Search Results (30)

Extreme rainfall events often trigger landslides, debris flows, and sediment-laden floods that cause severe damage in built-up areas, yet sediment deposition is rarely quantified in hazard assessments. This study evaluates the capability of the physically based catchment model LISEMHazard to reconstruct sediment generation, transport, and deposition during Hurricane Maria (2017) in two catchments in Dominica (Coulibistrie and Grand Bay). Simulations were performed at 10 m resolution using rainfall, topography, soil, and land-use data. Model calibration and validation used mapped landslides and debris flows, field measurements of deposition height, and DEMs of Difference (DoDs). LISEMHazard reproduced the general magnitude of sediment volumes and the frequency–area distribution of medium and large landslides but showed poor ability to predict their exact locations and overestimated landslide depth and deposition height. Agreement between modeled and observed debris-flow patterns was good in major channels but weak in minor ones. Sensitivity analysis indicated that soil depth and cohesion dominate uncertainties, whereas saturated hydraulic conductivity and surface roughness exert minimal influence. Despite substantial data and model limitations, physically based modeling remains a practical approach for spatial estimation of sediment deposition needed for risk assessment, structural damage evaluation, and cleanup cost estimation. Full article

Integrated Coastal Zone Management (ICZM) requires multi-scalar, high-resolution monitoring data to effectively address climate change impacts, particularly sea-level rise and accelerated erosion. This study presents an innovative Remote Sensing (RS) and Geoinformatics approach to precisely quantify and contextualize the exposure of sandy beaches. The research focuses on the highly dynamic insular tidal inlet margin of the Pontal Sul da Ilha de Itamaracá, located within a tropical estuarine system in Northeast Brazil that is subject to intense anthropogenic pressure. The methodology of this study integrates high-resolution GNSS-PPK surveys from two seasonal cycles (2017–2018) with a Difference of DEMs (DoD) analysis to precisely quantify seasonal sediment transport. Furthermore, a multi-temporal analysis leverages the Fort Orange Archaeological Site as a stable datum, combining colonial-era maps with modern satellite imagery to trace shoreline evolution. During the 2017–2018 period, maximum erosion (up to ~2.60 m in altimetric losses) affected the southern and central-northern shoreline, while accretion (up to ~2.25 m in altimetric gains) occurred between these erosional sectors and in the northeastern offshore area. This multi-scalar approach provides the robust data necessary for ICZM, effectively prioritizing sustainable, nature-based strategies that align with local administrative capacities. Full article

The effect of rock cover on rainfall impact and hydrodynamic flow behavior is a topic that needs to be further explored. In this paper, the effects of rock fragments embedded (trapped in the topsoil layer) in clay soil on runoff and sediment yield under simulated rainfall are investigated. The experiments were performed on 0.25 m × 0.25 m sloping microplots with bare soil (control) or a surface covered by 35 embedded rock elements (rock). For each configuration, three rainfall intensities (260.2, 444.0, and 605.2 mm h⁻¹), obtained by Kamphorst’s simulator, were tested, and the whole suspension was collected to determine runoff and sediment yield. The microplots were surveyed before and after the runs to obtain a Digital Elevation Model (DEM) and a DEM of Difference (DoD) and determine sediment yield. The obtained results demonstrated that both runoff and sediment yield (both measured from bowls and calculated from the DoD) increase with increasing rainfall intensity and rock percentage cover. For embedded elements, a higher rate of the sediments moving along the microplots reaches the downstream end of the microplot due to flow channelization. Finally, for the control condition, the erosive phenomena are concentrated under the nozzles, while for the rock configuration, they are also spread in the areas among the rock elements. Full article

This study reconstructs seven decades (1949–2019) of morphodynamic changes and sediment dynamics in the Diable River (Québec, Canada) using nine series of aerial photographs, a high-resolution LiDAR Digital Elevation Model (2021), and grain-size analysis. The objectives were to document long-term river evolution, quantify erosion and deposition, and evaluate sediment connectivity between eroding sandy bluffs and depositional zones. Planform analysis and sediment budgets derived from DEMs of Difference (DoD) reveal an oscillatory trajectory characterized by alternating phases of sediment export and temporary stabilization, rather than a simple trend of degradation or aggradation. The most dynamic interval (1980–2001) was marked by widespread meander migration and the largest net export (−142.5 m³/km/year), whereas the 2001–2007 interval showed net storage (+70.8 m³/km/year) and short-term geomorphic recovery. More recent floods (2017, 2019; 20–50-year return periods) induced localized but persistent sediment loss, underlining the structuring role of extreme events. Grain-size results indicate partial connectivity: coarse fractions tend to remain in local depositional features, while finer sediments are preferentially exported downstream. These findings emphasize the geomorphic value of temporary sediment sinks (bars, beaches) and highlight the need for adaptive river management strategies that integrate sediment budgets and local knowledge into floodplain governance. Full article

