Thesis Abstract

Abstract
The rapid urbanization and land use changes witnessed in recent years have highlighted the crucial need for effective methods to monitor and classify urban land use. This research project focuses on the integration of Geographic Information Systems (GIS) and Remote Sensing techniques to enhance urban land use classification and change detection. The study aims to provide a comprehensive analysis of urban land use patterns and changes using advanced spatial technologies. Chapter One of the thesis introduces the research topic, provides the background of the study, states the problem statement, outlines the objectives, discusses the limitations and scope of the study, emphasizes the significance of the research, and presents the structure of the thesis. Furthermore, key terms related to the study are defined to ensure clarity and understanding. Chapter Two consists of a detailed literature review that explores existing research, theories, and methodologies related to GIS, Remote Sensing, urban land use classification, and change detection. This chapter critically analyzes relevant studies to establish a theoretical framework for the research project. Chapter Three focuses on the research methodology employed in this study. It includes the research design, data collection methods, data preprocessing techniques, image classification algorithms, accuracy assessment procedures, change detection approaches, and validation methods. The chapter also discusses the software tools and technologies utilized for data analysis and interpretation. Chapter Four presents the findings and results of the study, highlighting the classification of urban land use types and the detection of land use changes over time. The chapter includes detailed discussions on the accuracy of the classification results, the effectiveness of the change detection techniques, and the implications of the findings for urban planning and management. Finally, Chapter Five presents the conclusion and summary of the research project. The chapter discusses the key findings, implications, limitations, and future research directions. The study concludes by emphasizing the importance of integrating GIS and Remote Sensing for urban land use classification and change detection and its potential applications for sustainable urban development. In conclusion, this thesis contributes to the existing body of knowledge in the field of Surveying and Geo-informatics by demonstrating the effectiveness of integrating GIS and Remote Sensing for urban land use classification and change detection. The research findings provide valuable insights for urban planners, policymakers, and researchers seeking to enhance land use monitoring and management practices in rapidly evolving urban environments.

Thesis Overview

The project titled "Integration of GIS and Remote Sensing for Urban Land Use Classification and Change Detection" focuses on the utilization of Geographic Information Systems (GIS) and Remote Sensing technologies to enhance the understanding of urban land use dynamics. This research aims to address the challenges associated with urban development, land use changes, and their impacts on the environment and society. Urban areas are constantly evolving due to population growth, economic activities, and infrastructure development. These changes have significant implications for urban planning, resource management, and environmental sustainability. GIS and Remote Sensing offer powerful tools for monitoring, analyzing, and predicting urban land use changes by providing spatial data and analysis capabilities. The project will begin with a comprehensive literature review to explore existing studies, methodologies, and technologies related to urban land use classification and change detection using GIS and Remote Sensing. This review will establish the theoretical framework and guide the research methodology. The research methodology will involve data collection, processing, and analysis using GIS software and remote sensing imagery. Various classification algorithms and change detection techniques will be applied to satellite images and other geospatial data to identify and map urban land use categories and detect changes over time. The findings of the study will be discussed in detail in Chapter Four, highlighting the effectiveness and limitations of the GIS and Remote Sensing approach for urban land use classification and change detection. The results will provide valuable insights into urban dynamics, land use patterns, and trends, which can inform decision-making processes in urban planning, environmental management, and sustainable development. In conclusion, this project will contribute to the field of surveying and geo-informatics by demonstrating the potential of GIS and Remote Sensing technologies for urban land use analysis. By integrating these tools, the research aims to enhance our understanding of urban environments, support evidence-based decision-making, and promote sustainable urban development practices.