GIS-Based Crime Density Mapping Using Data Analytics: A Case Study for Manila City

Crime poses a significant concern for personal safety, especially in densely populated areas like Manila City, Philippines. Despite ongoing efforts to combat crime, individual safety remains a pressing issue. This study aims to address this problem by developing an innovative crime-mapping solution using a GIS-based system. The objective is to design a mapping system that visually represents crime density through color-coded indicators. The findings demonstrate the system's capability to generate information across different time points and accurately forecast annual crime rates. Throughout the testing phase, the system consistently delivers reliable outcomes, validated using data from the Manila Police District Headquarters. The findings of this research have practical application for law enforcement agencies and urban planners in Manila City, as the developed GIS-based system can assist in allocating resources and implementing targeted crime prevention strategies. A crime risk forecasting system, considering factors such as crime type, location, timing, day, and frequency, can anticipate potential criminal activity. The developed GIS-based system provides a valuable tool for crime forecasting and enhancing public safety in Manila City.