The rapid expansion of ski tourism and climate change-induced snow shortages have led to intensified ski run maintenance, including extensive earthworks, artificial snowmaking, and regular snow grooming. While these activities are known to cause significant land degradation, quantitative geomorphological studies, specifically on the effects of snow grooming, are limited. This study addresses this knowledge gap by quantitatively assessing the impact of snow grooming on erosion processes and hillslope morphology by comparing them with natural landforms. We achieved this by determining the spatial distribution, morphometry, and long-term persistence of studied landforms. The study area consisted of a unique ski resort at Kasprowy Wierch, which does not use artificial snowmaking or extensive earthworks. We combined detailed field mapping with the analysis of multi-temporal Digital Elevation Models (DEMs) and orthophotos from 2012, 2019, 2020, and 2023. Our methodology also included the calculation of volumetric changes using the DEM of Difference (DoD) analysis. We distinguished two groups of eroded areas, natural landforms (e.g., shallow landslides, debris flow tracks, nivation niches) and snow groomer-induced forms, which were concentrated on ski runs. Natural landforms were elongated and deeper, with higher edges, clustered along debris flow tracks, and occurred on steeper slopes (mean 26.8°). They were more persistent and extensive, with a total area ranging from 3891 m² in 2012 to 3452 m² in 2023. In contrast, groomer-eroded landforms, located on gentler slopes (mean 23.4°), were smaller, more angular, less persistent, and concentrated on narrower, intensively used ski run sections. Their total area decreased from 2122.71 m² to 1762.25 m² over the same period, despite an increase in their count. The volumetric analysis revealed distinct dynamics: over the long term (2012–2023), natural forms showed a total deposition of +8.196 m³, while groomer-eroded forms experienced total erosion of −2.070 m³. During an extreme rainfall event in 2020, natural landforms experienced vast erosion of −163.651 m³, nearly five times greater than the −33.765 m³ observed on snow groomer-eroded landforms, demonstrating their greater susceptibility to high-magnitude events. Importantly, a comparison with other studies reveals that the scale of erosion from snow grooming is relatively small compared to the severe impacts of artificial snowmaking. Our findings are relevant for managing protected areas, such as Tatra National Park, where the focus should be on mitigating anthropogenic impacts to preserve natural processes, which in turn implies that the development of new ski infrastructure should be prohibited. Full article

UAV platforms equipped with RTK positioning and LiDAR sensors are increasingly used for landslide monitoring, offering frequent, high-resolution surveys with broad spatial coverage. In this study, we applied high-frequency UAV-based monitoring to the active Baldiola earthflow (Northern Apennines, Italy), integrating 10 UAV–LiDAR and photogrammetric surveys, acquired at average intervals of 14 days over a four-month period. UAV-derived orthophotos and DEMs supported displacement analysis through homologous point tracking (HPT), with robotic total station measurements serving as ground-truth data for validation. DEMs were also used for multi-temporal DEM of Difference (DoD) analysis to assess elevation changes and identify depletion and accumulation patterns. Displacement trends derived from HPT showed strong agreement with RTS data in both horizontal (R² = 0.98) and vertical (R² = 0.94) components, with cumulative displacements ranging from 2 m to over 40 m between April and August 2024. DoD analysis further supported the interpretation of slope processes, revealing sector-specific reactivations and material redistribution. UAV-based monitoring provided accurate displacement measurements, operational flexibility, and spatially complete datasets, supporting its use as a reliable and scalable tool for landslide analysis. The results support its potential as a stand-alone solution for both monitoring and emergency response applications. Full article

