Use of Satellite Data to Study the Impact of Land-Cover/Land-Use Change in Madison County Alabama
- 1 USDA, ARS, National Germplasm Repository Subtropical Horticulture Research Station, United States
Abstract
The monitoring of land/use land cover changes along the northern part of Madison County Alabama are essential for the developers, planners, policy makers and management of government, public and private organizations. Remote sensing was used to analyze and study land-use/land-cover use changes impact on the environment of Madison County Alabama. This study area was selected because it is one of the fastest growing areas in the state of Alabama. The study used data sets obtained from several sources. Remote sensing images, land-use/land-cover use maps, global positioning data. The remote sensing images were LANDSAT Thematic Mapper (TM) images acquired during April 1987 and May 1997. The data was processed and analyzed using MAP-X/RS and ERDAS. Six classes or categories of land-use/land-cover were analyzed to determine changes and the relationship to suburban sprawl. Each method used was assessed and checked in field. Six land use/land cover classes are produced. The overall accuracy for the 1987 image is (78.92%) and for the 1997 image is (85.44%) Analysis of the images for 1987 and 1997 showed a (26 and 15%) increase in the urbanization and industrial development respectively and a decrease in all other classes. The most significant decrease (25%) was in the pastures class, however, less significant changes were observed for the water resources and forest. The results from this study could be beneficial to state/county planners, researchers and policy makers.
DOI: https://doi.org/10.3844/ajassp.2009.656.660
Copyright: © 2009 Tomas Ayala-Silva, Garry Gordon and Robert Heath. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Remote sensing
- geospatial
- LANDSAT
- classification