Understanding the Evidence Base for Poverty–Environment Relationships using Remotely Sensed Satellite Data: An Example from Assam, India

•We investigated poverty–environment relationships using census and satellite data.•Satellite-derived metrics explained 61% of variance in lowest welfare quintile.•Satellite-derived metrics explained 57% of variance in highest welfare quintile.•Time to town and woodland coverage were related to low welfare.•Results open new possibilities for exploring population–environment relationships. This article presents results from an investigation of the relationships between welfare and geographic metrics from over 14,000 villages in Assam, India. Geographic metrics accounted for 61% of the variation in the lowest welfare quintile and 57% in the highest welfare quintile. Travel time to market towns, percentage of a village covered with woodland, and percentage of a village covered with winter crop were significantly related to welfare. These results support findings in the literature across a range of different developing countries. Model accuracy is unprecedented considering that the majority of geographic metrics were derived from remotely sensed data.