The issue of population density in a particular area has been delved into by this paper, and various factors that contribute to the phenomenon are examined. The study utilizes census data and satellite imagery to analyse changes in land use patterns in response to changes in population density, with a focus on identifying the factors that drive these changes and the role of land use planning. The research finds that population density has a significant impact on land use patterns, with areas of high population density experiencing more intense land use and greater pressure on natural resources. A comprehensive solution that employs statistical and geographic tools, such as SVM (Support Vector Machine) for land classification, Edge Detection with the Laplacian of Gaussian filter for calculating unused land area, and Linear Regression for predicting population density is proposed by the paper to tackle this problem. Additionally, QGIS (Quantum Geographic Information System) and its related plugins like HCMGIS and SCP are utilized by the paper to export graphical maps and satellite images for further analysis.

Population density, SVM, Edge detection, Prewitt method, Multiple linear regression, Land classification.