Against the backdrop of serious global environmental problems, satellite imagery for the analysis and monitoring of land transformation is attracting attention. Especially in developing countries where data are scarce, the analysis of satellite image data using spatial information technology is gaining prominence as a powerful tool for understanding changes in urban environments. Geographers are expected to deepen empirical research by creating versatile geospatial data, developing sophisticated spatial analysis functions, constructing new methodologies, and applying them to regional geography and area studies. In the era of big data utilization, the development of spatial information technology, which enables instant visualization and simultaneous analysis of vast amounts of geospatial information, has forced geographers to reconsider research methods and conventional concepts of time and space. It has prompted a shift from aggregative to nonaggregative thinking, from spatial to spatiotemporal analysis, from batch to realtime processing, from modeldriven to datadriven forecasting, and from hypothesis testing to hypothesis building.