Multitemporal land-cover classification of Mexico using Landsat MSS imagery
A complete land-cover classification of Mexico was performed using Landsat Multi-Spectral Scanner (MSS) imagery corresponding to years 1974, 1986 and 1990 (± 1 y). The categorization of the approximately 2 M km2 geographical region included the classification of approximately 300 equivalent scene images. Vegetation experts throughout the country provided an initial 250-class inventory of major vegetation associations by applying an unsupervised classification approach. A final regrouping was performed to produce a generalized thematic product containing 12 classes to provide a consistent national scale product. Classification accuracies were evaluated for each scene by means of cartographic comparison using two independently developed reference datasets corresponding to the 1970s and 1990s. An automated evaluation procedure was developed that incorporated decision rules to duplicate the results obtained using a manual accuracy assessment procedure. Overlaying both the image and the digital cartographic information allowed for the comparison of randomly selected pixels within each image scene. An overall accuracy for the three epochs of 62% was obtained for the 300 image scenes. Study results have provided a historical baseline documenting vegetation extent and distribution across Mexico over the two-decade period. This study serves as a possible model for subsequent North American land-cover characterization efforts.
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Document Type: Research Article
Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, 04510 México, DF; e-mail: [email protected]
Dirección General de Servicios de Cómputo Académico, Universidad Nacional Autónoma de México, 04510 México, DF
US Environmental Protection Agency, National Exposure Research Laboratory (MD-56), Research Triangle Park, NC 27771, USA
Instituto de Geografía, Universidad Nacional Autónoma de México, 04510 México, DF
Publication date: 01 June 2003
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