with a non-repetitive (spirograph) scan pattern. The flight plans for this project targeted a swath overlap of 50% with the following flight parameters: altitude of 61 m, flight line spacing at 45 m, a velocity of 10 m/s, and a 2-second camera triggering interval. At these parameters, the natural color RGB camera module was set to trigger every 3 seconds to achieve 50% sidelap and forelap for colorization of the LPC in post-processing. For every lidar UAS flight, the following steps were followed to properly operate the system and collect data: After powering on the UAS and lidar system, the GPS, scanner, and camera module all must initialize. After takeoff, an additional initialization pattern must be manually flown by the pilot to signal to the IMU to begin collecting lidar data. This pattern consists of a forward, back, and forward flight path ending with a hook-shaped coordinated turn on the last forward maneuver. It is best practice that this is flown below the camera triggering altitude. Once the maneuver is completed, the UAS is ascended to the camera triggering altitude where the RGB camera module sets the ISO for the entire flight. It is recommended to make this altitude close to the flight plan altitude. The mission is uploaded to the UAS and it begins the automated flight plan. When the data collection is finished or batteries require swapping, the same initialization pattern flown at the beginning is flown again to de-initialize the scanner. The lidar data is saved to a 256 GB USB thumb drive in three different files: (1) the IMU+GPS data, decimated for quick post-processing, in binary *.ys format, (2) the scanner data in *.lvx format (~600 MB per minute of data collection), (3) and the complete IMU+GPS data in Applanix (Trimble) binary *.t04 format. The RGB images are saved to a 64 GB micro-SD card as *.jpeg files. The camera triggering time-interval was determined and set based on the focal length and ground sampling distance (GSD) of the camera as well as the altitude and speed of the UAS in order to achieve ~50% forelap between adjacent photos for colorizing the lidar point cloud. The camera triggering interval as well as the altitude at which the camera automatically sets the ISO for the scene is written into a configuration file located on a USB stick that is plugged into the YellowScan Mapper Plus system.
    Date: 16-Mar-2024 (process 4 of 8)
    Thermal Camera: Thermal infra-red (TIR) and natural color (RGB) aerial images were collected using a DJI Zenmuse XT2 camera mounted to a DJI M600 UAS. TIR and RGB imagery flights occurred between 3/13/2024 and 3/16/2024. The XT2 camera was set to high gain scene range, which has a higher sensitivity to temperature differences over a smaller range (-13 to 212 degrees Fahrenheit). The Darby Creek main channel and tributaries were surveyed with corridor type mapping flight plan design. Flight plans targeted a photo sidelap and forelap of 75%, sufficient for photogrammetric processing by following these flight parameters: 61 meters altitude, 3 m/s velocity, and a 3-second camera triggering interval. The TIR and RGB images were saved to a 128 GB micro-SD card as *.tiff and *.jpeg files, respectively.
    Date: 16-Mar-2024 (process 5 of 8)
    Lidar data processing: After each data collection, the three data files are stored on the USB thumb drive in a folder following a naming scheme of "YS-YYYYMMDD-HHMMSS" where YS is the acronym for YellowScan, YYYYMMDD is the date stamp, and HHMMSS is the time stamp in UTC time (e.g. YS-20230830-171402). Within this folder are the three files containing the IMU+GPS data in .ys and .t04 format and the scanner data in *.lvx format, which follow the same naming scheme as the parent folder. The RGB images are stored on the SD card following a naming scheme of DSC#####.JPG (e.g. DSC00001.JPG). Upon import of the raw scanner data (.ys file) for each flight to YellowScan CloudStation v. 2210.0.0, the sensor's Lidar (.profile) and Camera (.camera) profiles, provided by the vendor, are selected for the project and the project coordinate reference system is defined. CloudStation auto-identifies sensor position trajectories that are to be included in the model based on their length and linearity, but adjustments are usually required as the software will sometimes misidentify trajectories that should not be included, such as the path the UAS took to reach the first waypoint of the mission or leave out paths that are considered too short. If there is a slight waiver in a flight path, the software will sometimes cut off the ends of the flight paths. The .T04 file and base station GNSS RINEX file were used to correct and optimize the sensor position trajectories using th GNSS Inertial Processor and produce a Smoothed Best Estimate of Trajectory (SBET) file in .txt ASCII format, which represents the Post Processing Kinematic (PPK) Solution. The lever arm offsets and boresight angle corrections were applied to the LPC, along with a strip adjustment between transect swaths using CloudStation's "robust" setting. The LPC was then colorized using the images. The Cut Overlap function was applied to remove redundant points based on the closest parallel flight trajectory. The unclassified LPC model was then exported from CloudStation as a 1.4 LAZ file. The LPCs were brought into Global Mapper (v. 26.0) and manually cleaned by reclassifying or removing points interpreted to be noise, points that were either not classified or incorrectly classified as ground or are above a reasonable elevation threshold based on the surrounding features. The LPCs were exported as a 1.4 LAZ files. To produce the DSMs, the LPCs are gridded in Global Mapper using maximum values and exported to geotiff format. To produce DTMs, only the ground points are gridded using maximum values and exported to geotiff format. All files were exported in EPSG:6347 NAD83(2011)/UTM zone 18N and the vertical datum in EPSG:5703 NAVD88 using Geoid 18.
