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Assessment and Monitoring of Soil Erosion Risk and Land Degradation in Arable Land Combining Remote Sensing Methodologies and RUSLE Factors

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Computational Science and Its Applications – ICCSA 2021 (ICCSA 2021)

Abstract

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.

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Correspondence to Biagio Tucci , Gabriele Nolè , Antonio Lanorte , Valentina Santarsiero , Giuseppe Cillis , Francesco Scorza or Beniamino Murgante .

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Tucci, B. et al. (2021). Assessment and Monitoring of Soil Erosion Risk and Land Degradation in Arable Land Combining Remote Sensing Methodologies and RUSLE Factors. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12954. Springer, Cham. https://doi.org/10.1007/978-3-030-86979-3_50

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  • DOI: https://doi.org/10.1007/978-3-030-86979-3_50

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