Land-use change, including agricultural expansion, is one of the major drivers of biodiversity loss globally. Given the rapid pace of land-use change, data-driven, strategic, and dynamic conservation planning is imperative. We present an exemplar application of using existing data to inform conservation planning. Specifically, we developed a systematic approach for identifying areas of conservation concern due to cannabis cultivation in California, USA. We used three existing datasets: 1) camera trap data from ten projects (n = 1,186); 2) the locations of cannabis cultivation sites eradicated by law enforcement (n = 834); and 3) the locations of cultivation licenses (n = 4,366). We analyzed this data using multi-species occupancy models to estimate the occupancy and richness of 30 species, and maximum entropy models to estimate the risk of unlicensed and trespass cultivation. We then identified areas of overlap and determined the percent of suitable habitat potentially impacted by cannabis cultivation. Our results can be used to prioritize eradication, restoration, and remediation activities and to target mitigation efforts and grant funded activities. Further, our study demonstrates the utility of aggregating existing biological and socioeconomic data to inform conservation planning.