When and why do states permit the operation of informal industries? Understanding the politics of informality -- its causes, effects, and responses to policy levers -- is a rapidly expanding and theoretically rich area of study across disciplines in the social sciences. Of primary concern to all strains of this research question is the issue of measurement: how do we study something that is inherently in the shadows? How can we measure informal industries? The goal of this paper is threefold: First, to synthesizes the existing literature discussing the disadvantages (including ethical) and the advantages to measuring informal industries with geospatial data. Next, I introduce a concept-to-measure approach to constructing spatially and temporally disaggregated datasets indicating the existence of -- and enforcement against -- informal industries using publicly available data and AI processing models underutilized in current political science research. I end with the construction of panel datasets measuring two types of illicit industries across Nigeria, Africa's largest country: illicit mining and informal road transport; as well as an R package intended to extend the dataset to other cases. I conclude with some analysis of these datasets, which suggests that the timing of informal industry enforcement at the subnational level depends on the nature of local political networks.