This article examines the combined use of UAV (Unmanned Aerial Vehicle) photogrammetry and TLS (Terrestrial Laser Scanning) to detect changes in coastal cliffs in the Strunjan Nature Reserve. Coastal cliffs present unique surveying challenges, including limited access, unstable reference points due to erosion, GNSS (Global Navigation Satellite System) signal obstruction, dense vegetation, private property restrictions and weak mobile data. To overcome these limitations, UAV and TLS techniques are used with the help of GNSS and TPS (Total Positioning Station) surveying to establish a network of GCPs (Ground Control Points) for georeferencing. The methodology includes several epochs of data collection between 2019 and 2024, using a DJI Phantom 4 RTK for UAV surveys and a Riegl VZ-400 scanner for TLS. The data processing includes point cloud filtering, mesh comparison and a DoD (DEM of difference) analysis to quantify cliff surface changes. This study addresses the effects of vegetation by focusing on vegetation-free regions of interest distributed across the cliff face. The results aim to demonstrate the effectiveness and limitations of both methods for detecting and monitoring cliff erosion and provide valuable insights for coastal management and risk assessment. Full article

UAV-based topographic change detection is widely used in geoscience communities. The change detection involves comparison of two digital elevation models (DEMs) produced by UAV surveys, which are affected by the DEM resolution. Coarse resolution DEMs introduce errors in change detection, but the DEM resolution effect remains poorly understood. Moreover, effective strategies for mitigating the resolution effect have yet to be investigated. This study generated UAV-based DEMs at resolutions ranging from 0.1 m to 10 m with various resampling methods. The impact of DEM resolution on topographic change detection was then evaluated by analyzing the difference of DEM (DoD) and volume budget errors with indices such as mean error (ME), standard deviation (STD), and Moran’s I. The results from two human-altered landscapes showed that the random errors of DoD increase rapidly with the DEM resolution coarsening, while DoD systematic errors (spatial distribution of errors) become stable after 4 m resolution. The volume budget errors also increase with DEM coarsening. Coarser resolution DEMs tend to underestimate the volume budget (gross erosion, gross deposition, and net changes). Moreover, selecting an appropriate method for generating DEM is beneficial in decreasing the errors caused by the resolution effect. Among the seven methods (MAX, MIN, MEAN, BIL, NEAR, NEB, and TIN), the BIL method is optimum for mitigating both DoD and volume errors. The NEAR, NEB, and TIN methods are equivalent, and they are superior to the aggregation methods (MAX, MIN, MEAN). The slope of DoD (SDoD) should be considered when selecting a resolution for change detection. Large errors tend to appear in areas with large SDoD and vice versa. Coarse resolution DEMs are tolerable in areas with low SDoD, while high resolution DEMs are necessary in areas with large SDoD. Full article

The monitoring of beach topographical changes and recovery processes under typhoon storm influence has primarily relied on traditional techniques that lack high spatial resolution. Therefore, we used an unmanned aerial vehicle light detection and ranging (UAV LiDAR) system to obtain the four time periods of topographic data from Tantou Beach, a sandy beach in Xiangshan County, Zhejiang Province, China, to explore beach topography and geomorphology in response to typhoon events. The UAV LiDAR data in four survey periods showed an overall vertical accuracy of approximately 5 cm. Based on the evaluated four time periods of the UAV LiDAR data, we created four corresponding DEMs for the beach. We calculated the DEM of difference (Dod), which showed that the erosion and siltation on Tantou Beach over different temporal scales had a significant alongshore zonal feature with a broad change range. The tidal level significantly impacted beach erosion and siltation changes. However, the storm surge did not affect the beach area above the spring high-tide level. After storms, siltation occurred above the spring high-tide zone. This study reveals the advantage of UAV LiDAR in monitoring beach changes and provides novel insights into the impacts of typhoon storms on coastal topographic and geomorphological change and recovery processes. Full article

The integration of multiple data sources, including satellite imagery, aerial photography, and ground-based measurements, represents an important development in the study of landslide processes. The combination of different data sources can be very important in improving our understanding of geological phenomena, especially in cases of inaccessible areas. In this context, the study of coastal areas represents a real challenge for the research community, both for the inaccessibility of coastal slopes and for the numerous drivers that can control coastal processes (subaerial, marine, or endogenic). In this work, we present a case study of the Conero Regional Park (Northern Adriatic Sea, Ancona, Italy) cliff-top retreat, characterized by Neogenic soft rocks (flysch, molasse). In particular, the study is focused in the area between the beach of Portonovo and Trave (south of Ancona), which has been studied using aerial orthophoto acquired between 1978 and 2021, Unmanned Aerial Vehicle (UAV) photographs (and extracted photogrammetric model) surveyed in September 2021 and 2012 LiDAR data. Aerial orthophotos were analyzed through the United States Geological Survey’s (USGS) tool Digital Shoreline Analysis System (DSAS) to identify and estimate the top-cliff erosion. The results were supported by the analysis of wave data and rainfall from the correspondent period. It has been found that for the northernmost sector (Trave), in the examined period of 40 years, an erosion up to 40 m occurred. Furthermore, a Digital Elevation Model (DEM) of Difference (DoD) between a 2012 Digital Terrain Model (DTM) and a UAV Digital Surface Model (DSM) was implemented to corroborate the DSAS results, revealing a good agreement between the retreat areas, identified by DSAS, and the section of coast characterized by a high value of DoD. Full article

