A Method For Normalizing Classified Land-Cover Imagery For Use In Change-Detection Analysis
Abstract
The availability of a long historical record of Landsat satellite imagery made possible the development of multitemporal land-cover mapping for large regions. Use of these data sets for change detection and other landscape analyses sometimes is hampered by differences in the image-classification methods employed at different times. To resolve these problems for 1987 and 2003 land-cover data for Florida from the Florida Fish and Wildlife Conservation Commission, the authors developed an automated GIS-based technique that relied on comparisons between the two land-cover data sets as well as ancillary land-use data from Florida's five Water Management Districts. This Land Cover Correction Process demonstrably improved the accuracy of the 1987 and 2003 land-cover data and permitted more reliable measures of anthropogenic land-use changes. The improved habitat loss rates estimated for ecologically important vegetative communities such as pinelands, sandhills, and scrub using the corrected data provide valuable guidance for conservation efforts in Florida.
Publication Date
1-1-2015
Publication Title
URISA Journal
Volume
26
Issue
2
Number of Pages
5-24
Document Type
Article
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
84939521273 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84939521273
STARS Citation
Gilbrook, Michael J. and Weishampel, John F., "A Method For Normalizing Classified Land-Cover Imagery For Use In Change-Detection Analysis" (2015). Scopus Export 2015-2019. 32.
https://stars.library.ucf.edu/scopus2015/32