The aim of this study is to assess of the distribution and map the geomorphological effects of soil erosion at thebasin scale identifying newly-formed erosional landsurfaces (NeFELs), by means of an integration of Landsat ETM 7+ remotelysensed data and fi eld-surveyed geomorphological data. The study was performed on a 228·6 km2-wide area, located in southernItaly. The study area was fi rst characterized from a lithological, pedological, land-use and morpho-topographic point of view andthematic maps were created. Then, the georeferenced Landsat ETM 7+ satellite imagery was processed using the RSI ENVI 4.0software. The processing consisted of contrast stretching, principal component analysis (PCA), decorrelation stretching and RGBfalse colour compositing. A fi eld survey was conducted to characterize the features detected on the imagery. Particular attentionwas given to the NeFELs, which were located using a global positioning system (GPS). We then delimited the Regions of Interest(ROI) on the Landsat ETM 7+ imagery, i.e. polygons representing the ‘ground-truth’, discriminating the NeFELs from the otherfeatures occurring in the imagery. A simple statistical analysis was conducted on the digital number (DN) values of the pixelsenclosed in the ROI of the NeFELs, with the aim to determine the spectral response pattern of such landsurfaces. The NeFELswere then classifi ed in the entire image using a maximum likelihood classifi cation algorithm. The results of the classifi cationprocess were checked in the fi eld. Finally, a spatial analysis was performed by converting the detected landsurfaces into vectorialformat and importing them into the ESRI ArcViewGIS 9.0 software.Application of these procedures, together with the results of the fi eld survey, highlighted that some ‘objects’ in the classifi edimagery, even if displaying the same spectral response of NeFELs, were not landsurfaces subject to intense soil erosion, thusconfi rming the strategic importance of the fi eld-checking for the automatically produced data. During the production of the mapof the NeFELs, which is the fi nal result of the study, these ‘objects’ were eliminated by means of simple, geomorphologicallycoherentintersection procedures in a geographic information system (GIS) environment. The overall surface of the NeFELs hadan area of 22·9 km2, which was 10% of the total. The spatial analysis showed that the highest frequency of the NeFELs occurredon both south-facing and southwest-facing slopes, cut on clayey-marly deposits, on which fi ne-textured and carbonate-richInceptisols were present and displaying slope angle values ranging from 12° to 20°. The comparison of two satellite imageries ofdifferent periods highlighted that the NeFELs were most clearly evident immediately after summer tillage operations and not soevident before them, suggesting that these practices could have played an important role in inducing the erosional processes.
Soil erosion assessment using Geomorphological Remote Sensing techniques: an example from southern Italy
MAGLIULO P.
2010-01-01
Abstract
The aim of this study is to assess of the distribution and map the geomorphological effects of soil erosion at thebasin scale identifying newly-formed erosional landsurfaces (NeFELs), by means of an integration of Landsat ETM 7+ remotelysensed data and fi eld-surveyed geomorphological data. The study was performed on a 228·6 km2-wide area, located in southernItaly. The study area was fi rst characterized from a lithological, pedological, land-use and morpho-topographic point of view andthematic maps were created. Then, the georeferenced Landsat ETM 7+ satellite imagery was processed using the RSI ENVI 4.0software. The processing consisted of contrast stretching, principal component analysis (PCA), decorrelation stretching and RGBfalse colour compositing. A fi eld survey was conducted to characterize the features detected on the imagery. Particular attentionwas given to the NeFELs, which were located using a global positioning system (GPS). We then delimited the Regions of Interest(ROI) on the Landsat ETM 7+ imagery, i.e. polygons representing the ‘ground-truth’, discriminating the NeFELs from the otherfeatures occurring in the imagery. A simple statistical analysis was conducted on the digital number (DN) values of the pixelsenclosed in the ROI of the NeFELs, with the aim to determine the spectral response pattern of such landsurfaces. The NeFELswere then classifi ed in the entire image using a maximum likelihood classifi cation algorithm. The results of the classifi cationprocess were checked in the fi eld. Finally, a spatial analysis was performed by converting the detected landsurfaces into vectorialformat and importing them into the ESRI ArcViewGIS 9.0 software.Application of these procedures, together with the results of the fi eld survey, highlighted that some ‘objects’ in the classifi edimagery, even if displaying the same spectral response of NeFELs, were not landsurfaces subject to intense soil erosion, thusconfi rming the strategic importance of the fi eld-checking for the automatically produced data. During the production of the mapof the NeFELs, which is the fi nal result of the study, these ‘objects’ were eliminated by means of simple, geomorphologicallycoherentintersection procedures in a geographic information system (GIS) environment. The overall surface of the NeFELs hadan area of 22·9 km2, which was 10% of the total. The spatial analysis showed that the highest frequency of the NeFELs occurredon both south-facing and southwest-facing slopes, cut on clayey-marly deposits, on which fi ne-textured and carbonate-richInceptisols were present and displaying slope angle values ranging from 12° to 20°. The comparison of two satellite imageries ofdifferent periods highlighted that the NeFELs were most clearly evident immediately after summer tillage operations and not soevident before them, suggesting that these practices could have played an important role in inducing the erosional processes.File | Dimensione | Formato | |
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