文章基本信息

标题：Use of Remote Sensing Data to Detect Environmental Degradation in the Coastal Region of Southern Nigeria
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作者：Albert Osei ; Edmund C. Merem ; Yaw A. Twumasi 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2006
卷号：XXXVI Part 7
出版社：Copernicus Publications
摘要：Environmental degradation is one of the major issues confronting many governments around the world. This problem is acute in developing countries where the lack of proper regulatory enforcement and ineffective monitoring mechanisms due to weak legislation have led to serious environmental degradation in the form of soil, air, water pollution, degradation of native and planted vegetation and scarring of the land surface. Southern Nigeria, which is the prime focus of this study, is not an exception. The region is home to the industrial heartland sustaining the political economy of the country under the orbit of Global capital. While the region embarks upon a rapid phase of economic expansion, it faces several environmental challenges caused partly by the pressures induced by anthropocentric activities through petroleum activities, economic development and demographic changes. This continued growth has resulted in environmental problems such as coastal wetland loss, habitat degradation, water pollution, gas flaring, destruction of forest vegetation and host of other issues. The gravity of these problems underscores the urgent need to design new approaches for effectively managing these resources. Despite previous efforts, there has not been any major emphasis in the literature focusing on a remote sensing based assessment of the growing incidence of environmental change within the coastal and forest zones environment of the study area. This project explores the applications of remote sensing in the forest and coastal zone environments with emphasis on the environmental impacts of economic development in the coastal regions of Southern Nigeria
关键词：Environmental degradation; forest vegetation; coastal environment; remote sensing; GIS; satellite imagery