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Digital terrain models are key tools in land analysis and management as they are directly employable in GIS systems and other specific applications like hydraulic modelling, geotechnical analyses, road planning, telecommunication, and many others. TIN generation, from different kind of measurement techniques, is ruled by specific regulations. Interpolation techniques to compute a regular grid from a TIN, are, instead, still lacking in specific regulations: a unitary and shared methodology has not already been made compulsory in order to be used in cartographic production while generating digital models. Such ambiguity obviously involves non univocal results and can affect precision, which can lead to divergent analyses on the same territory. In the present study different algorithms will be analysed in order to spot an optimal interpolation methodology. The availability of the recent digital model produced by the Regione Piemonte with airborne LIDAR and the presence of sections of testing realized with higher resolutions and the presence of independent digital models on the same territory allow to set a series of analysis with consequent determination of the best methodologies of interpolation. The analysis of the residuals on the test sites allows to calculate the descriptive statistics of the computed values: all the algorithms have furnished interesting results; all the more interesting, notably for dense models, the IDW (Inverse Distance Weighing) algorithm results to give best results in this study case. Moreover, a comparative analysis was carried out by interpolating data at different input point density, with the purpose of highlighting thresholds in input density that may influence the quality reduction of the final output in the interpolation phase.

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Abstract:Mapping ecosystem services (ES) increases the awareness of natural capital value, leading to building sustainability into decision-making processes. Recently, many techniques to assess the value of ES delivered by different scenarios of land use/land cover (LULC) are available, thus becoming important practices in mapping to support the land use planning process. The spatial analysis of the biophysical ES distribution allows a better comprehension of the environmental and social implications of planning, especially when ES concerns the management of risk (e.g., erosion, pollution). This paper investigates the nutrient retention model of InVEST software through its spatial distribution and its quantitative value. The model was analyzed by testing its response to changes in input parameters: (1) the digital terrain elevation model (DEM); and (2) different LULC attribute configurations. The paper increases the level of attention to specific ES models that use water runoff as a proxy of nutrient delivery. It shows that the spatial distribution of biophysical values is highly influenced by many factors, among which the characteristics of the DEM and its interaction with LULC are included. The results seem to confirm that the biophysical value of ES is still affected by a high degree of uncertainty and encourage an expert field campaign as the only solution to use ES mapping for a regulative land use framework.

In the present study different algorithms, usually available in GIS environment, are analyzed in order to spot an optimal interpolation methodology and to define, by classification techniques, which morphological variable affects the interpolation quality. The investigated dataset is a helicopter-borne laser scanner survey carried out on a mountain slope. It has been interpolated at various resolutions, and a percentage of the entire set has been employed to evaluate the interpolation accuracy. The analysis has highlighted, among the tested interpolators, the Natural Neighbour as the best one. The classification has drawn the attention to the total curvature and slope as the main factors affecting interpolation accuracy. The next goal is the mapping of such classification results.