In recent years, there has been substantial interest in obtaining geospatial information on specific physical characteristics of buildings, such as roof materials, information that is key for estimating property values. However, collecting this data is resource-intensive and requires extensive fieldwork. This review article presents a bibliometric and descriptive analysis of the main trends in the study and mapping of roof materials and urban land covers, whit a focus on indirect methods such as remote sensing. Among the most notable findings is that artificial intelligence algorithms have become the primary tool for processing Earth observation data, and that multiple sensor data integration is one of the most commonly used techniques for data preparation in the study of roof materials. The way forward for remote sensing and urban land cover studies requires, therefore, innovation in the use of emerging technologies to improve identification, classification, and mapping accuracy of urban features and covers.