Geographic Information Systems Analysis of Crime in San Luis Obispo for 2012

The research and final project that I plan to do will be composed of a few different parts. I will be taking crime report data from the city of San Luis Obispo and analyzing it with GIS software. The data will be from the most recent reported calendar year. I will be looking at the data spatially so that I can compare the areas of the city in which crime is most prevalent. I will be creating multiple maps which will be looking individually at different types of crime, such as violent crimes, burglary and theft, assault and battery, sex crimes, alcohol and drug related crimes, and others. I hope to be able to compare the maps of individual crimes to compile a complete spatial view of the city as it relates to criminal activity. It should be interesting to compare the completed maps to the proximity to schools, bars, other local businesses, and population density, to see what has the greatest impact on where the crimes are committed. The final project will consist of a number of GIS maps of the city of SLO, an analysis of each and the implications of the findings. I would also like to do a simple analysis with all the crimes committed during one year, and another with all the crimes committed five years later so that I can examine the changes over that period. Hopefully this will illuminate some trends that influence the crime in the city and may provide some solutions for the problems. In conclusion, my final project should be a comprehensive report of the crime report data in SLO, examined spatially, and analyzed in comparison to previous years, hopefully providing insight into current trends in crime in our city

Literature analysis of international experiences in studying the theoretical and methodological framework of GIS-based demographic mapping processes

This research conducts a comprehensive analysis of GIS-based demographic mapping, synthesizing international literature to unravel evolving theoretical frameworks, spatial analysis techniques, and the integration of emerging technologies. The study reveals a convergence of Spatial Demography, Agent-Based Modeling, and Geodemographics, providing nuanced insights into population dynamics. Spatial clustering, gravity modeling, geostatistical analysis, and cellular automata modeling represent advancements in spatial analytics, enriching our understanding of migration patterns and population distribution. The integration of emerging technologies—LiDAR, Artificial Intelligence, and Blockchain—marks a transformative shift, enhancing accuracy in population density estimation and introducing novel dimensions of predictive modeling and data security. Ethical considerations, including anonymization techniques and algorithmic transparency, contribute to responsible GIS-based demographic mapping practices. Addressing challenges such as data quality issues, limited accessibility, and ethical considerations, the research proposes practical solutions, from citizen science integration to standardized GIS protocols. Future directions advocate for the adoption of 5G technology, spatial big data analytics, community-engaged mapping, and investigating the intersection of climate change and demography. The synthesis of these findings positions this research as a vital resource, guiding researchers, practitioners, and policymakers in navigating the dynamic landscape of GIS-based demographic analysis