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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:contributor>R.D. Ramsey</dc:contributor>
  <dc:contributor>K. Thomas</dc:contributor>
  <dc:contributor>D. Schrupp</dc:contributor>
  <dc:contributor>T. Sajwaj</dc:contributor>
  <dc:contributor>J. Kirby</dc:contributor>
  <dc:contributor>E. Waller</dc:contributor>
  <dc:contributor>S. Schrader</dc:contributor>
  <dc:contributor>S. Falzarano</dc:contributor>
  <dc:contributor>L. Langs</dc:contributor>
  <dc:contributor>G. Manis</dc:contributor>
  <dc:contributor>C. Wallace</dc:contributor>
  <dc:contributor>K. Schulz</dc:contributor>
  <dc:contributor>P. Comer</dc:contributor>
  <dc:contributor>K. Pohs</dc:contributor>
  <dc:contributor>W. Rieth</dc:contributor>
  <dc:contributor>C. Velasquez</dc:contributor>
  <dc:contributor>B. Wolk</dc:contributor>
  <dc:contributor>W. Kepner</dc:contributor>
  <dc:contributor>K. Boykin</dc:contributor>
  <dc:contributor>L. O’Brien</dc:contributor>
  <dc:contributor>D. Bradford</dc:contributor>
  <dc:contributor>B. Thompson</dc:contributor>
  <dc:contributor>J. Prior-Magee</dc:contributor>
  <dc:creator>J. Lowry</dc:creator>
  <dc:date>2007</dc:date>
  <dc:description>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. ?? 2006 Elsevier Inc. All rights reserved.</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>10.1016/j.rse.2006.11.008</dc:identifier>
  <dc:language>en</dc:language>
  <dc:title>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)</dc:title>
  <dc:type>article</dc:type>
</oai_dc:dc>