DEM Of Difference Research Articles

Characterization of displacement and internal structure of landslides from multitemporal UAV and ERT imaging

Preliminary knowledge of the surface movement and internal structure of a landslide is essential to improve the understanding of landslide behavior as an initial step to develop suitable mitigation measures. This paper characterizes displacement and internal structure of landslides using multitemporal unmanned aerial vehicles (UAV) and electrical resistivity tomography (ERT) imaging. Multitemporal orthophotos, digital elevation model (DEM) profile lines, DEMs of difference (DoD), and ERT images allowed us to measure the landslide morphometry and areal changes, detect the trend of surface displacement, calculate the surface movement rate and direction, characterize the spatial variability in surface movement rates, and relate spatial variation in displacement to the internal structure of the landslide. The Kalisari Landslide experienced retrogressive movement where the scarp of landslide moved backward 38 m from 2015 to 2019. The surface movement ranged from 0.7 to 8.1 m with the direction mostly to the northeast. The depletion and accumulation ranged from 0.1 to 5 m, with the most active change located northwest of the landslide. The variability in movement was influenced by the spatial variability in the subsurface material inferred from the ERT images, i.e., surface material, clay, weathered breccias (possibly altered), and breccias. The interpretation from multitemporal UAV and ERT images indicates that the Kalisari Landslide has a nonhomogeneous multiple retrogressive behavior with a curved slip surface located at the clay layer.

Integrated analysis of sediment source areas in an Alpine basin

In Alpine environment, studying the evolution of sediment mobility from hillslopes to lower landforms and channel network is a challenging task, mainly due to the complex interplay of erosion and colluvial processes, topographic features and climatic conditions. The combination of direct field surveys and digital terrain models can provide a good opportunity to accurately investigate the sediment delivery processes and improve the understanding of geomorphic sediment cascade. The main aim of this work is to analyze sediment dynamics in sediment source areas of an Alpine basin (Rio Cordon catchment, 5 km2), integrating techniques that are usually applied separately: sediment tracing with Passive Integrated Transponders (PITs) and DEM of Difference (DoD). Additionally, the relationship between rainfall characteristics and sediment source behavior was analyzed. Sediment transfer through source areas and the geomorphic evolution of those areas were analyzed by field investigations between October 2017 and September 2018. Specifically, eleven source areas with five different typologies were investigated by installing 268 tracers to analyze sediment mobility along hillslopes. The source areas and the tracers’ displacements monitoring was carried out after snowmelt (late May 2018) and periodically during Summer 2018 (July, August and September. To investigate the geomorphic changes in source areas, high-resolution DEMs (0.05 m cell) were derived with a Structure from Motion (SfM) technique in two different periods, after snowmelt in early June 2018 and in the following September; the collection of these data permitted computation of DoDs. To analyze the rainfall characteristics, five rain gauging stations were used. Rainfall analysis revealed that three different events exceeded the threshold of a two-year recurrence interval for different durations, which in turn were considered to be triggering events for each monitored period. The tracers exhibited an interesting mobility rate (37.7%) with different dynamics for source typologies, while geomorphic evolution computed with DoDs showed consistent changes mainly in debris-flow channels and debris-flow deposits. The rainfall intensity resulted as a variable controlling the sediment mobility through the source areas, while the integration of the two methodologies highlighted how mobilized tracers originate mainly from erosional surfaces. The research provides a detailed analysis of hillslope dynamics in the surveyed area, providing increased knowledge regarding the delivery processes that act on sediment sources and better interpretations of sediment mobility in Alpine environments.

Inferring sediment transfers and functional connectivity of rivers from repeat topographic surveys

AbstractHigh‐resolution topographic models have revolutionized monitoring of river changes by comparing sequential river topographic surveys (i.e. change detection). Nevertheless, much more may be obtained from this innovative quantification of changes. In this paper, we enhance the interpretation of geomorphic processes by presenting a new method for understanding of sources and sinks of sediment, river sediment transfers and functional sediment connectivity. Repeat digital elevation models (DEMs) obtained by photogrammetry were used to quantify topographic change after two floods by creating a DEM of difference (DoD) of a 6.5 km‐long reach of Rambla de la Viuda stream, an ephemeral gravel‐bed river in eastern Spain. The proposed method involved dividing the channel into 10 m‐long longitudinal strips that were used to systematically draw boundaries between the erosional and depositional areas of the DoD. The analysis objectively: (i) drew a series of erosional and depositional segments, from 120 to 1360 m in length; (ii) estimated ranges of source‐to‐storage sediment transport distances, 320–670 m in the upstream and middle reaches and up to 2030 m in the lower reach; and (iii) obtained values of functional connectivity (i.e. the ratio between the sediment exported (erosion) and retained (deposition), ranging from 103 to 10−3). The variability in these three parameters along the river was found to be related to the level of channel disturbance by in‐stream mining during the 1990s and 2000s. Additionally, this method indicates that the main process responsible for self‐adjustment of the present morphosedimentary conditions is intra‐reach erosion of banks and channel beds. Thus, this study proposes a new methodology to characterize morphological change, sediment transfer and connectivity that may serve as environmental indicators of the hydromorphological integrity of rivers with potential application to the European Water Framework Directive. © 2019 John Wiley & Sons, Ltd.

