Climate change is intensifying droughts, heatwaves, and hydrological extremes, increasing crop vulnerability and threatening global food security. This study analyzes the scientific evolution of research on remote sensing-based crop vulnerability to climate, focusing on temporal trends, geographical patterns, thematic structures, remote sensing data, and methodological approaches. A quantitative, exploratory, descriptive, longitudinal, and retrospective bibliometric analysis was applied to 2343 Scopus-indexed documents published between 1985 and 2026. Bibliometrix 5.1.1 and VOSviewer 1.6.20 were used to assess productivity, collaboration, intellectual structure, keyword co-occurrence, thematic evolution, and Reference Publication Year Spectroscopy. Results show sustained growth, with a 4% annual growth rate and a sharp acceleration after 2015, reaching 487 publications in 2025. This trend reflects a transition from descriptive crop monitoring toward predictive and operational geospatial intelligence. China, the United States, and India lead scientific production, while specialized journals concentrate dissemination. The most common remote sensing data and indicators include NDVI, MODIS, Landsat, Sentinel imagery, SAR, drought indices, vegetation condition metrics, and Google Earth Engine. Frequent methods include bibliometric mapping, keyword co-occurrence analysis, thematic clustering, machine learning, time-series analysis, and multi-sensor integration. Overall, the field is mature but still faces challenges in interoperability, geographical representation, validation, and decision-oriented applications.
Hoyos-Alayo et al. (Tue,) studied this question.