Land Cover Data
Use the map to download landcover data by state, county, or ecoregion. You can also download the entire dataset with overviews or without overviews (smaller file), or browse the files if you'd prefer.
Multi-season satellite imagery (Landsat ETM+) from 1999-2001 were used in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform, aspect, etc.) to model natural and semi-natural vegetation. Landcover classes are drawn from NatureServe’s Ecological System concept, with 109 of the 125 total classes mapped at the system level. For the majority of classes, a decision tree classifier was used to discriminate landcover types, while a minority of classes (e.g. urban classes, sand dunes, burn scars, etc.) were mapped using other techniques. Twenty mapping areas, each characterized by similar ecological and spectral characteristics, were modeled independently of one another. These mapping areas, which included a 4 km overlap, were subsequently mosaicked to create the regional dataset. An internal validation for modeled classes was performed on a withheld 20% of the sample data. Results of the validation are presented in the project final report. While the modeling area encompassed these 5 southwestern states (Arizona, Colorado, Nevada, New Mexico, Utah) the actual GIS dataset downloaded from this site may be a subset of the 5-state region.
A total of 125 land cover classes were mapped for the five-state region. One hundred and nine are considered natural or semi-natural land cover classes. The remaining land cover classes are disturbed natural or anthropogenic land cover/use classes. The basic thematic mapping unit for natural and semi-natural land cover classes is the ecological system developed by NatureServe. Ecological systems represent recurring groups of biological communities found in similar physical environments and influenced by similar dynamic ecological processes, such as fire or flooding. They are intended to provide a thematic mapping unit that is mappable at a meso-scale level often from remotely sensed imagery.
Recommended citation for this land cover dataset: Lowry, J. H, Jr., R. D. Ramsey, K. Boykin, D. Bradford, P. Comer, S. Falzarano, W. Kepner, J. Kirby, L. Langs, J. Prior-Magee, G. Manis, L. O’Brien, T. Sajwaj, K. A. Thomas, W. Rieth, S. Schrader, D. Schrupp, K. Schulz, B. Thompson, C. Velasquez, C. Wallace, E. Waller and B. Wolk. 2005. Southwest Regional Gap Analysis Project: Final Report on Land Cover Mapping Methods, RS/GIS Laboratory, Utah State University, Logan, Utah.