Remote Senesing and Gis Based Urban Land Suitablity Modeling at Parcel Level Using Multicritria Decision Analysis; a Case Study of Bole Sub City, Addis Abeba, Ethiopia

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Date

2015-06-06

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Addis Ababa University

Abstract

This research was carried out to evaluate the suitability of the land for urban development activities using remote sensing and GIS applications with the integration of MCDA approach. Evaluation of urban land in terms of suitability classes based on the method described in FAO guide line for land evaluation the parameters used for the evaluation of land suitability for urban development activities were slope, soil type, rivers and streams, soil depth, geology, road network, ground water prospect .This research aimed at assessing urban land suitability modeling of the study area through Geographic Information System and remote Sensing based urban land suitability modeling techniques, by preparing maps that enhance proper urban land use for sustainable urban land development and management. Spatial Data was processed and generated from these specified parameters to generate urban land suitability model map at parcel level finally. IDRISI was applied to generate weight for each parameter according to their level of importance. By the help of ArcGIS weight was given for each parameter and finally With spatial analytic capability of Geographic information system weighted overlay method was used to generate the final urban land suitability model map from which urban land suitability maps were developed. Accordingly the final result of this research shows 72.09% of the total area was suitable for urban development activities and 29.33% was unsuitable for urban development activities the current urban development activities of the study area were in the area which was identified as suitable area. Finally this research recommends that areas identified us unsuitable area needs additional improvements after urban development activities made.

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Keywords

Remote Sensing, Geographic Information System, Suitability Modeling, Analytic Hierarchy Process

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