ABSTRACT As urbanization continues, urban water resource dynamics are increasingly crucial for sustainable city planning, flood risk mitigation, and long‐term water security. Geospatial and remote sensing tools enable efficient monitoring of water resources in rapidly growing cities, aiding decision‐making for sustainable urban planning. This research examined spatiotemporal changes in 17 lakes within the rapidly expanding Dallas‐Fort Worth (DFW) metropolitan area in the United States from 1984 to 2021, using the Global Surface Water (GSW) dataset via cloud‐based remote sensing (Google Earth Engine, GEE) and non‐cloud‐based remote sensing (ArcGIS Pro). No statistically significant differences were found between the two datasets and methods with only slight differences depending on specific lake and classification approach, suggesting that both the ArcGIS Pro and GSW‐GEE methods can effectively detect geospatial and temporal changes in lakes. Overall, this study highlights the importance of selecting the appropriate dataset and method for analyzing spatiotemporal changes in urban lake environments.
Raad et al. (Sun,) studied this question.