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

¹ “Tashkent Institute of Irrigation and Agricultural Mechanization Engineers” National Research University, Tashkent, 100000, Uzbekistan
² Institute for Retraining and Advanced Training of Physical Culture and Sports Specialists, Tashkent, 100042, Uzbekistan
³ Tashkent State Pedagogical University, Tashkent, 100185, Uzbekistan
⁴ Termez Institute of Agrotechnology and Innovative Development, Termez, 190100, Uzbekistan
⁵ Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi, Xinjiang
⁶ Uzbek-Finnish Pedagogical Institute, Samarkand, 230044, Uzbekistan

^* Corresponding author: s.abdurakhmonov@tiiame.uz

Abstract

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.