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)
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.