Geospatial data that is a derivative land cover product depicting woodland on topographic maps.

Geospatial data that is a derivative land cover product depicting woodland on topographic maps.

The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2016. The NLCD 2016 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2016 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2016: a streamlined process for assembling and preprocessing Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2016 production. The performance of the developed strategies and methods were tested in twenty World Reference System-2 path/row throughout the conterminous U.S. An overall agreement ranging from 71% to 97% between land cover classification and reference data was achieved for all tested area and all years. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2016 operational mapping. Questions about the NLCD 2016 land cover product can be directed to the NLCD 2016 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.

The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2016. The NLCD 2016 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2016 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2016: a streamlined process for assembling and preprocessing Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2016 production. The performance of the developed strategies and methods were tested in twenty World Reference System-2 path/row throughout the conterminous U.S. An overall agreement ranging from 71% to 97% between land cover classification and reference data was achieved for all tested area and all years. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2016 operational mapping. Questions about the NLCD 2016 land cover product can be directed to the NLCD 2016 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.

In support of mapping ecological conditions (e.g. invasive annual grass) in sagebrush-dominated landscapes of the western United States, we developed weekly (starting from week 7 to week 42 and Week 1 starts January 1 or Day of the year 1 to 7, week 2 is from Day of year 8 to 14, and so on) 30-m cloud-free Normalized Difference Vegetation Index (NDVI) from 2016 to 2019. The data was generated with machine-learning techniques (i.e., regression tree [RT]) and harmonized Landsat and Sentinel -2 (HLS) data. The geographic coverage includes areas in the Great Basin, the Snake River Plain, the state of Wyoming, and contiguous areas. This NDVI collection allows for local-scale detection and analysis such as, fuel breaks in sagebrush ecosystem and wildfire activity, that are not possible with coarse scale datasets (such as 250-m).

In support of mapping ecological conditions (e.g. invasive annual grass) in sagebrush-dominated landscapes of the western United States, we developed weekly (starting from week 7 to week 42 and Week 1 starts January 1 or Day of the year 1 to 7, week 2 is from Day of year 8 to 14, and so on) 30-m cloud-free Normalized Difference Vegetation Index (NDVI) from 2016 to 2019. The data was generated with machine-learning techniques (i.e., regression tree [RT]) and harmonized Landsat and Sentinel -2 (HLS) data. The geographic coverage includes areas in the Great Basin, the Snake River Plain, the state of Wyoming, and contiguous areas. This NDVI collection allows for local-scale detection and analysis such as, fuel breaks in sagebrush ecosystem and wildfire activity, that are not possible with coarse scale datasets (such as 250-m).

These datasets are continuous parameter grids (CPG) of land cover types (percent of basin classified by cover type) for the years 2001, 2006, and 2011 in the Pacific Northwest. Cover types include forest, agriculture, developed, wetland, and open water. Source data was the National Land Cover Dataset, produced by the Multi-Resolution Land Characteristics (MRLC) Consortium.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Following development of vegetation classifications after plot sampling, the preliminary vegetation map was further edited and refined in 2005. Using ArcGIS 9.0, polygon boundaries were revised on-screen based on plot data and additional field observations collected during 2004 field visits. Field notes and limited field mapping supplemented GIS mapping. Each polygon was attributed with a map class name that is the common name of a USNVC association, a park-specific map class name representing a variant of an association, or an Anderson Level II use/land cover map class based on plot data, field observations, aerial photography signatures, and topographic maps. Map units in the 2005 vegetation map were equivalent to the association level with few exceptions. The overall 2005 map accuracy and Kappa index was 76%, which fell below the USGS/NPS vegetation mapping protocol requirement of 80%. Revisions were subsequently made to the 2005 vegetation map to increase the accuracy of the final product. The final 2007 vegetation map accuracy was 85.7% and Kappa index was 84.6%.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Following development of vegetation classifications after plot sampling, the preliminary vegetation map was further edited and refined in 2005. Using ArcGIS 9.0, polygon boundaries were revised on-screen based on plot data and additional field observations collected during 2004 field visits. Field notes and limited field mapping supplemented GIS mapping. Each polygon was attributed with a map class name that is the common name of a USNVC association, a park-specific map class name representing a variant of an association, or an Anderson Level II use/land cover map class based on plot data, field observations, aerial photography signatures, and topographic maps. Map units in the 2005 vegetation map were equivalent to the association level with few exceptions. The overall 2005 map accuracy and Kappa index was 76%, which fell below the USGS/NPS vegetation mapping protocol requirement of 80%. Revisions were subsequently made to the 2005 vegetation map to increase the accuracy of the final product. The final 2007 vegetation map accuracy was 85.7% and Kappa index was 84.6%.

These data were converted from the originally delivered Microsoft Access PLOTs database from the Vegetation Mapping Inventory Project of Marsh-Billings-Rockefeller National Historical Park. These comma-delimited data tables contain(s) vegetation mapping plot classification and accuracy assessment data, as well as summary information about the data itself. If a table is empty, then it was empty in the original database.