The spectral characterization of land covers using earth observation technologies is a constantly developing and highly demanded field for the study and monitoring of natural resources, agricultural activity, and urban planning. In urban applications, these technologies are gaining ground in obtaining highly detailed primary information through field spectroscopy, with key applications in risk management, cadastral management, and climate change. This study presents the spectral characterization of eight common building roof materials, based on reflectance measurements in the 350–2500 nanometer range, for a total of 938 effective spectral signatures of eight roof materials captured across 156 sampling points in five Colombian cities during the first semester of 2025. The methodology included a specific sampling and subsampling design to capture spectral variance at the roof level, using a NaturaSpec spectroradiometer and a contact probe. An analysis of the spectral library, which included descriptive and feature importance analysis using Random Forest and Spectral Normal Variate Normalization, revealed that the material types characterized in all five cities exhibit significant similarities in their absorption patterns, trends, and peaks, with the exception of translucent materials such as plastics. Furthermore, while the spectral response is dominated by building roofs color in the visible region, the short-wave infrared region has a greater spectral separability of material type and conservation status. These spectral data and, their corresponding metadata, were captured and cataloged to contribute to the construction of a National Spectral Bank, with the goal of consolidating a comprehensive Colombian spectral database for applications in agriculture, environmental monitoring, and urban management.

Consolidated field spectral ground-truth data of urban surfaces are scarce in Latin America, where construction materials, building traditions, and aging dynamics differ from those of the temperate cities for which most existing libraries were developed. This study built and characterized a full-range (350–2500 nm) field spectral library of eight roof materials across five Colombian cities in the Andean and Caribbean regions and identified the spectral regions that maximize their separability. The sampling was designed for field spectra capture under two constraints common in these settings, the absence of prior information on material distribution and the limited accessibility of roofs, following a documented institutional protocol with structured metadata. In total, 859 signatures from 151 georeferenced roofs were acquired with a Spectral Evolution NaturaSpec spectroradiometer and a contact probe. Spectral separability was quantified with the Spectral Angle Mapper (SAM) between median endmembers, and the five materials with sufficient support were classified with Random Forest, Support Vector Machine, and XGBoost on original and Standard Normal Variate (SNV) normalized signatures, under a roof-grouped, leakage-controlled evaluation. Roof color drives the response in the visible region, whereas the shortwave infrared concentrates the absorption features that discriminate composition. The mean SAM angle between materials (23.4°) is considerably larger than that between cities for the same material (4.3–8.3°), indicating that a material's signature remains consistent across the five cities and supporting their aggregation into a single library. The library and its structured metadata provide a reusable ground-truth resource for urban Earth observation in tropical contexts.

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.