Back to Search Start Over

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)

Authors :
Lowry, J.
Ramsey, R.D.
Thomas, K.
Schrupp, D.
Sajwaj, T.
Kirby, J.
Waller, E.
Schrader, S.
Falzarano, S.
Langs, L.
Manis, G.
Wallace, C.
Schulz, K.
Comer, P.
Pohs, K.
Rieth, W.
Velasquez, C.
Wolk, B.
Kepner, W.
Boykin, K.
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