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.

According to the official statistics the areas of abandoned agricultural land in Lithuania are gradually decreasing, but very slightly. The aim of this study is to research spatial determination and abandoned land classification in the territory of Vilnius District Municipality. Vilnius District Municipality was chosen for the research because it, although located near the capital of the country and has a high population density, it is still the district having the largest percent of abandoned land plots. A fast, cost-effective and sufficiently accurate method for determination of abandoned land plots would allow to constantly monitoring, to fix changes and foresee the abandoned land plots reduction possibilities. In the study there was used the multispectral RGB and NIR colour Sentinel-2 satellite images, the layer of the administrative boundary of Vilnius County and layer of abandoned agriculture land, which is available in Lithuanian Spatial Information Portal (www.geoportal.lt). The data was processed by Geographic Information System (GIS) techniques using classical classification Region Growing Algorithm. The research shows that NIR image classification result is more reliable than the result from RGB images.