Recent advancements in data collection have expanded the tools and information available for urban and spatial-based research. This paper presents an overview of spatial big data sources used in urban science and urban economics, with the goal of directing and enriching future research by other applied economists. We structure our discussion around data origins and analytical methods, discussing geographic information maps, GPS and CDR, textual repositories, social media, credit card transactions, street imagery, sensor readings, volumetric data, street patterns, transportation metrics, public records, geocoded historical data, business analytics, real estate transactions, and crowdsourced input. While aiming to provide an overarching perspective, we also touch upon common challenges in urban big data research, especially those unique to data collection, analysis, and inference.