    Date: 16-Mar-2024 (process 6 of 8)
    Imagery processing: Telemetry navigation logs for each flight were exported from the Ignis app in GPX format and used to manually geotag the imagery from the YellowScan Mapper Plus camera modules in preparation for photogrammetric processing. Image timestamps were adjusted to UTC time depending on time zone and daylight saving. These corrections were done using the program ExifTool. ExifTool uses linear interpolation to determine the position of the device at the time recorded in the image. This creates values for tags GPSLatitude, GPS LatitudeRef, GPSLongitude, GPSLongitudeRef, GPSAltitude, GPSTimeStamp, GPSDateStamp. A sample of code used to geotag images: exiftool -v2 -geotag ../../telemetry/Nav_FlightLogs/Flight\ Logs\ GPX/flight_log_2022_10_10_14_02_42_AGL.gpx -geosync=+16 '-geotime<${DateTimeOriginal}-04:00' -P f05XT2c/*.JPG. All images were renamed to ensure unique filenames following the USGS Coastal and Marine Hazards and Resources Program's best practices for image naming convention: "FieldActivityNumber_f##sensorID_YYYYMMDDTHHMMSS_OriginalFilename.tif" (e.g. "2024006FA_f05XT2c_20240313T155702Z_DJI_0184.jpg") Field activity number is a unique identifier assigned to the field effort under which the data was collected (e.g. 2024006FA), f## denotes the flight in which the photos were taken (e.g. f05), sensor ID is the sensor or camera used to collect the imagery (e.g. XT2c = Zenmuse XT2 natural color RGB camera; XT2t = Zenmuse XT2 thermal infra-red TIR camera, YSMP = YellowScan Mapper Plus), 'YYYYMMDD' is the UTC date, 'HHMMSS' is UTC time and the 'T' is used to separate the UTC date from UTC time, and the original filename is appended to the end. To ensure compliance with USGS Coastal and Marine Hazards and Resources Program's best practices for image exif, exif tags were added using a CSV containing header information for each photo. A sample of the code used to edit the image tags using ExifTool version 12.52:
    'exiftool -csv="C:\directory\name\EXIF.csv" C:\directory\name\of\photos *.[ext]
    The following tags were added to the image exif: -IPTC:Credit="U.S. Geological Survey" -IPTC:Contact="WHSC_data_contact@usgs.gov" -EXIF:Copyright="Public Domain" -XMP:UsageTerms="Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty." -EXIF:ImageDescription="https://cmgds.marine.usgs.gov/fan_info.php?fan=2024-006-FA; Low-altitude aerial natural color photograph of the Lower Darby Creek Superfund Site and John Heinz National Wildlife Refuge, Darby Township, Pennsylvania, taken with a DJI XT2 thermal camera during USGS field activity 2024-006-FA" -XMP:AttributionURL="https://doi.org/10.5066/P134HU3Y" -EXIF:GPSAreaInformation="camera-integrated GPS" -EXIF:GPSMapDatum="EPSG:4326 (WGS 84)" -IPTC:keywords="UAS Aerial Imagery, John Heinz National Wildlife Refuge, Lower Darby Creek Superfund, Darby Township, Pennsylvania, 2023-006-FA, USGS, DJI Zenmuse XT2" -EXIF:Artist="WHCMSC AIM Group" -XMP:PreservedFilename>Filename.
    The images for this data release have been uploaded to the Imagery Data System (IDS), which renames the images to safeguard from accidental overwriting. A user can restore the preserved filename with ExifTool. It is recommended to test on a single image before running on all images. To test on a single image:
    exiftool "-XMP:PreservedFilename<Filename" filename.tif.
