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Mapping moderate-scale land-cover over very large geographic areas within a collaborative framework: A case study of the Southwest Regional Gap Analysis Project (SWReGAP)
- Source :
-
Remote Sensing of Environment . May2007, Vol. 108 Issue 1, p59-73. 15p. - Publication Year :
- 2007
-
Abstract
- Land-cover mapping efforts within the USGS Gap Analysis Program have traditionally been state-centered; each state having the responsibility of implementing a project design for the geographic area within their state boundaries. The Southwest Regional Gap Analysis Project (SWReGAP) was the first formal GAP project designed at a regional, multi-state scale. The project area comprises the southwestern states of Arizona, Colorado, Nevada, New Mexico, and Utah. The land-cover map/dataset was generated using regionally consistent geospatial data (Landsat ETM+ imagery (1999–2001) and DEM derivatives), similar field data collection protocols, a standardized land-cover legend, and a common modeling approach (decision tree classifier). Partitioning of mapping responsibilities amongst the five collaborating states was organized around ecoregion-based “mapping zones”. Over the course of 21/2 field seasons approximately 93,000 reference samples were collected directly, or obtained from other contemporary projects, for the land-cover modeling effort. The final map was made public in 2004 and contains 125 land-cover classes. An internal validation of 85 of the classes, representing 91% of the land area was performed. Agreement between withheld samples and the validated dataset was 61% (KHAT=. 60, n =17,030). This paper presents an overview of the methodologies used to create the regional land-cover dataset and highlights issues associated with large-area mapping within a coordinated, multi-institutional management framework. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 00344257
- Volume :
- 108
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Remote Sensing of Environment
- Publication Type :
- Academic Journal
- Accession number :
- 24710802
- Full Text :
- https://doi.org/10.1016/j.rse.2006.11.008