vegetation-based indicators with soil-moisture proxies and socioeconomic components reveals risk variability at monthly scales while clarifying which dimensions remain structurally persistent, thereby supporting seasonally targeted and spatially differentiated interventions (https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2025.1564900/full). Likewise, projecting ecological responses under climate change benefits from ensemble niche modeling and explicit checks on extrapolation, producing scenario-aware evidence that can guide conservation planning and resource allocation for ecologically and economically relevant species is discussed in the following paper (https://www.frontiersin.org/journals/plant-science/articles/10.3 389/fpls.2025.1517060/full).Importantly, the Research Topic also illustrates how GIS -RS toolkits are increasingly central to providing solutions to the energyenvironment nexus problem. Urban photovoltaic potential is not merely a function of regional climate; it is conditioned by three-dimensional urban form, shading, and sky-view constraints that shape irradiance at the neighborhood scale. Integrating microclimate simulation with LiDAR-based 3D morphology provides actionable guidance for distributed PV deployment aligned with urban renewal and climate-adaptive design (https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2025.1534576/full). At broader scales, multi-criteria suitability analysis that fuses long-term meteorological and RS products can identify priority development zones and constraint-dominated regions, supporting strategic siting and energy-structure optimization (https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2024.1528134/full).Taken together, these contribution of these papers point to three shared directions for further and future investigation. First, progress will depend on tighter coupling between physical understanding, spatial context, and AI/MLso that models remain robust in optically complex waters, extreme climates, and heterogeneous landscapes. Second, the next step is operationalization: developing transferable pipelines that bridge pixel-to-basin and street-to-region scales while moving closer to near-real-time delivery. Third, multi-source and multi-modal (i.e., data from different sensors and modalities) fusion must be accompanied by clearer uncertainty quantification and communication, ensuring that outputs are not only accurate but also interpretable and trustworthy for decision-makers.We hope this collection encourages continued cross-disciplinary collaboration and accelerates the development of geospatial methods and data products that can support sustainable water and ecosystem management, environmental monitoring, and low-carbon transitions in a rapidly changing world.
Pan et al. (Tue,) studied this question.