Satellite images and deep learning for the prediction of socioeconomic indicators in the Vale do Ribeira - Machicao, Jeaneth; Costa, Iago Fava da; Triñanes, Enrico; Corrêa, Pedro (Anais do Brazilian e-Science Workshop (BreSci); 2022: Anais do XVI Brazilian e-Science Workshop, 2022)
Due to low awareness and low investment in data collection and processing in developing countries, industry has struggled to plan and collaborate with public policy on data-driven socioeconomic decisions. This paper presents a deep learning approach to estimate socioeconomic indicators using satellite imagery. For this purpose, a region in southeastern Brazil called Vale do Ribeira was selected as a study case due to its data availability and environmental relevance. We used publicly available data to analyze three socioeconomic indicators: Longevity, Income and Literacy, the main representatives of the Human Development Index. Our preliminary results show a relevant correlation between satellite imagery and the income indicator, although they are not yet conclusive for longevity and literacy.