Evaluation of the Environmental Impacts on Urban Forests in Greater Khartoum Based on Remote Sensing and GIS Techniques

The main objective of this study is to analyze and evaluate the environmental impacts on urban forests in Greater Khartoum area during the period from 1987 to 2000 based on remote sensing and GIS techniques. This includes investigations to highlight the environmental impacts on Khartoum Sunt Forest. Generating a digital dynamic GIS model associated with Urban Forest in the study area is one of the main issues in this study. The research work aims to develop methods and techniques to model the real world for the purpose of detecting the environmental changes taken place in the study area during 1987-1996, 1996-2000 and 1987-2000. One of the main objectives is to extract sustained urban forest zones and areas subjected to be urban forest in Greater Khartoum and particularly in Khartoum Sunt Forest. A further objective of this study is to analyze environmental factors believed to have some impacts on urban forest in the study area. This includes agricultural area, cultivated area, scattered vegetation, flooded area, urban area, barren land, sand, sandy land, rocky land, hills and water bodies. A wide range of procedures has been carried out to achieve these objectives. Remotely sensed data acquired by the American Landsat Thematic Mapper (TM) imaging system in year 1987 and 1996 and Enhanced Thematic Mapper plus (ETM+) in year 2000. The acquired data covers most of Khartoum state with visible and infrared spectral bands. To produce land cover maps of the study area for year 1987, 1996 and 2000 the visible bands of the corresponding years were subjected to digital enhancement and classification operations. Digital image analysis operations have been applied to the classified images to model the environmental changes during the specified periods. The classified images have been crossed, in term of pixels, with each other to extract temporal changes for each class (environmental factors). Results obtained from the cross process were statistically analyzed to comment about the environmental changes taken place in the study area during 1987-2000. Further processing was carried out to evaluate the environmental impacts on urban forests in the study area as well as Khartoum sunt forest. Geographical Information System (GIS) as a powerful analysis tool was used to generate vector coverage (feature classes) for each classified image. Overlay and spatial analysis operations offered by the GIS environment were applied to extract sustained urban forests and areas subjected to be urban forest in the study area and Khartoum sunt forest. Furthermore, the same operations were used to model the appearance of the environmental factors individually. The contribution of each factor towards urban forest sustainability was analyzed. The study came to the conclusion that 31.21% of the study area and 22.80% of Khartoum sunt Forest were found to be sustained urban forest area. The area subjected to be urban forest was extracted as 61.30% and 84.99% respectively. Output results show that although approximately 30% of the study area was occupied by urban activities but increasing in urban activity was not on the account of the urban forest in the study area. Finally, high spectral and spatial resolutions remotely sensed data is recommended for urban forest and environmental changes detection. Other artificial intelligent systems such as Artificial Neural Networks may offer solutions for forest pattern recognition and classification without being involved into sophisticated processing techniques