Mapping Retrogressive Thaw Slumps Using Single-Pass TanDEM-X Observations

Vast areas of the Arctic host ice-rich permafrost, which is becoming increasingly vulnerable to terrain-altering thermokarst in a warming climate. Among the most rapid and dramatic changes are retrogressive thaw slumps. These slumps evolve by a retreat of the slump headwall during the summer months, making them detectable by comparing digital elevation models over time using the volumetric change as an indicator. Here, we present and assess a method to detect and monitor thaw slumps using time series of elevation models applied on two contrasting study areas in Northern Canada. Our two-step method is tailored to single-pass InSAR observations from the TanDEM-X satellite pair, which have been acquired since 2011. For each acquisition, we derive a digital elevation model and uncertainty estimates. In the first step, we difference digital elevation models and detect the significant elevation changes using a blob-detection algorithm. In the second step, we classify the detections into those due to thaw slumps and other causes using a simple thresholding method (accuracy: 78%), a random forest classifier (87%), and a support vector machine (86%). When our method is applied to other areas, the classifiers should be trained with data from part of the study area or with data obtained from similar areas in terms of topography, vegetation, and thaw slump characteristics to achieve the best performance. The obtained locations of thaw slumps can be used as a starting point to extract important slump properties, such as the headwall height and the volumetric change, which are currently not available on regional scales.

Investigating morphodynamics on Little Ice Age lateral moraines in the Italian Alps using archival aerial photogrammetry and airborne LiDAR data

The rapid glacier recession in the European Alps exposes large amounts of unconsolidated sediment. Several processes are involved in the reworking of this sediment on steep lateral moraines, e.g. small slides on the upper slopes, sheet erosion by snow gliding, fluvial erosion and debris flows. To gain deeper insight into the dependence of the morphodynamics on lateral moraines on the time since deglaciation, we analysed erosion rates and geomorphological processes occurring at different distances from the present-day glacier termini. Moreover, we assessed the significance of parameters like slope gradient, altitude a.s.l. and the presence of dead ice for the morphodynamics. We used historical (1959) as well as contemporary (2016) aerial images and airborne laserscanning data (2006) to derive orthophotos, 3D point clouds (SfM) and Digital Elevation Models of Difference (DoD). These models cover the entire lateral moraine sections of two glaciers in South Tyrol, Italy, but detailed analysis was restricted to five test areas which deglaciated at different times. We were able to detect areas with decreasing geomorphological activity showing an erosion rate below 1 cm per year mainly on moraine sections remote from the contemporary glacier tongue. Simultaneously, moraine sections with continuous high levels of morphodynamics or even increasing activity were observed. The latter show heavy gullying on the upper slopes with erosion rates of 5.9–10.1 cm per year and no indications of decreasing rework rates could be found. We suppose a strong influence of degrading debris-covered dead ice, which all these slope experienced over many years after glacier melting. However, moisture availability and the slope angles, amongst others, also affect the geomorphological processes forming the moraine slopes. Thus, our results are only partly consistent with the literature, because we found areas with decreasing activity, as assumed in the paraglacial adjustment model, as well as moraine sections where no stabilization can be observed to date.

