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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/7335

Title: Analysis of Forest Cover Change Detection
Authors: Forkuo, Eric K
Frimpong, Adubofour
Keywords: Land Use
Land Cover
Forest Cover
Change Detection
Issue Date: 2012
Publisher: International Journal of Remote Sensing Applications
Citation: International Journal of Remote Sensing Applications Vol. 2 Iss. 4, December 2012
Abstract: While the concepts of change detection analysis is not new, the emergence of new imaging sensors and geospatial technologies has created a need for image processing techniques that can integrate observation from a variety of different sensors and datasets to map, detect and monitor forest resources. In addition to timber, forests provide such resources as grazing land for animals, wildlife habitat, water resources and recreation areas and these are threatened constantly by both human impacts like forest fires, air pollution, clearing for agricultural uses, and illegal cutting. Farming activities, continued sand winning operations and the allocation of plots of land to prospective developers in and around the catchments of the Owabi dam pose a serious threat to the forest covers and the lifespan of the dam. The overall objective of this study is to map out and analyze the structural changes of forest cover using Landsat and ASTER imageries of the study area. A supervised classification was performed on three multi-temporal satellite imageries and a total of eight major land use and land cover (LULC) classes were identified and mapped. By using post-classification techniques, from 1986 to 2002 and 2002 to 2007 the forest cover has decreased by an amount of 2136.6 ha and 1231.56 ha respectively representing 24.7% and 14.2%. Generally, the results indicate that from 1986 to 2007, forest cover reduced by 3368.16 ha, representing 38.9%. Decrease in vegetation has been as a result of anthropogenic activities in the study area. An NDVI analysis was performed on these images and it was noted that there was no significant difference between the NDVI classification and the supervised classification of the images. Overlay of the reserved forest of the 1974 and the classified map of 2007 shows vegetation changed during 1986-2007 remarkably.
Description: Article published in International Journal of Remote Sensing Applications, 2012.
URI: http://hdl.handle.net/123456789/7335
Appears in Collections:College of Engineering

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