Monitoring Nature of Nairobi City Land Features from Landsat 5 Images Using Index-Based Mapping

Abstract

Urban environments are complex and heterogeneous ecosystems characterized by mixed land use and land cover (LULC). They form important centers of social integration and generation of national wealth. However, urban areas especially in developing countries suffer from poor planning; mismanagement and uncoordination. Evaluation of dynamics driven by LULC changes in these ecosystems is key in management of urban areas. In evaluating urban environments, land use and land cover mapping using multispectral classification methods has been widely utilized. Supervised classification techniques require the use of expert local area knowledge for accurate classification. Application of remote sensing indices in mapping has not been widely used yet they are effective in the extraction of general land use and land cover. Existing remote sensing indices are used for mapping and emphasizing particular land uses/cover. Such indices cannot be applied to map multiple LULC in heterogeneous urban environments. This study seeks to apply an improved thematic based remote sensing index (ITRSI) to map open water, built up areas, vegetation and bare land within the city of Nairobi in Kenya. The results were then compared to those of supervised and unsupervised classification to assess the efficacy of this improved method in extracting general land use and land cover. The index offers an alternative method to map LULC and classify urban areas in Kenya based on land use and land cover data.