Sediment budget data for Lees Ferry dune field, February-May 2019

These data were compiled to enable estimation of aeolian dune field sediment budgets calculated using remote sensing methods. The objective of the study was to evaluate sediment budgets calculated for the Lees Ferry dune field in Grand Canyon, Earth as a terrestrial analog for aeolian dune fields in Valles Marineris, Mars. These data represent digital elevation models (DEM) of the topography of the Lees Ferry dune field in February and May, 2019, respectively. These data were collected with an Uncrewed Aerial Vehicle (UAV) remote sensing survey conducted on February 28th and then repeated on May 2nd, 2019. The images acquired with the UAV surveys were processed with photogrammetric modelling to produce the DEMs. These data were collected and processed by Geoff Debenedetto (USGS Arizona Water Science Center) and further processed and analyzed by Joshua Caster and Joel B. Sankey (USGS Southwest Biological Science Center, Grand Canyon Monitoring and Research Center). These data can be used to investigate the topography of, and calculate and evaluate remote sensing sediment budgets of, the Lees Ferry dune field.

Data and Resources

Field Value
accessLevel public
bureauCode {010:12}
catalog_@context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
catalog_@id https://ddi.doi.gov/usgs-data.json
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catalog_describedBy https://project-open-data.cio.gov/v1.1/schema/catalog.json
identifier http://datainventory.doi.gov/id/dataset/usgs-6291031bd34ef70cdba45356
metadata_type geospatial
modified 2022-09-20T00:00:00Z
old-spatial -111.5990, 36.8610, -111.5960, 36.8620
publisher U.S. Geological Survey
resource-type Dataset
source_datajson_identifier true
source_hash e97f30575549dfc605bdea9447aca53af9d0c22066241aef1f9d873633eca84a
source_schema_version 1.1
spatial {"type": "Polygon", "coordinates": [[[-111.5990, 36.8610], [-111.5990, 36.8620], [ -111.5960, 36.8620], [ -111.5960, 36.8610], [-111.5990, 36.8610]]]}
theme {geospatial}
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • 10-cm-grid-cell
  • AmeriGEO
  • AmeriGEOSS
  • CKAN
  • GEO
  • GEOSS
  • National
  • North America
  • United States
  • aeolian
  • analog
  • arizona
  • colorado-river
  • continuous-elevation-surface
  • data-release
  • dem
  • digital-elevation-models
  • dune
  • dune-field
  • elevation
  • eolian
  • geoscientificinformation
  • glen-canyon-national-recreation-area
  • grand-canyon
  • imagerybasemapsearthcover
  • in-situ
  • lees-ferry
  • photogrammetric-modeling
  • remote-sensing
  • sediment-budget
  • topographic-maps
  • topography
  • uav
  • unconsolidated-deposits
  • uncrewed-aerial-vehicle
  • united-states
  • usgs-6291031bd34ef70cdba45356
  • vermillion-cliffs-national-monument
isopen False
license_id notspecified
license_title License not specified
maintainer Joel B. Sankey
maintainer_email jsankey@usgs.gov
metadata_created 2025-09-24T07:11:07.405262
metadata_modified 2025-09-24T07:11:07.405272
notes These data were compiled to enable estimation of aeolian dune field sediment budgets calculated using remote sensing methods. The objective of the study was to evaluate sediment budgets calculated for the Lees Ferry dune field in Grand Canyon, Earth as a terrestrial analog for aeolian dune fields in Valles Marineris, Mars. These data represent digital elevation models (DEM) of the topography of the Lees Ferry dune field in February and May, 2019, respectively. These data were collected with an Uncrewed Aerial Vehicle (UAV) remote sensing survey conducted on February 28th and then repeated on May 2nd, 2019. The images acquired with the UAV surveys were processed with photogrammetric modelling to produce the DEMs. These data were collected and processed by Geoff Debenedetto (USGS Arizona Water Science Center) and further processed and analyzed by Joshua Caster and Joel B. Sankey (USGS Southwest Biological Science Center, Grand Canyon Monitoring and Research Center). These data can be used to investigate the topography of, and calculate and evaluate remote sensing sediment budgets of, the Lees Ferry dune field.
num_resources 2
num_tags 38
title Sediment budget data for Lees Ferry dune field, February-May 2019