The alleviation of landslide impacts is a priority since they have the potential to cause significant economic damage as well as the loss of human life. Mitigation can be achieved effectively by using warning systems and preventive measures. The development of improved methodologies for the analysis and understanding of landslides is at the forefront of this scientific field. Identifying effective monitoring techniques (accurate, fast, and low cost) is the pursued objective. Geographic Information Systems (GISs) and remote sensing techniques are utilized in order to achieve this goal. In this study, four methodological approaches (manual landslide delineation, a segmentation process, and two mapping models, specifically object-based image analysis and pixel-based image analysis (OBIA and PBIA)) were proposed and tested with the use of Unmanned Aerial Vehicles (UAVs) and data analysis methods to showcase the state and evolution of landslides. The digital surface model (DSM)-based classification approach was also used to support the aforementioned approaches. This study focused on streamside landslides at research sites in three different countries: Greece, Romania, and Turkey. The results highlight that the areas of the OBIA-based classifications were the most similar (98%) to our control (manual) classifications for all three sites. The landslides’ perimeters at the Lefkothea and Chirlesti sites showed similar results to the OBIA-based classification (93%), as opposed to the Sirtoba site, where the perimeters of the landslides from OBIA-based classification were not well corroborated by the perimeters in the manual classification. Deposition areas that extend beyond the trees were revealed by the DSM-based classification. The results are encouraging because the methodology can be used to monitor landslide evolution with accuracy and high performance in different regions. Specifically, terrains that are difficult to access can be surveyed by UAVs because of their ability to take aerial images. The obtained results provide a framework for the unitary analysis of landslides using modern techniques and tools.

Factors influencing streambank erosion at the field/reach scale include both watershed and riparian land-uses, stream hydrology and channel morphology at the catchment scale. This study assesses the relationship of riparian land-uses, stream morphologic characteristics and catchment scale variables to streambank erosion within grazed riparian pastures in the Southern Iowa Drift Plain. Thirteen cooperating beef cow–calf farms and their catchments ranging from 2.5 to 12.9 km² in the Rathbun Lake watershed in South Central Iowa (USA) were chosen to conduct this study. Results suggest that the integration of stream morphologic characteristics and riparian land-uses at both the reach and catchment scale are necessary to explain the current level of streambank erosion measured at the reach scale. Larger catchment size or catchments with more total channel length were found to experience more bank erosion at the reach scale. A significant positive relationship between percent sand-and-silt in the bank soil and bank erosion rates implies that bank soils with less cohesiveness are more erodible. Catchment-scale assessments of the thirteen watersheds showed that within the 50 m corridor on both sides of the stream, 46 to 61% of riparian area was devoted to agricultural use and only 6 to 11% was in ungrazed perennial vegetation, much of it enrolled in the USDA Conservation Reserve Program. Overall, this and previous Rathbun watershed studies have shown that intensive agricultural use of riparian areas over such extents of time and scale could be directly (in field scale) and/or indirectly (watershed scale) related to excessive amounts of streambank erosion (ranging from 8.6 to 38.3 cm/yr) to receiving streams and lakes leading to their impairment and reduction in ecological services. Exclusion of cattle grazing in the riparian areas along buffered stream lengths (2.1% of the total watershed area) of the Rathbun watershed would reduce this impact. This approach could also be applicable to other similar watersheds with extensive land-use under grazed management.

Floods often cause changes in the hydro-geomorphology of riverbeds and banks. These changes need to be closely monitored to find a balance and exchange between lateral and vertical erosion and deposition, upstream local sediment supply, and a stream’s transport capacity. Low-frequency cross-sectional field surveys cannot map hard-to-reach locations. Innovative techniques, such as small unmanned aerial vehicles (UAVs), must be employed to monitor these processes. This research compared historical data with a UAV survey and the Pix4DMapper structure-from-motion (SfM) program to assess the longitudinal, lateral, and vertical changes of Sidere Creek in the eastern Black Sea, Türkiye. Digitization was undertaken using 2011–2015–2017 Google Earth photographs, 1960s topographic maps, and 2023 orthomosaics. ArcGIS 10.6 was used to delineate the centerlines (thalweg), left/right banks, alluvial bars, active channel widths, and channel confinement layers. Channel Migration Toolbox and CloudCompare were utilized for analyzing lateral and vertical morphological changes, respectively. The active channel migrated 25.57 m during 1960–2011, 15.84 m during 2011–2015, 6.96 m during 2015–2017, and 5.79 m during 2017–2023. Left-bank channel confinement rose from 2.4% to 42% and right-bank channel confinement from 5.9% to 34.8% over 63 years. Neither stream meandering nor sinuosity index changed statistically. Active channel boundary widths varied from 149.79 m to 9.46 m, averaging 37.3 m. It can be concluded that UAV surveys can precisely measure and monitor the stream channel longitudinal, lateral, and vertical morphological changes at a lower cost and in less time than previous methods.