Sediment flow connectivity index data for the Apulia region (Italy): An open-source geodatabase and the innovative CONNECTOSED WebGIS platformZenodo - Alok Kushabaha; Domenico Capolongo; Giovanni Scicchitano; Floriana Rizzo; Marina Zingaro (Data in Brief)
An open-source geodatabase and its associate WebGIS platform (CONNECTOSED) were developed to collect and utilize data for the Sediment Flow Connectivity Index (SfCI) for the Apulia region of southern Italy. Maps depicting sediment mobility and connectivity across the hydrographic basins of the Apulia region were generated and stored in the geodatabase. This geodatabase is organized into folders containing data in TIFF, shapefile, Jpeg and Pdf formats, including input variables (digital elevation model, land cover map, rainfall map, and soil units dataset for each hydrographic basin), classification graphs (ranking of variable values), dimensionless index maps (slope, ruggedness, rainfall, land cover, and soil stability) and key products (maps of sediment mobility, SfCI, and applied SfCI). The geodatabase maintains the mapping methodology underlying the SfCI algorithm by integrating various Earth datasets from multiple sources through ArcMap™, QGIS® and Matlab® software. This approach aligns surface characteristics with driving forces to describe the spatial variability of sediment pathways and identify hotspot areas. The availability of both input and processed data enables the computation and continuous updating of this applied geomorphological indicator, which is useful for assessing susceptibility to rapid Earth surface changes related to multi-hazard exposure. The geodatabase and the CONNECTOSED platform are valuable tools for researchers and stakeholders involved in land monitoring. The geodatabase and the CONNECTOSED platform are essential tools for researchers, policymakers, and stakeholders involved in land monitoring and environmental management. These tools provide open access to extensive datasets and detailed descriptions of surface dynamics, establishing connections between the causes and effects of extreme phenomena, such as floods, landslides, fires, soil pollution. This integration allows users to combine various forms of environmental data, a capability that is vital for enhancing scientific knowledge, supporting the development of insights, and fostering more informed, evidence-based decision-making in land use planning, conservation efforts, and sustainability initiatives.