The main objective of this study is to review and evaluate three common interpolation methods namely: Inverse Distance Weighting (IDW), Radial Basis Function (RBF) and Ordinary Kriging (OK), and generate maps of soil pH using these methods. The accuracy and efficiency of the generated maps have been examined as well as the most fitting technique for estimating spatial distribution of soil pH in the study area is identified. Studies were conducted within the limits of land use of RUP “Uchkhoz BGSHA” (Republic of Belarus, Mogilev region, Goretsky district). The total area of the surveyed territory is 3197.89 hectares. For the analysis data is used about pHKCl of soil solution obtained from materials of an agrochemical survey executed in 2014. Forecasting and visualization of the spatial distribution of pH sub(KCl) was carried out using the Geostatistical Analyst module of the ArcGIS software. The experimental anisotropic variograms were calculated to determine the possible spatial structure of soil pH. Based on cross-validation results, a polynomial function was identified as the best variogram model. The model created by the method of radial basis functions turned out to be the most suitable for forecasting purposes (the value of the root-mean-square error was 0.763). In terms of interpolation accuracy, the investigated deterministic and geostatistical methods are located in the next descending row: RBF greater than IDW greater than OK.

With recent advances in aerial data acquisition technologies from aircraft and Unmanned Aerial Vehicles (UAVs) very large datasets can be collected rapidly, covering significant surfaces with centimetre-scale resolution, with the consequence possibility to analyse geological structures of coastal areas within those datasets digitally. The monitoring of erosion mechanisms in fact requires high standards of precision to appreciate their effects. With the availability of a regular coastal monitoring programme being carried out in a large territory, UAVs can replace many of the conventional flights, with considerable advantages in the cost of data acquisition and without any loss in the quality of topographic and aerial imagery data. Several works in literature have been focused on finding an effective and sustainable survey strategy to limit costs and work times. However, it is necessary to refine the photogrammetric mapping process to optimize its geometrical accuracy and ensure the multi-temporal and multi-scaling repeatability of final products. The aim of this work is to test the accuracy obtainable from various photogrammetric workflows concerning the 3D modelling of a coastline area that is subject to hydrogeological instability. To this purpose, a set of image data acquired with a UAV, equipped with a non-metric camera and a low-accuracy GNSS/INS receiver, was processed. To maintain and test the accuracy of the whole process, an adequate number of Ground Control Points (GCPs) was acquired by means of a high precision GNSS surveying.