Integrating Street Views, Satellite Imageries and Remote Sensing Data Into Economics and the Social Sciences.

This article reviews the integration of street views, satellite imageries, and remote sensing data into economics and social science research, highlighting how computer vision and deep learning methods enhance data retrieval and analysis. It discusses major data sources such as Google Street View, Google Earth Engine, Orbital Insight, and RS Metrics, and categorizes applications into themes including housing economics, urban planning, criminology, environmental assessment, and economic development. The review emphasizes that image data often yield more detailed and cost-effective insights than traditional methods, supporting improved policy decisions and socioeconomic understanding. It also addresses challenges such as data accessibility, reproducibility, and limitations in temporal coverage, while suggesting future research directions that leverage these technologies for broader and more nuanced analyses.