Data di Pubblicazione:
2018
Citazione:
TECNICHE DI CARTOGRAFIA DIGITALE PER LA REDAZIONE DI MAPPE DI DETTAGLIO DEL SUOLO / M. Musetti ; tutor: L. Trombino ; co-tutore: R. Comolli ; coordinatore: E. Erba. Università degli Studi di Milano, 2018 Feb 08. 29. ciclo, Anno Accademico 2016. [10.13130/musetti-marco_phd2018-02-08].
Abstract:
The goal of this work was to produce high-quality thematic maps for an Apennine area, using digital soil mapping (DSM) techniques; various statistical methods were applied starting from 30 geomorphometric variables, obtained from the digital elevation model (DEM) with 10-m pixel. The aim was to: i) obtain cartographic products, with a low cost both in terms of time and money; and ii) verify their reliability.
The study area, consisting of two adjacent valleys (Oltrepo Pavese, PV), included Val di Nizza (27 km2), Val Ardivestra (47 km2) and the "plaque" of Pizzocorno-Pietragavina (17 km2). With regard to soil data acquisition, two different soil surveys were carried out, one of which was planned to obtain a minimum representative sample of soil variability of the area. A total of 132 georeferenced soil profiles were opened and described, and 468 soil samples were collected and analyzed for the main chemical and physical soil properties.
The thesis work was composed by 7 chapters. The first chapter (Study site) provided the study area description, focusing on main factors which affect pedogenetic processes, such as climate, vegetation, geomorphology and geology. Among these factors, geological characterization was carefully described due to its strong relationship with soil. Previous soil data and land use history were also considered and described.
The second and the third chapters were relative to digital soil mapping and geomorfometric variables respectively.
In the Digital Soil Mapping chapter the theoretical and practical aspects, needed for obtaining soil thematic maps using DSM techniques, were reported. The DSM methodology, its related problems and the different approaches used to represent the pedogenetic processes, were addressed. The two approaches adopted in this work (soil-landscape paradigm and geomorphometric assessment of topography) were described in detail.
The third chapter (Geomorphometric variables) included the preparatory study for soil mapping. In this section the geomorphometric variables were calculated; various inference methods were tested, with different combinations of variables calculated with open source and/or proprietary software. Before statistical elaborations the characteristics of the geomorphometric variables used as predictors were studied: in particular, the trend was analyzed, as well as reciprocal correlations and collinearity. Particular interest has been directed to the outliers, considering the influence they can have on calculations. From the analyzes carried out emerged that the outliers are connected to the calculation of the variables themselves and there is some degree of correlation, which is not said to correspond to collinearity. This redundancy of statistical information, however, corresponds to a different interpretation of the physical morphology of the land, which can be considered an additional information value to be used in statistical elaborations.
The fourth chapter (Soil Sampling Design) provided a guidance for soil sampling strategy. The aim was to reduce time and costs by providing a map of the representative sampling areas. The selected approach was simple from both conceptual and computational point of view. It was based on the soil-landscape paradigm and on landform segmentation. Firstly, a principal component analysis (PCA) was carried out on the overall set of geomorphometric variables; then on the base of PCA results, eight variables were selected and used as input variables of a neural network (Self-Organizing Feature Maps), resulting in the identification of eight different geomorphometric units.
In order to increase the pedological detail, the map was cross-checked with the geological map obtaining a total of 25 land units. To assess t
Tipologia IRIS:
Tesi di dottorato
Keywords:
DIGITAL SOIL MAPPING
Elenco autori:
M. Musetti
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