de93dba9-4e90-49cf-95ec-b1ee4ccfed83 Porensky, Lauren Lauren.Porensky@usda.gov 2026-02-06T15:53:38.684Z ISO 19115:2003/19139 1.0 WGS 1984 Data from: Bringing cross-validation into the real world to evaluate transferability of satellite-based vegetation models 2026-02-06 10.15482/USDA.ADC/31271986 This tabular dataset supports findings reported in Bringing cross-validation into the real world to evaluate transferability of satellite-based vegetation models published in Scientific Reports. Data are from the Central Plains Experimental Range (CPER), near Nunn, Colorado, and contains nearly 10,000 ground samples collected from 2014 to 2023. Data are aggregated to the plot level (n=2,322), of which there are 4-6 in each pasture and also provided at the transect level (n=9,647), of which there are 4 in each plot. Data were used to train progressively more complex Machine learning algorithms (MLAs) to predict standing aboveground herbaceous biomass in grazinglands, such as those found at CPER. These data support an investigation of whether (1) do simpler geospatial MLAs have better transferability to ‘unseen’ conditions and ‘worst-case’ performance (i.e., under extreme conditions) compared to more complex MLAs and (2) are they more consistent when re-trained with new data. Data include (1) unique identifiers and blocking co-variates (2) in-situ ground-sampled herbaceous standing biomass estimated using visual obstruction (VO) methods, along with the VO readings themselves (3) geographic polygon bounding coordinates of each plot/transect (WKT format), and (4) satellite-derived indices and bands from the Harmonized Landsat Sentinel (HLS) data product. All in situ values and satellite derived indices are means for the respective plot and transect areas. To enable reproduction of model fitting using ground data and remote sensing of vegetation. Porensky, Lauren Lauren.Porensky@usda.gov Justin D Derner http://orcid.org/0000-0001-8076-0736 WWW:LINK-1.0-http--link ORCID ORCID Mikael Hiestand Erika Peirce Lauren M. Porensky http://orcid.org/0000-0001-6883-2442 WWW:LINK-1.0-http--link ORCID ORCID David J. Augustine http://orcid.org/0000-0003-3144-0466 WWW:LINK-1.0-http--link ORCID ORCID Sean Kearney vegetation rangelands remote sensing grasslands Landsat grazing lands biomass algorithms artificial intelligence pastures Great Plains region Colorado data collection models National Agricultural Library Thesaurus (NALT) USDA NAL Keywords 2015 2021 Edition USDA National Agricultural Library * National Agricultural Library Thesaurus (NALT) Coordinator 10301 Baltimore Ave Beltsville, MD 20705 United States of America agref@usda.gov https://agclass.nal.usda.gov/ HTTP Web Browser USDA National Agricultural Library Thesaurus and Glossary Home Page The Thesaurus and Glossary are online vocabulary tools of agricultural terms in English and Spanish and are cooperatively produced by the National Agricultural Library, USDA, and the Inter-American Institute for Cooperation on Agriculture as well as other Latin American agricultural institutions belonging to the Agriculture Information and Documentation Service of the Americas (SIDALC). A controlled vocabulary of keywords to classify dataset records in Ag Data Commons Department of Agriculture=5 > Agricultural Research Service=005:018 OMB Bureau Codes Office of Management and Budget Bureau Codes 2016 revision 2016 OMB Bureau Codes https://obamawhitehouse.archives.gov/sites/default/files/omb/assets/a11_current_year/app_c.pdf HTTP Web Browser APPENDIX C—LISTING OF OMB AGENCY/BUREAU AND TREASURY CODES In the MAX system, OMB assigns and uses agency and bureau codes, which are associated with agency and bureau titles that are published in the Budget.PDF file. information Resource Provider Complete list of bureau codes Department of Agriculture=5 > National Research=005:040 Federal Program Inventory US Federal Program Codes 2013-09-16 revision Fiscal Year 2013 Office of Management and Budget https://www.whitehouse.gov/omb HTTP Web Browser Office of Management and Budget The Office of Management and Budget (OMB) serves the President of the United States in overseeing the implementation of his vision across the Executive Branch. Specifically, OMB’s mission is to assist the President in meeting his policy, budget, management and regulatory objectives and to fulfill the agency’s statutory responsibilities. information Originator Office of Management and budget. File FederalProgramInventory_FY13_MachineReadable_091613.xls, current loation unknown. USDA-ARS: 0201-88888-002-000D USDA-ARS: 0201-88888-003-000D USDA-ARS: 3012-21500-001-000D Crossref Funding Crossref Open Funder Registry 2016-08-11 1.2 Crossref funder.registry@crossref.org https://www.crossref.org/services/funder-registry/ HTTP Web Browser Open Funder Registry Funding data provides a standard way to report funding sources for published scholarly research. Publishers deposit funding information from articles and other content using a standard taxonomy of funder names. A common taxonomy of over 11,000 funding body names that funding data initiative participants should use to normalize Funder Names and IDs. 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Please choose from U.S. Public Domain, Creative Commons CCZero, Creative Commons Attribution, or Creative Commons Attribution Share-Alike. biomass RANGELANDS satellite remote sensing; machine learning grasslands imageryBaseMapsEarthCover geoscientificInformation farming environment biota 2014-06-01 2023-10-31 -104.7901 -104.6824 40.8003 40.8697 CSV 1 https://doi.org/10.15482/USDA.ADC/31271986 WWW:LINK-1.0-http--link Data files Data files for Data from: Bringing cross-validation into the real world to evaluate transferability of satellite-based vegetation models