    Once desired output is confirmed, use this code to rename all images in the folder: exiftool "-Filename<XMP:PreservedFilename" -overwrite_original -P *.tif *note that the case of the image extension may matter (e.g. TIF vs tif).
    CSV files corresponding to each sensor set of photos containing image location information was generated using ExifTool version 12.52. A sample of this code and the included tags:exiftool -n -csv -XMP:PreservedFilename -EXIF:GPSMapDatum -EXIF:GPSLatitude -EXIF:GPSLatitudeRef -EXIF:GPSLongitude -EXIF:GPSLongitudeRef *.JPG > 2023020FA_YSM+_ImageLocs.csv
    Date: 06-Dec-2024 (process 7 of 8)
    Structure-from-motion processing: The SfM products were created in Agisoft Metashape v. 2.0.1 using the following generalized workflow (see Over and others, 2021 for a more detailed methodology explanation): 1. A project was created in Metashape and imagery specific to each sensor and flight area were imported. 2. Photos were aligned at a low accuracy and then GCPs were automatically detected in the point cloud. GCP positions (2024006FA_Clearview_Mar2024_AeroPoint.csv) were added to the project in the reference systems NAD83(2011)/UTM Zone 18N and NAVD88 (geoid 18). The horizontal and vertical accuracies for the GCPs were set to 0.04/0.02 m, respectively, and the camera positions for the images were turned off. The photos were then re-aligned with high accuracy (the pixels were not subsampled) using a key point limit of 60,000 and unlimited tie points. 3. The alignment process matched pixels between images to create point clouds and put the imagery into a relative spatial context using the GCPs. The resultant point clouds were filtered using one iteration of the 'Reconstruction uncertainty' filter at a level of 10, one iteration of the 'Projection accuracy' filter at a level of 3, and eight iterations of the 'Reprojection accuracy' filter to get to a level of 0.3. With each filter, iteration points are selected, deleted, and then the camera model was optimized to refine the focal length, cx, cy, k1, k2, k3, p1, and p2 camera model coefficients. 4. Multiple ‘chunks’ were created so that a high-quality dense cloud with a low-frequency filtering algorithm could be made from the images. The dense point cloud was then edited by visual inspection and Metashape’s confidence filter to remove points with a low confidence near the edges and near water bodies. 5. A DSM was built from the dense point cloud and then an orthomosaic was built from the DSM with refined seamlines. The DSMs are exported in the coordinate reference system (CRS) EPSG:6347 NAD83(2011)/UTM18N coordinate reference system (CRS) and the vertical reference system EPSG:5703 NAVD88 (Geoid 18).
    Date: 06-Dec-2024 (process 8 of 8)
    CLOUD OPTIMIZATION: All geoTIFF products were DEFLATE compressed and turned into a cloud-optimized GeoTIFFs (COG) using either the export tool in Global Mapper or gdal_translate with the following command: for %i in (.\*.tif) do gdal_translate %i .\cog\%~ni_cog.tif -of COG -stats -co BLOCKSIZE=256 -co COMPRESS=DEFLATE -co PREDICTOR=YES -co NUM_THREADS=ALL_CPUS -co BIGTIFF=YES (v. 3.1.4 accessed October 20, 2020 https://gdal.org/). Where "i" is the name of each geoTIFF section. Person who carried out this activity:
    Jennifer M. Cramer
    U.S. Geological Survey, Woods Hole Coastal and Marine Science Center
    Geographer
    U.S. Geological Survey
    Woods Hole, MA

    508-548-8700 x2314 (voice)
    jcramer@usgs.gov
  3. What similar or related data should the user be aware of?
    Over, Jin-Si R., Ritchie, Andrew C., Kranenburg, Christine J., Brown, Jenna A., Buscombe, Daniel D., Noble, Tom, Sherwood, Christopher R., Warrick, Jonathan A., and Wernette, Phillipe A., 2021, Processing coastal imagery with Agisoft Metashape Professional Edition, version 1.6-Structure from motion workflow documentation: Open-File Report 2021-1039, U.S. Geological Survey, Reston, VA.

    Online Links:

    Other_Citation_Details:
    This publication includes the general methodology for processing imagery in Metashape to produce digital surface models and ortho products.

How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?
