GeoReg is an innovative regression model designed to estimate critical socio-economic indicators like regional GDP and education levels, particularly in data-scarce regions of developing countries. Developed by researchers from the Korea Advanced Institute of Science and Technology and the Max Planck Institute, GeoReg harnesses satellite imagery and web-based geospatial data, augmented by large language models (LLMs) to identify relationships between data features and target indicators. This approach allows for effective estimations with minimal labeled data. By categorizing correlations as positive, negative, or irrelevant, GeoReg enhances accuracy through tailored weight constraints, improving estimations significantly. In tests across South Korea, Vietnam, and Cambodia, GeoReg demonstrated an impressive 87.2% success rate, outperforming traditional methods. This breakthrough offers a scalable, interpretable framework for policymakers to address socio-economic challenges, contributing to sustainable development and effective decision-making, especially in low-income areas where reliable data is often lacking.
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