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Land abandonment is among the most complex la nd use change processes driven by a multiplicity of anthropogenic and natural factors, such as agricultural over-exploitation, implementation of agricultural policies, socio-economic and climatic aspects. Therefore, it is necessary to deepen the effects of land abandonment based on methodologies that are as multidisciplinary as possible. Environmental and social problems related to abandonment include soil erosion and environmental degradation. Approaches combining GIS (Geographic Information System), remote sensing, and image analysis techniques allow for assessments and predictions based on integrating theoretical models with advanced geospatial and geostatistical models. One of the most widely used models for soil erosion estimation is the Revised Universal Soil Loss Equation (RUSLE). The present work developed a model using remote sensing and GIS tools to investigate some factors of the RUSLE equation to evaluate the adverse effects of soil erosion in areas covered by arable crops and subsequently abandoned. To identify potentially degraded areas, two factors of the RUSLE were related: the C Factor describing the vegetation cover of the soil and the A Factor representing the amount of potential soil erosion. Through statistical correlation analysis with the RUSLE factors, based on the deviations from the average erosion values and mapping of the areas of vegetation degradation relating to arable land, the areas identified and mapped are susceptible to soil degradation.

Sustainable land management is one of the key actions for the achievement of objectives set by the 2030 Agenda for Sustainable Development. In particular, land represents a fundamental resource to address issues of climate change, biodiversity preservation, maintaining ecosystem services, and at the same time ensuring shared prosperity and well-being. Therefore, it is necessary to activate strategies to monitor changes in land use and land cover in order to evaluate strategies for proper management. To do this, the new open source geospatial analysis tools and the increasing availability of remote sensed open data can allow the activation of methodologies for monitoring changes in land use and land cover in order to provide data usable in other research areas or, for example, to implement a decision support system for environmental sustainability. In this study, a GIS approach based on open remote sensing data has been used to perform a spatial analysis of land cover changes within the Basilicata region (Southern Italy) that is spatially expeditious yet accurate. The results showed a very evident land transformation with important repercussions on the environmental components. The ease of use of techniques makes this methodology replicable in other territory and can be used as a preliminary approach to sustainable development model.