    Lidar point clouds: A YellowScan Mapper Plus (YSMP) high-density lidar system, containing a Livox Avia lidar sensor, Applanix inertial measurement unit (IMU) and GPS/GNSS antenna, and natural color RGB SONY UMC-10RC camera module, was mounted to a DJI Matrice 600 uncrewed aircraft system (UAS) to collect low-altitude aerial lidar point cloud (LPC) data and simultaneous overlapping natural color color images. GPS/GNSS data from real-time kinematic (RTK) base station collecting positions on a known point at 1-hz for the duration of the lidar surveys is used for post-processing kinematic (PPK) corrections of the lidar system trajectory positions. Accuracy of the point clouds can be influenced by the flight altitude, velocity, positions of satellites, terrain, overlap, and atmospheric conditions. Returns are scattered or lost over water, resulting in large bands of no data. This does not impact the goal of the data collection, which is focused on the elevation of the land. Positional accuracy of the processed point cloud can be assessed using RTK-surveyed ground control points and checkpoints (see ground control and checkpoints section below). Horizontal accuracy can be difficult to assess due to difficulty visualizing the cross-checkered pattern of the ground control targets in the point cloud.
    Ground control and checkpoints: Ground control points (GCPs) are highly visible, typically square and cross-checkered black and white (or light grey), targets designed to be easily identifiable in aerial remote sensing data. RTK-GPS embedded, Wi-Fi enabled grey and black foam Propeller AeroPoints were used to collect continuous location and elevation data as GCPs. To improve visibility in the lidar point cloud, 2x2 meter square vinyl targets, with the same cross-checkered pattern as the AeroPoints were placed underneath the AeroPoints, with grey and black areas aligned.
    RTK-GPS: GPS point accuracy is assessed based on occupations of a known reference mark and GPS point precision is based on a positioning solution within 1-3 cm or “FIX” for each point and root mean square values of the position.
    Elevation products: The positional accuracy of elevation and image mosaic rasters are typically determined from RTK-surveyed GCPs and check points. GCPs are surveyed targets visible in aerial imagery that are used to georeference the model, while check points are independent of the model and can be used for post-validation. Certain products generated from data collected over the John Heinz National Wildlife Refuge did not contain GCPs due to poor accessibility; however, checkpoints were surveyed in some discrete locations within the Wildlife Refuge allowing for some localized assessment of vertical accuracy. GCPs and checkpoints were surveyed at the Clearview Landfill survey location. Accuracy degrades toward the edges of the raster products due to the absence of GCPs as well as the lack of overlap along the perimeter of the flight plan and angle of the images where the UAS is turning.
  2. How accurate are the geographic locations?
    Lidar data: Determining horizontal positional accuracy using ground control is difficult due to poor visualization of the center location of ground control targets in the LPC. Considering the GNSS reference accuracy of ~5 cm, a conservative horizontal positional error estimate could be considered up to 10 cm.
    Aerial Imagery: YellowScan Mapper+ camera module images were manually geotagged using the drone telemetry logs (tlogs), while the XT2 images were geotagged via the DJI M600 UAS hand controller, which gathers the GPS information from the M600 onboard GPS and transmits to the XT2, and embeds the information to the images in real time. The DJI M600 is equipped with a DJI A3 GPS, which receives signals from GPS and GLONASS satellites in WGS84 (EPSG::4326), but is otherwise uncorrected. Horizontal locations are considered accurate to approximately 0.5 meters, but may be greater than 10 meters due to UAS flight path uncertainty. Where present, it is recommended to use the ground control points in the CSV files "2024006FA_Clearview_Mar2024_AeroPoint.csv" provided in the larger work citation for georeferencing. left off here
    Structure-from-motion (SfM) processing: Horizontal RMSE of photogrammetric models at the Clearview Landfill where GCPs were deployed is 0.11 m. Photogrammetric models of the Darby Creek and tributaries using the XT2 RGB and thermal imagery lack GCPs. As a result, the orthomosaic georeferencing relies solely on autonomous GPS positioning. Horizontal RMSE estimates based on processing in Agisoft Metashape is 2.73 m. These estimates have not been independently validated.
    GPS Data: Horizontal positions for the AeroPoint targets are determined from the embedded RTK-GPS. The internal theoretical horizontal accuracy is 10 mm. The global horizontal accuracy is calculated using the following equation: global horizontal accuracy (mm) = internal horizontal accuracy (mm) + longest baseline distance (km) * 2. The resultant global horizontal accuracy of AeroPoint positions is 0.018 m.
