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Soil degradation is a phenomenon that describes the degradation of soil quality due to which agricultural land in particular is unproductive as a consequence of the loss of ability to produce crops and biomass. The causes are many but, especially in the inland areas of the Mediterranean regions, some dynamics related to agriculture have particularly influenced the grading process. Specifically, agricultural over exploitation with unsustainable practices and land abandonment are causing ecological alterations that require contextual analysis to assess the medium and long-term effects. The aim of this work is to investigate the role of some factors that make up the RUSLE index have in the detection and monitoring of potentially degraded areas. In particular, the areas cultivated with arable crops were chosen as the area to be analyzed, because the average annual rate of soil erosion (A factor in RUSLE equation) is high despite the presence of vegetation cover and shown evident problems due to the phenomenon of degradation. In order to identify the potential degraded areas, two factor of RUSLE index have been correlated: C factor that describes the vegetation cover of the soil and A factor which represent the amount of potential soil erosion. All methodologies have been applied in a rural area in the northern part of Basilicata Region (Italy) using GIS and remote sensing approaches, as allows the possibility to perform a series of a complex studies and can be efficiently implemented in environmental monitoring plans.

Fires are one of the main causes of environmental degradation as they have an impact on flora and fauna, can also strongly influence ecological and geomorphological processes and permanently compromise the functionality of the ecosystems and soils on which they impact. The severity of the fire event influences the superficial hydrological response and the consequent loss of soil. Precipitation on the basins recently affected by fires produces an increase in the outflow which commonly transports and deposits large volumes of sediment, both inside and downstream of the burned area. In the years following the fire, the loss of soil is very high and the degradation processes of the soils are much greater than in the pre-event. The aim of this study is to evaluate the potential annual loss due to post-fire erosion using remote sensing techniques, RUSLE (Revised Universal Soil Loss Equation) methodology and GIS tecniques in nine different event occurred in 2019 in the northern part of the Apulia Region (Southern Italy). Geographic Information System techniques and remote sensing data have been adopted to study the post-fire soil erosion risk. Satellite images are the most appropriate for environmental monitoring as they provide high resolution multispectral optical images, infact are able to monitor the development of vegetation by assessing the water content an changes in chlorophyll levels. This study can be useful to spatial planning authorities as a tool for assessing and monitoring eroded soil in areas affected by fires, representing a useful tool for land management.

Soil erosion in fired areas is one of the main environmental problem involves degrading the quality of the soil and reducing the productivity of the affected lands. The aim of this work is to implement a procedure that analyzes the change detection of the potential soil eroded in a burned area, and discriminate the amount of potential soil loss. As part of the MESARIP project (in agreement with the Regional Civil Protection) in order to implement the analyses of soil erosion pre and post fire event, using Sentinel 2 data and with the RUSLE (Revised Universal Soil Loss Equation) method in a GIS open source environment, a graphical model has been developed. The application of the RUSLE requires a series of consequential spatial analysis elaborations and, according to this scheme, the model has been developed with the Graphical Modeler. QGIS contains in a single environment a multiplicity of tools and algorithms native to other open source GIS software, such as, for example, SAGA GIS and GRASS GIS. The user interface is very simple and requires basic and thematic input data such as DEM, MASK areas or vegetation indices etc. The advantages in the construction of the model can be identified in the standardization of map algebra operations and also in the speed of execution of the steps. Currently the model has been tested in some burned areas in 2019 located in the northern part of the Apulia Region and will be tested in operational mode during the 2020 summer season.