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Open Geosciences

formerly Central European Journal of Geosciences

Editor-in-Chief: Jankowski, Piotr

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2391-5447
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Exploring Land use and Land cover change in the mining areas of Wa East District, Ghana using Satellite Imagery

Prosper Laari Basommi
  • School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China; Department of Environment and Resource Studies, UDS, Wa-Ghana
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Qingfeng Guan
  • School of Information Engineering, China University of Geosciences, Wuhan 430074, China; National Engineering Research Center of GIS, China University of Geosciences, Wuhan 430074, China
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Dandan Cheng
Published Online: 2015-11-06 | DOI: https://doi.org/10.1515/geo-2015-0058

Abstract

Satellite imagery has been widely used to monitor the extent of environmental change in both mine and post mine areas. This study uses Remote sensing and Geographical Information System techniques for the assessment of land use/land cover dynamics of mine related areas in Wa East District of Ghana. Landsat satellite imageries of three different time periods, i.e., 1991, 2000 and 2014 were used to quantify the land use/cover changes in the area. Supervised Classification using Maximum Likelihood Technique in ERDAS was utilized. The images were categorized into five different classes: Open Savannah, Closed Savannah, Bare Areas, Settlement and Water. Image differencing method of change detection was used to investigate the changes. Normalized Differential Vegetative Index valueswere used to correlate the state of healthy vegetation. The image differencing showed a positive correlation to the changes in the Land use and Land cover classes. NDVI values reduced from 0.48 to 0.11. The land use change matrix also showed conversion of savannah areas into bare ground and settlement. Open and close savannah reduced from 50.80% to 36.5% and 27.80% to 22.67% respectively whiles bare land and settlement increased. Overall accuracy of classified 2014 image and kappa statistics was 83.20% and 0.761 respectively. The study revealed the declining nature of the vegetation and the significance of using satellite imagery. A higher resolution satellite Imagery is however needed to satisfactorily delineate mine areas from other bare areas in such Savannah zones.

Keywords: Land use / Land cover; NDVI; Vegetation; Remote sensing and GIS

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About the article

Received: 2015-03-20

Accepted: 2015-10-16

Published Online: 2015-11-06


Citation Information: Open Geosciences, ISSN (Online) 2391-5447, DOI: https://doi.org/10.1515/geo-2015-0058.

Export Citation

©2015 L. B. Prosper et al.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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