Soil degradation phenomena are induced by both natural (soil characteristics, climate conditions) and anthropogenic (overgrazing, deforestation, improper agricultural practices) factors. Among the man-induced factors, the intensive agriculture is one of the widest diffused causes of soil deterioration. Particularly, persistent passes of operative machineries produce a dangerous alteration of soil chemical-physical properties. In the framework of Interreg IIIB MILDMAP-MEDIA project, we developed a new index based on the integration of land cover classifications and slope for assessing the level of mechanization that combined with information on soil types allows for estimating the soil vulnerability to compaction. Two Landsat-TM images were classified with a hybrid unsupervised/supervised approach to obtain land cover maps. On the basis of cultivation type and slope values, derived from a DEM, we associated the required number of machinery passes and evaluated the different use between tyred and tracked vehicles. Results obtained form the comparison of the implemented index with other commonly used indices enhanced its capability to provide a more detailed classification of vulnerability to soil compaction representing precious information for land degradation assessment.
A new index for the evaluation of land management in the framework of land degradation assessment
Imbrenda V;Simoniello T;Lanfredi M;
2009
Abstract
Soil degradation phenomena are induced by both natural (soil characteristics, climate conditions) and anthropogenic (overgrazing, deforestation, improper agricultural practices) factors. Among the man-induced factors, the intensive agriculture is one of the widest diffused causes of soil deterioration. Particularly, persistent passes of operative machineries produce a dangerous alteration of soil chemical-physical properties. In the framework of Interreg IIIB MILDMAP-MEDIA project, we developed a new index based on the integration of land cover classifications and slope for assessing the level of mechanization that combined with information on soil types allows for estimating the soil vulnerability to compaction. Two Landsat-TM images were classified with a hybrid unsupervised/supervised approach to obtain land cover maps. On the basis of cultivation type and slope values, derived from a DEM, we associated the required number of machinery passes and evaluated the different use between tyred and tracked vehicles. Results obtained form the comparison of the implemented index with other commonly used indices enhanced its capability to provide a more detailed classification of vulnerability to soil compaction representing precious information for land degradation assessment.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.