  3. How accurate are the heights or depths?
    Lidar data: Using the SP80 RTK-surveyed points and AeroPoint targets as checkpoints, the lidar QC tool in Global Mapper v. 26.0 was used to determine the root mean square error (RMSE) of point cloud compared to the checkpoints. AeroPoints were used to assess the LPC of the Clearview Landfill (2024006FA_Clearview_Mar2024_YSMP_LPC) while the RTK rover checkpoints all fell within the point cloud for the Westernmost LPC (2024006FA_Heinz_Henderson_Mar2024_YSMP_LPC) of the John Heinz National Wildlife Refuge. The point spacing was set to 3 (~12 cm), which averages the elevation value of points falling within a 3 point buffer from the checkpoint position. Due to the variable conditions between the Wildlife Refuge and the Landfill, the resulting RMSE values were significantly different. The vertical RMSE determined from the AeroPoint target positions for the Clearview Landfill LPC was 3.30 cm, while the vertical RMSE for the Wildlife Refuge LPC was 17.5 cm. This discrepancy is likely due certain conditions, including: (1) The lack of tall and dense vegetation on the landfill, while the Refuge contained dense vegetated areas, especially along the paths where the checkpoints were surveyed, and (2) the nature of placement of the AeroPoint ground control targets, which tend to be open and flat, relatively unvegetated, locations.
    Aerial Imagery: YellowScan Mapper+ camera module images were manually geotagged using the drone telemetry logs (tlogs), while the XT2 images were geotagged via the DJI M600 UAS hand controller, which gathers the GPS information from the M600 onboard GPS and transmits to the XT2, and embeds the information to the images in real time. It is important to note that due to an unknown error, the vertical position values (altitude) in the XT2 images were incorrectly tagged by the hand controller and should not be considered accurate or usable. The DJI M600 is equipped with a DJI A3 GPS, which receives signals from GPS and GLONASS satellites in WGS84 (EPSG::4326), but is otherwise uncorrected. Horizontal locations are considered accurate to approximately 0.5 meters, but may be greater than 10 meters due to UAS flight path uncertainty. Where present, it is recommended to use the ground control points in the CSV files "2024006FA_Clearview_Mar2024_AeroPoint.csv" provided in the larger work citation for georeferencing.
    Structure-from-motion (SfM) processing: Elevation rasters from photogrammetric processing is not provided in this data release, but the SfM model was used to generate the orthomosaics so the vertical accuracy is still provided. Photogrammetric models at the Clearview Landfill where GCPs were deployed have an estimated vertical accuracy of 0.10 m. Photogrammetric models of the Darby Creek and tributaries using the XT2 RGB and thermal imagery lacks ground control. As a result, the orthomosaic georeferencing relies solely on autonomous GPS positioning. Vertical RMSE Estimates based on processing in Agisoft Metashape is 1.73 m. These estimates have not been independently validated.
    GPS Data: Vertical positions for the AeroPoint targets are determined from the embedded RTK-GPS. The internal theoretical vertical accuracy is 10 mm. The global vertical accuracy is calculated using the following equation: global vertical accuracy (mm) = internal vertical accuracy (mm) + longest baseline distance (km) * 2. The resultant global vertical accuracy of AeroPoint positions is 0.028 m.
  4. Where are the gaps in the data? What is missing?
    Lidar data: Data was collected over 13 flights over the Clearview Landfill and John Heinz National Wildlife Refuge with the YellowScan Mapper Plus (YSMP) system. The resulting data included 7 .ys, .lvx, and .T04 scanner data files. These files were used in the creation of the .laz point cloud file, but are not included in this data release. One LPC was produced for the survey area over the Clearview Landfill totaling 1.06 GB while the larger survey area within the National Wildlife Refuge was processed in three sections to generate three LPCs totaling 17.1 GB. A digital surface model (DSM) and digital terrain model (DTM) were generated for the Clearview Landfill, totaling 1.01 GB, and three DSMs and three DTMs for the John Heinz National Wildlife Refuge, totaling 8.54 GB.
    Aerial Imagery: Gaps in sequential 2-second photo intervals exist where photos were removed from the collection. Photos can be removed for reasons including, collected outside flight plan bounds, poor photo quality, overexposure, or redundancy. The final image count for the YSMP natural color imagery in this data release is 5,502 images totaling 40.3 gigabytes (GB). The final image count for the XTS natural color and thermal imagery in this data release is 2,228 images totaling 4.39 GB in size. Images were geotagged either manually or by an integrated GPS in the sensor. Image location information is provided in the CSV files titled "2024006FA_Clearview_Mar2024_YSMP_ImageLocs.csv", "2024006FA_Darby_Mar2024_XT2_ImageLocs.csv", "2024006FA_Heinz_Henderson_Mar2024_YSMP_ImageLocs.csv", "2024006FA_Heinz_LowerImpoundment_Mar2024_YSMP_ImageLocs.csv" and "2024006FA_Heinz_TurkeyFoot_Mar2024_YSMP_ImageLocs.csv."
