Rachel Bellamy, Kuntal Dey, et al.
IEEE Software
Satellite imagery is a form of big data that can be harnessed for many social good applications, especially those focusing on rural areas. In this article, we describe the common problem of selecting sites for and planning rural development activities as informed by remote sensing and satellite image analysis. Effective planning in poor rural areas benefits from information that is not available and is difficult to obtain at any appreciable scale by any means other than algorithms for estimation and inference from remotely sensed images. We discuss two cases in depth: the targeting of unconditional cash transfers to extremely poor villages in sub-Saharan Africa and the siting and planning of solar-powered microgrids in remote villages in India. From these cases, we draw out some common lessons broadly applicable to informed rural development.
Rachel Bellamy, Kuntal Dey, et al.
IEEE Software
Kush R. Varshney, Lav R. Varshney
IEEE Trans. Inf. Theory
Diego Garcia-Olano, Yasumasa Onoe, et al.
ACL-IJCNLP 2021
Flavio Du Pin Calmon, Dennis Wei, et al.
NeurIPS 2017