GIS and Remote Sensing Technologies for the Assessment of Soil Erosion Hazard in the Mediterranean Island Landscapes

Filippo Catani, Minja Kukavicic, Caterina Paoli

Abstract


The islands of the Mediterranean Sea are widely subjected to desertification problems due to the concurrent impact of deforestation and climate change leading to soil losses. The Cyclades islands represent a typical example of such a situation and in particular the island of Naxos is a very suitable prototype site for studying the evolution, the characteristics and the possible methods to mitigate soil erosion and soil loss risks. Here we develop an RS and GIS-based method to evaluate a multi-temporal model for soil loss prediction and management in Naxos. The model, a modified distributed version of the USLE equation, is based on a set of variables depending on land cover, soil characteristics, hydrology and morphometry. Remote sensing techniques and field surveys and measurements, applied to different periods of time from 1987 to 2006, have been used to produce GIS based soil, land cover, topographic and geological maps. Such data has been used to assess the soil loss potential through the distributed cell-based application of the modified USLE equation using GIS tools. The results show that there has been a notable increase in soil losses from 1987 to recent times and that future scenario forecast a possible complete loss of soil in the Naxos Island in the next century, unless countermeasures are taken. We demonstrate that soil conservation practices have degraded in the last 30 years mainly due to the widespread change of land use and to the progressive abandon of agriculture from rural communities that have shifted their main activity towards tourism development and exploitation. Possible countermeasures are represented by the restoration of terracing systems throughout the island and by the construction of micro-dams acting as sediment repository and water storage system within steep sloping channels.


Keywords


Soil Erosion; Naxos Island; USLE; Landsat; ASTER; Soil Depth

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*2016 Journal Impact Factor was established by dividing the number of articles published in 2014 and 2015 with the number of times they are cited in 2016 based on Google Scholar, Google Search and the Microsoft Academic Search. If ‘A’ is the total number of articles published in 2014 and 2015, and ‘B’ is the number of times these articles were cited in indexed publications during 2016 then, journal impact factor = A/B. To know More: (http://en.wikipedia.org/wiki/Impact_factor)