Assessment of Urban Expansion and its Implications on Land use Change in North East Peri-Urban Area of Nairobi Kenya.
Barbara, Esther Njiru
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Rapid urban population growth has led to not only an increasing demand for urban land more so residential use. This land is not available within the city but at the peri-urban areas where parcels of fertile agricultural land are being converted into residential use at an alarming rate. This is because of the expanding urban area to its urban fringes that accompanied by an increasing demand for land to accommodate the increasing urban developments. The general objective of this study is to a create a geospatial tool for urbanization and land cover and land use change detection in the North eastern peri-urban area of Nairobi city that can be used in decision making. Remote sensed data on land use/land cover change for the period of 1976-2010 together with any historical information and archived reference data will be used to compute spatial/temporal changes in the expansion of urban settlement and extent of land use/land cover changes. Multispectral Landsat imageries for 1976, 1987, 2000 and 2010 will be analysed using Erdas Imagine 2013 software applying object-based Classification with Maximum Likelihood Classifier will be used to classify the images into land cover and land use types. Overlay operations of the' classified images will be done under Erdas Imagine 2013 software to detect the changes that will have occurred in each cover type over the study period. Overlays will determine what actually will have changed to what, according to the land cover classes used. The process will involve a pixel-to-pixel comparison of the study year images. Combination of NDVI and image differencing (~VI) will be used on 1976 and 2010 images to determine and quantify the land cover changes that will have occurred. Accuracy assessment will be based on the GPS co-ordinates acquired during fieldwork and topographic maps through a handheld GPS receiver. Qualitative data will be analysed thematically through coding using MAXQDA and narrative analysis while Ms Excel analytical tools will be used for statistical data analysis. Data will be presented in form of thematic maps, graphs and tables.