Detecting Urban Markets with Satellite Imagery : An Application to India

This paper proposes a methodology for defining urban markets based on economic activity detected by satellite imagery. We use nighttime lights data, whose use in economics is increasingly common, to define urban markets based on contiguous pixels that have a minimum threshold of light intensity. The coarseness of the nightlight data and the blooming effect of lights, however, create markets whose boundaries are too expansive and too smooth relative to the visual inspection of actual cities. We compare nightlight-based markets to those formed using high-resolution daytime satellite imagery, whose use in economics is less common, to detect the presence of builtup landcover. We identify an order of magnitude more markets with daytime imagery; these markets are realistically jagged in shape and reveal much more within and across-market variation in the density of economic activity. The size of landcover-based markets displays a sharp sensitivity to the proximity of paved roads that is not present in the case of nightlight-based markets. Our results suggest that daytime satellite imagery is a promising source of data for economists to study the spatial extent and distribution of economic activity