Urban Land Use Classification Using Remote Sensing and GIS Techniques

Thesis Abstract

Abstract
Urban land use classification is a crucial aspect of urban planning and development, as it provides valuable insights into the spatial distribution of different land uses within a city. This thesis focuses on utilizing remote sensing and Geographic Information System (GIS) techniques to classify urban land use, with the aim of enhancing the accuracy and efficiency of land use mapping. The study area selected for this research is a rapidly growing urban region facing challenges related to urban sprawl, land use change, and environmental degradation. The research begins with a comprehensive review of existing literature on urban land use classification, remote sensing technologies, GIS applications, and methodologies for land use mapping. The literature review highlights the importance of accurate land use classification for informed decision-making in urban planning and sustainable development. The methodology chapter outlines the research design, data collection methods, and analysis techniques employed in this study. Remote sensing data, including satellite imagery and aerial photographs, are processed using image classification algorithms to extract land cover information. GIS software is utilized to integrate and analyze the classified land use data, generating thematic maps that depict different land use categories within the study area. The results chapter presents the findings of the land use classification process, including the identification and mapping of various land use types such as residential areas, commercial zones, industrial estates, green spaces, and transportation networks. Accuracy assessment techniques are applied to evaluate the performance of the classification model and validate the accuracy of the land use maps generated. The discussion chapter provides a detailed interpretation and analysis of the research findings, discussing the implications of the classified land use information for urban planning and management. The study identifies patterns of land use distribution, spatial relationships between different land use categories, and potential areas of land use conflict or synergy within the urban landscape. The conclusion chapter summarizes the key findings of the research, highlighting the contributions of remote sensing and GIS techniques to urban land use classification. The study underscores the importance of accurate land use mapping for effective urban planning strategies, resource management, and sustainable development initiatives. Recommendations for future research and practical applications of the study findings are also provided. Overall, this thesis contributes to the advancement of knowledge in urban land use classification using remote sensing and GIS technologies, offering valuable insights and methodologies for enhancing spatial analysis and decision-making in urban planning contexts.