This case study focuses on the area of El Plateado near the city of Loja, Ecuador, where landslides with a high impact on infrastructures require monitoring and control. The main objectives of this work are the characterization of the landslide and the monitoring of its kinematics. Four flights were conducted using a remotely piloted aerial vehicle (RPAS) to capture aerial images that were processed with SfM techniques to generate digital elevation models (DEMs) and orthoimages of high resolution (0.05 m) and sufficient accuracy (below 0.05 m) for subsequent analyses. Thus, the DEM of differences (DoD) and profiles are obtained, but a morphometric analysis is conducted to quantitatively characterize the landslide’s elements and study its evolution. Parameters such as slope, aspect, topographic position index (TPI), terrain roughness index (TRI), and topographic wetness index (TWI) are analyzed. The results show a higher slope and roughness for scarps compared to stable areas and other elements. From TPI, slope break lines have been extracted, which allow the identification of landslide features such as scarps and toe tip. The landslide shows important changes in the landslide body surface, the retraction of the main scarp, and advances of the foot. A general decrease in average slope and TRI and an increase in TWI are also observed due to the landslide evolution and stabilization. The presence of fissures and the infiltration of rainfall water in the unsaturated soil layers, which consist of high-plasticity clays and silts, contribute to the instability. Thus, the study provides insights into the measurement accuracy, identification and characterization of landslide elements, morphometric analysis, landslide evolution, and the relationship with geotechnical factors that contribute to a better understanding of landslides. A higher frequency of the RPAS surveys and quality of geotechnical and meteorological data are required to improve the instability analysis together with a major automation of the GIS procedures. Full article

Since the end of the Little Ice Age (LIA, ~1830), the accelerated glaciers’ shrinkage along mid-latitude high mountain areas promoted a quick readjustment of geomorphological processes with the onset of the paraglacial dynamic, making proglacial areas among the most sensitive Earth’s landscapes to ongoing climate change. A potentially useful remote-sensing method for investigating such dynamic areas is the DEM (Digital Elevation Model) of Difference (DoD) technique, which quantifies volumetric changes in a territory between successive topographic surveys. After a detailed geomorphological analysis and comparison with historical maps of the Martello Valley (central Italian Alps), we applied the DoD for reconstructing post-LIA deglaciation dynamics and reported on the surface effects of freshly-onset paraglacial processes. The head of the valley is still glacierized, with three main ice bodies resulting from the huge reduction of a single glacier present at the apogee of the LIA. Aftermath: the glaciers lose 60% of their initial surface area, largely modifying local landforms and expanding the surface of the proglacial areas. The DoD analysis of the 2006–2015 timeframe (based on registered DEM derived from LiDAR—Light Detection and Ranging—data) highlights deep surface elevation changes ranging from +38 ± 4.01 m along the foot of rock walls, where gravitative processes increased their intensity, to −47 ± 4.01 m where the melting of buried ice caused collapses of the proglacial surface. This approach permits estimating the volume of sediments mobilized and reworked by paraglacial processes. Here, in less than 10 years, −23,675 ± 1165 m³ of sediment were removed along the proglacial area and transported down valley, highlighting the dynamicity of proglacial areas. Full article

South Manitou Island, part of Sleeping Bear Dunes National Lakeshore in northern Lake Michigan, is a post-glacial lacustrine landscape with substantial geomorphic changes including landslides, shoreline and bluff retreat, and sand dune movement. These changes involve interrelated processes, and are influenced to different extents by lake level, climate change, and land use patterns, among other factors. The utility of DEM of Difference (DoD) and other terrain analyses were investigated as a means of understanding interrelated geomorphologic changes and processes across multiple decades and at multiple scales. A 1m DEM was developed from 1955 historical aerial imagery using Structure from Motion Multi-View Stereo (SfM-MVS) and compared to a 2016 lidar-based DEM to quantify change. Landslides, shoreline erosion, bluff retreat, and sand dune movement were investigated throughout South Manitou Island. While the DoD indicates net loss or gain, interpretation of change must take into consideration the SfM-MVS source of the historical DEM. In the case of landslides, where additional understanding may be gleaned through review of the timing of lake high- and lowstands together with DoD values. Landscape-scale findings quantified cumulative feedbacks between interrelated processes. These findings could be upscaled to assess changes across the entire park, informing future change investigations and land management decisions. Full article

