Earth Observation Data for Sustainable Management ofWater Resources to Inform Spatial Planning Strategies

Water is a vital resource for sustaining human life, well-being, and the Earth's biodiversity and ecosystems. However, its availability and usability are decreasing due to strong anthropogenic pressure and intense climatic stress, leading to a variety of environmental issues, including desertification. Consequently, areas exposed to these factors, such as those in Southern Italy, are highly vulnerable to desertification. To address soil deterioration, it is crucial to identify and implement appropriate land management strategies aimed at promoting sustainability and improving ecosystem services. Remote sensing techniques provide a low-cost and non-destructive tool for extracting baseline information on water bodies, land use/cover classes, and Earth morphology features. When combined with meteorological data, these techniques can help identify the most effective, efficient, and sustainable water management strategies to tackle desertification. This is made possible by the vast amount of publicly available medium-resolution satellite data, such as Landsat and Sentinel missions, as well as open-source cloud infrastructures formanaging big geographic data, likeGoogleEarth Engine (GEE). The primary goal of this study is to provide a reference framework for a comprehensive workflow that moves from available data, through their proper elaboration with models, to knowledge management aimed at informing public policies. The case study presented provides a snapshot of the current state of natural water resource availability in the Apulian environment by identifying and evaluating the key hydrological balance components provided by the BIGBANG model. The input data for the model were images from Landsat missions and climate data handled in GEE. The results from the BIGBANG model were then used to define a scenario analysis to determine the best water resource planning and management policies.