Dataset Identification:

Resource Abstract:
description: The vertical land change activity focuses on the detection, analysis, and explanation of topographic change. These detection techniques include both quantitative methods, for example, using difference metrics derived from multi-temporal topographic digital elevation models (DEMs), such as, light detection and ranging (lidar), National Elevation Dataset (NED), Shuttle Radar Topography Mission (SRTM), and Interferometric Synthetic Aperture Radar (IFSAR), and qualitative methods, for example, using multi-temporal aerial photography to visualize topographic change. The geographic study areas of this activity are in Itasca and St. Louis counties in the northern Minnesota Mesabi Iron Range. Available multi-temporal lidar, NED, SRTM, IFSAR, and other topographic elevation datasets, as well as aerial photography and multi-spectral image data were identified and downloaded for these study area counties. Mining (vector) features were obtained from the Minnesota Department of Natural Resources and St. Louis Government Services Center. These features were used to spatially locate the study areas within Itasca and St. Louis counties. Previously developed differencing methods (Gesch, 2006) were used to develop difference raster datasets of NED/SRTM (1947-2000 date range) and SRTM/IFSAR (2000-2008 date range). The difference rasters were evaluated to exclude difference values that were below a specified vertical change threshold, which was applied spatially by National Land Cover Dataset (NLCD) 1992 and 2006 land cover type, respectively. This spatial application of the vertical change threshold values improved the overall ability to detect vertical change because threshold values in bare earth areas were distinguished from threshold values in heavily vegetated areas.High-resolution (1-3 m) DEMs, generated from lidar point cloud data, were acquired for Itasca and St. Louis counties in Minnesota from the Minnesota Department of Natural Resources. ESRI Mosaic Datasets were generated from lidar point-cloud data and available topographic DEMs for the specified study areas. These data were analyzed to estimate volumetric changes on the land surface at three different periods with lidar acquisitions occurring for Itasca County between April 5, 2012 to April 28, 2012 and St. Louis County between May 3, 2011 to June 1, 2011. A recent difference raster dataset time span (2007-2012 date range) was analyzed by differencing the Minnesota lidar-derived DEMs and an IFSAR-derived dataset. The IFSAR-derived data were resampled to the resolution of the lidar DEM (approximately 1-m resolution) and compared with the lidar-derived DEM. Land cover based threshold values were applied spatially to detect vertical change using the lidar/IFSAR difference dataset. Itasca County included metadata describing vertical root mean square error (RMSE) values for different land cover types. This allowed additional refinement of the spatially explicit threshold values. A single RMSE value was used for St. Louis County because RMSE values for land cover types were not provided.References: Gesch, Dean B., 2006, An inventory and assessment of significant topographic changes in the United States Brookings, S. Dak., South Dakota State University, Ph.D. dissertation, 234 p, at https://topotools.cr.usgs.gov/pdfs/DGesch_dissertation_Nov2006.pdf.; abstract: The vertical land change activity focuses on the detection, analysis, and explanation of topographic change. These detection techniques include both quantitative methods, for example, using difference metrics derived from multi-temporal topographic digital elevation models (DEMs), such as, light detection and ranging (lidar), National Elevation Dataset (NED), Shuttle Radar Topography Mission (SRTM), and Interferometric Synthetic Aperture Radar (IFSAR), and qualitative methods, for example, using multi-temporal aerial photography to visualize topographic change. The geographic study areas of this activity are in Itasca and St. Louis counties in the northern Minnesota Mesabi Iron Range. Available multi-temporal lidar, NED, SRTM, IFSAR, and other topographic elevation datasets, as well as aerial photography and multi-spectral image data were identified and downloaded for these study area counties. Mining (vector) features were obtained from the Minnesota Department of Natural Resources and St. Louis Government Services Center. These features were used to spatially locate the study areas within Itasca and St. Louis counties. Previously developed differencing methods (Gesch, 2006) were used to develop difference raster datasets of NED/SRTM (1947-2000 date range) and SRTM/IFSAR (2000-2008 date range). The difference rasters were evaluated to exclude difference values that were below a specified vertical change threshold, which was applied spatially by National Land Cover Dataset (NLCD) 1992 and 2006 land cover type, respectively. This spatial application of the vertical change threshold values improved the overall ability to detect vertical change because threshold values in bare earth areas were distinguished from threshold values in heavily vegetated areas.High-resolution (1-3 m) DEMs, generated from lidar point cloud data, were acquired for Itasca and St. Louis counties in Minnesota from the Minnesota Department of Natural Resources. ESRI Mosaic Datasets were generated from lidar point-cloud data and available topographic DEMs for the specified study areas. These data were analyzed to estimate volumetric changes on the land surface at three different periods with lidar acquisitions occurring for Itasca County between April 5, 2012 to April 28, 2012 and St. Louis County between May 3, 2011 to June 1, 2011. A recent difference raster dataset time span (2007-2012 date range) was analyzed by differencing the Minnesota lidar-derived DEMs and an IFSAR-derived dataset. The IFSAR-derived data were resampled to the resolution of the lidar DEM (approximately 1-m resolution) and compared with the lidar-derived DEM. Land cover based threshold values were applied spatially to detect vertical change using the lidar/IFSAR difference dataset. Itasca County included metadata describing vertical root mean square error (RMSE) values for different land cover types. This allowed additional refinement of the spatially explicit threshold values. A single RMSE value was used for St. Louis County because RMSE values for land cover types were not provided.References: Gesch, Dean B., 2006, An inventory and assessment of significant topographic changes in the United States Brookings, S. Dak., South Dakota State University, Ph.D. dissertation, 234 p, at https://topotools.cr.usgs.gov/pdfs/DGesch_dissertation_Nov2006.pdf.
Citation
Title Vertical Land Change, Itasca and St. Louis Counties, Minnesota.
creation  Date   2018-05-21T11:51:30.077667
Resource language:
Processing environment:
Back to top:
Digital Transfer Options
Linkage for online resource
name Dublin Core references URL
URL:https://doi.org/10.5066/F7445K05
protocol WWW:LINK-1.0-http--link
link function information
Description URL provided in Dublin Core references element.
Linkage for online resource
name Dublin Core references URL
URL:https://doi.org/10.5066/F7445K05
protocol WWW:LINK-1.0-http--link
link function information
Description URL provided in Dublin Core references element.
Linkage for online resource
name Dublin Core references URL
URL:https://topochange.cr.usgs.gov/
protocol WWW:LINK-1.0-http--link
link function information
Description URL provided in Dublin Core references element.
Metadata data stamp:  2018-08-07T00:03:57Z
Resource Maintenance Information
maintenance or update frequency:
notes: This metadata record was generated by an xslt transformation from a dc metadata record; Transform by Stephen M. Richard, based on a transform by Damian Ulbricht. Run on 2018-08-07T00:03:57Z
Metadata contact - pointOfContact
organisation Name  CINERGI Metadata catalog
Contact information
Address
electronic Mail Addresscinergi@sdsc.edu
Metadata language  eng
Metadata character set encoding:   utf8
Metadata standard for this record:  ISO 19139 Geographic Information - Metadata - Implementation Specification
standard version:  2007
Metadata record identifier:  urn:dciso:metadataabout:69f7c404-9d32-47a2-a03b-28236e10d264

Metadata record format is ISO19139 XML (MD_Metadata)