Skip all navigation and jump to content Jump to site navigation
NASA Logo - Goddard Space Flight Center

+ NASA Homepage

    
Goddard Space Flight Center
About MODIS News Data Tools /images2 Science Team Science Team Science Team

   + Home
ABOUT MODIS
MODIS Publications Link
MODIS Presentations Link
MODIS Biographies Link
MODIS Science Team Meetings Link
 

 

 

Sexton, JO; Urban, DL; Donohue, MJ; Song, CH (2013). Long-term land cover dynamics by multi-temporal classification across the Landsat-5 record. REMOTE SENSING OF ENVIRONMENT, 128, 246-258.

Abstract
Supervised classification of land cover across space and time is a long-standing goal of the Earth Science community. Although most past and current analyses focus on detecting changes between two or more times, the opening of the USGS Landsat archive in 2009 has enabled exploration of methods for higher-frequency, time-serial monitoring of land cover dynamics. Modifying the protocols used to develop the 2001 National Land Cover Database (NLCD 2001), we fit a single classifier to a spatio-temporally distributed reference sample and applied the model to 55 Landsat-5 images covering a section of the North Carolina Piedmont Plateau from 1984 to 2007. A generalized classification scheme, multi-temporal sampling design, supervised classification based on intra-annual spectral indices, and design-based accuracy assessment yielded a time-series of 16 land cover maps from 1985 to 2006 with a spatial extent of 1.7x 10(6) ha, minimum mapping unit of 1 ha, and mean temporal interval of <2 years. Comparable to accuracy of the NLCD 2001 Land Cover Layer for the region, overall accuracy for a spatio-temporally independent test sample was 75%, with K=0.7. When weighted by class proportions, percent correctly classified and kappa rose to 88% and 0.84, respectively. The resulting map series shows spatially and temporally complex changes in water, urban, forest, and herbaceous cover resulting from natural and anthropogenic processes that would not be observable in either unior bi-temporal maps. Agricultural crop area dropped from similar to 45% in the 1980s to similar to 36% in the 1990s and then rose slightly to similar to 38% at the end of the period. Forest area increased to a maximum of similar to 55% in the 1990s and then dropped to similar to 53% in 2005. Urban growth appeared to be most rapid in the 1980s and 1990s and slowed thereafter. With continued focus on the semantics, causation, sampling, and uncertainty underlying spectral land cover classification, long-term series of Landsat images will provide increasingly robust, reliable records for a growing scientific user community. These multi-temporal datasets will be indispensable for understanding past land cover dynamics and predicting the implications of future change on the provision and management of ecosystem services. (C) 2012 Elsevier Inc. All rights reserved.

DOI:

ISSN:
0034-4257

FirstGov logo Privacy Policy and Important Notices NASA logo

Curator: Brandon Maccherone
NASA Official: Shannell Frazier

NASA Home Page Goddard Space Flight Center Home Page