A four-day glacier-melt flood (13–16 August 2013) caused abrupt geomorphic changes in the proglacial gravel-bed Scott River, which drains the small (10 km²) Scott Glacier catchment (SW Svalbard). This type of flood occurs on Svalbard increasingly during periods of abnormally warm or rainy weather in summer or early autumn, and the probability of occurrence grows in direct proportion to the increase in temperature and/or precipitation intensity. In the summer of 2013, during the measurement season, the highest daily precipitation (17 mm) occurred on 13 August. During the following four days, it constituted in total 47 mm, i.e., 50% of the precipitation total for the measurement period of 2013. The largest flood in 20 years was caused by high precipitation with a synchronous rise in temperature from about 1.0 to 8.6 °C. These values exceeded multi-year averages (32 mm and 5.0 °C, respectively) at an average discharge of 0.9 m³/s (melt season mean 1986–2011). These conditions caused a rapid and abrupt response of the river with the dominant (90%) glacier-fed. The increase in discharge to 4.6 m³/s, initiated by the glacial flood, mobilized significant amounts of sediment in the river bed and channel. Geomorphic changes within the alluvial fan as an area of 58,940 m², located at the mouth of the Scott River, were detected by multi-sites terrestrial laser scanning using a Leica Scan Station C10 and then estimated using Geomorphic Change Detection (GCD) software. The changes found involved 39% of the alluvial fan area (23,231 m²). The flood-induced total area of lowering (erosion) covered 26% of the alluvial fan (6035 m²), resulting in the removal of 1183 ± 121 m³ of sediment volume. During the final phase of the flood, two times more sediment (1919 ± 344 m³) was re-deposited within the alluvial fan surface, causing significant aggradation on 74% of its area (17,196 m²). These geomorphic changes resulted in an average lowering (erosion) of the alluvial fan surface of 0.2 m and an average rising (deposition) of 0.1 m. Full article

Long-term and high-intensity coal mining has led to the increasingly serious surface subsidence and environmental problems. Surface subsidence monitoring plays an important role in protecting the ecological environment of the mining area and the sustainable development of modern coal mines. The development of surveying technology has promoted the acquisition of high-resolution terrain data. The combination of an unmanned aerial vehicle (UAV) point cloud and the structure from motion (SfM) method has shown the potential of collecting multi-temporal high-resolution terrain data in complex or inaccessible environments. The difference of the DEM (DoD) is the main method to obtain the surface subsidence in mining areas. However, the obtained digital elevation model (DEM) needs to interpolate the point cloud into the grid, and this process may introduce errors in complex natural topographic environments. Therefore, a complete three-dimensional change analysis is required to quantify the surface change in complex natural terrain. In this study, we propose a quantitative analysis method of ground subsidence based on three-dimensional point cloud. Firstly, the Monte Carlo simulation statistical analysis was adopted to indirectly evaluate the performance of direct georeferencing photogrammetric products. After that, the operation of co-registration was carried out to register the multi-temporal UAV dense matching point cloud. Finally, the model-to-model cloud comparison (M3C2) algorithm was used to quantify the surface change and reveal the spatio-temporal characteristics of surface subsidence. In order to evaluate the proposed method, four periods of multi-temporal UAV photogrammetric data and a period of airborne LiDAR point cloud data were collected in the Yangquan mining area, China, from 2020 to 2022. The 3D precision map of a sparse point cloud generated by Monte Carlo simulation shows that the average precision in X, Y and Z directions is 44.80 mm, 45.22 and 63.60 mm, respectively. The standard deviation range of the M3C2 distance calculated by multi-temporal data in the stable area is 0.13–0.19, indicating the consistency of multi-temporal photogrammetric data of UAV. Compared with DoD, the dynamic moving basin obtained by the M3C2 algorithm based on the 3D point cloud obtained more real surface deformation distribution. This method has high potential in monitoring terrain change in remote areas, and can provide a reference for monitoring similar objects such as landslides. Full article