    Structure-from-motion (SfM) processing: Images that were collected outside the bounds of the flight plan, whose photo quality was poor, were overexposed, or were redundant were disabled and excluded from the photogrammetric model processing. Only enabled images that were used in the photogrammetric model were included in this data release.
    GPS data: A total of 75 surveyed points within the John Heinz National Wildlife Refuge collected on 3/17/2024 are included in the "2024006FA_Darby_Mar2024_SP80.csv" dataset. 10 AeroPoints were deployed on 3/15/2024 across the Clearview Landfill and are included in the dataset. These points are saved in tabular format in two CSV files titled "2023020FA_20230828_AeroPoints.csv", "2024006FA_Darby_Mar2024_SP80.csv", and "2024006FA_Clearview_Mar2024_AeroPoint.csv"
  5. How consistent are the relationships among the observations, including topology?
    UAS data collection: Most missions require multiple flights to complete due to battery limitations. Between individual flights, the camera/sensor settings and mission plan specifications are not changed to ensure consistent data/imagery collection. Following each flight, data is downloaded to a field computer, copied to an external storage device, and later uploaded to a data server. For lidar data, the RGB photos are verified, and the scanner data is plotted in an offline version of YellowScan CloudStation between each flight to verify the scanner was operating as expected and that there are no areas of missing data. Images are also plotted in a photogrammetry software to verify no missing sections of the flight plan before continuing with the mission.
    GPS data: All RTK-GPS rover data were exported as a single tabular comma-separated values (CSV) file using Microsoft Excel v. 2208. AeroPoint data are uploaded via a WiFi connection to a user defined account on propelleraero.com. The raw data are processed by Propeller and exported to a CSV file.
    Image Data Management: Aerial images were organized into directories labeled by flight number and then transferred to an external drive and later uploaded to the AIMG server. Images were renamed to include the field activity number (FAN), flight number, camera ID, date and time (UTC), and original filename. Gaps in consecutive flight numbers may be due to a variety of reasons, including no photos being collected during a particular flight, failure to initiate camera, or issues with the imagery during a particular flight. Metadata contained in image file headers were modified for all photos to include standard USGS tags. The natural color images from the YellowScan camera module were manually geotagged using a script that accesses the UAS telemetry logs (tlogs). The natural color and thermal-IR images from the XT2 are geotagged via the M600 hand controller. Due to an unknown error, altitude values were incorrectly geotagged, varying from flight to flight by hundreds of meters; however, positional information of imagery is helpful, but not necessary for photogrammetric processing, and so these altitude values can be ignored. See the the processing steps in Lineage for more information.
    All processing was done by members of the Aerial Imaging and Mapping Group (AIMG).

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints None
Use_Constraints Public domain (CC0-1.0) data from the U.S. Government are freely redistributable with proper metadata and source attribution. Please recognize the U.S. Geological Survey (USGS) as the source of this information. These data are not intended for navigational use.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey - ScienceBase
    Denver Federal Center, Building 810, Mail Stop 302
    Denver, CO

    1-888-275-8747 (voice)
    sciencebase@usgs.gov
  2. What's the catalog number I need to order this data set? Aerial imaging and mapping of The Darby Creek Superfund Site and John Heinz National Wildlife Refuge includes four lidar point clouds, eight elevation models, two natural color orthomosaics, one thermal infra-red orthomosaic, associated imagery, ground control and check points.
  3. What legal disclaimers am I supposed to read?
    Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty.
  4. How can I download or order the data?

Who wrote the metadata?

Dates:
Last modified: 10-Jul-2025
Metadata author:
Jennifer M. Cramer
U.S. Geological Survey, Northeast Region
Geographer
U.S. Geological Survey
Woods Hole, MA

508-548-8700 x2314 (voice)
whsc_data_contact@usgs.gov
Contact_Instructions:
The metadata contact email address is a generic address in the event the person is no longer with USGS.
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/whcmsc/SB_data_release/DR_P134HU3Y/2024006FA_Darby_Mar2024_Metadata.faq.html>
Generated by mp version 2.9.51 on Fri Jul 11 10:39:43 2025