Development of an Automated Road Network Extraction System using Remote Sensing and GIS Techniques

Thesis Abstract

Abstract
This thesis presents the development of an Automated Road Network Extraction System utilizing the integration of Remote Sensing and Geographic Information System (GIS) techniques. The project aims to address the increasing need for accurate and efficient mapping of road networks for various applications such as urban planning, transportation management, and disaster response. The proposed system utilizes satellite imagery and GIS tools to automatically extract road features, overcoming the limitations of traditional manual mapping methods. The research begins with a comprehensive review of existing literature on remote sensing, GIS, and road network extraction techniques. The literature review covers topics such as image processing, feature extraction algorithms, and the integration of remote sensing data with GIS for mapping purposes. The chapter highlights the importance of automated approaches in improving the speed, accuracy, and cost-effectiveness of road network mapping. The methodology chapter outlines the step-by-step process of developing the Automated Road Network Extraction System. This includes data acquisition, preprocessing of satellite imagery, feature extraction algorithms, spatial analysis using GIS tools, and validation of extracted road networks. The chapter also discusses the selection criteria for the study area, the choice of satellite imagery, and the parameters used in the feature extraction algorithms. The findings chapter presents the results of the system implementation on a selected study area. The extracted road networks are evaluated based on accuracy measures such as precision, recall, and F1 score. The chapter also discusses the challenges encountered during the implementation process and proposes potential solutions for improvement. Visual representations of the extracted road networks are provided to demonstrate the effectiveness of the system. In the conclusion and summary chapter, the key findings and contributions of the research are summarized. The study highlights the potential of automated road network extraction systems in enhancing the efficiency of mapping processes and improving the quality of spatial datasets. The chapter also discusses the implications of the research for future applications and areas of further study. Overall, this thesis contributes to the field of Surveying and Geo-informatics by presenting a novel approach to road network extraction using Remote Sensing and GIS techniques. The Automated Road Network Extraction System developed in this study offers a promising solution for accurate and efficient mapping of road networks, with implications for various sectors including urban planning, transportation management, and disaster response.