Sensitivity analysis of the DEM resolution and effective parameters of runoff yield in the SWAT model: a case study

Abstract This study investigates the impact of different digital elevation model (DEM) resolutions on the topological attributes and simulated runoff, as well as the sensitivity of runoff parameters in the Mahabad Dam watershed in Iran. The watershed and streamlines were delineated in ArcGIS, and the hydrologic analyses were performed using the Soil and Water Assessment Tool (SWAT). The sensitivity analysis on runoff parameters was performed, using the Sequential Uncertainties FItting Ver. 2 algorithm, in the SWAT Calibration and Uncertainty Procedures (SWAT-CUP) program. The results indicated that the sensitivity of runoff parameters, watershed surface area, and elevations changed under different DEM resolutions. As the distribution of slopes changed using different DEMs, surface parameters were most affected. Furthermore, higher amounts of runoff were generated when DEMs with finer resolutions were implemented. In comparison with the observed value of 8 m3/s at the watershed outlet, the 12.5 m DEM showed more realistic results (6.77 m3/s). Comparatively, the 12.5 m DEM generated 0.74% and 2.73% more runoff compared with the 30 and 90 m DEMs, respectively. The findings of this study indicate that in order to reduce computation time, researchers may use DEMs with coarser resolutions at the expense of minor decreases in accuracy.

Partitioned by process: Measuring post‐fire debris‐flow and rill erosion with Structure from Motion photogrammetry

AbstractAfter wildfire, hillslope and channel erosion produce large amounts of sediment and can contribute significantly to long‐term erosion rates. However, pre‐erosion high‐resolution topographic data (e.g. lidar) is often not available and determining specific contributions from post‐fire hillslope and channel erosion is challenging. The impact of post‐fire erosion on landscape evolution is demonstrated with Structure from Motion (SfM) Multi‐View Stereo (MVS) photogrammetry in a 1 km2 Idaho Batholith catchment burned in the 2016 Pioneer Fire. We use SfM‐MVS to quantify post‐fire erosion without detailed pre‐erosion topography and hillslope transects to improve estimates of rill erosion at adequate spatial scales. Widespread rilling and channel erosion produced a runoff‐generated debris‐flow following modest precipitation in October 2016. We implemented unmanned aerial vehicle (UAV)‐based SfM‐MVS to derive a 5 cm resolution digital elevation model (DEM) of the channel scoured by debris‐flow. In the absence of cm‐resolution pre‐erosion topography, a synthetic surface was defined by the debris‐flow scour's geomorphic signature and we used a DEM of Difference (DoD) to map and quantify channel erosion. We found 3467 ± 422 m3 was eroded by debris‐flow scour. Rill dimensions along hillslope transects and Monte Carlo simulation show rilling eroded ~1100 m3 of sediment and define a volume uncertainty of 29%. The total eroded volume (4600 ± 740 m3) we measured in our study catchment is partitioned into 75% channel erosion and 25% rill erosion, reinforcing the importance of catchment size on erosion process‐dominance. The deposit volume from the 2016 event was 5700 ± 1140 m3, indicating ~60% contribution from post‐fire channel erosion. Dating of charcoal fragments preserved in stratigraphy at the catchment outlet, and reconstructions of prior deposit volumes provide a record of Holocene fire‐related debris‐flows at this site; results suggest that episodic wildfire‐driven erosion (~6 mm/year) dominate millennial‐scale erosion (~5 mm/Ka) at this site. © 2019 John Wiley & Sons, Ltd. © 2019 John Wiley & Sons, Ltd.

Stabilization by geomorphic reclamation of a rotational landslide in an abandoned mine next to the Alto Tajo Natural Park

Two abandoned kaolin mines, surrounding one of the most outstanding natural parks of Spain, the Alto Tajo, have caused frequent environmental impacts. Within these are unstable areas prone to extensive mass movements that influence off-site sediment dynamics over the fluvial system. A waste dump in the Nuria mine obstructing a stream in the center of a valley experienced a rotational landslide. Mass movement between 2012 and 2014 was 0.025–0.026 m day−1. To mitigate the high risk of an earthflow, a novel stabilizing surface drainage technique was implemented. Two remedial valleys designed with fluvial channels were constructed surrounding the landslide main body using natural landform design and regrading, with no need for artificial materials such as concrete or piles. This novel remediation process is generically termed geomorphic reclamation. The specific method applied to this site was GeoFluv with Natural Regrade software. Before (2014) and after geomorphic stabilization (2015–2017), the landslide was monitored using Digital Elevation Models (DEMs) of Difference (DODs) obtained by a Geomorphic Change Detection (GCD) tool. Two modern techniques, Terrestrial Laser Scanning (TLS), and, Structure from Motion photogrammetry combined with an Unmanned Aerial Vehicle (SfM-UAV), were used to acquire High-Resolution Topographies (HRTs) from which DEMs were derived. Data analysis and field monitoring results demonstrate that: i) the Nuria mine transformed almost 50% of the upper part of a natural catchment; ii) a waste dump active landslide with a surface rupture <15m posed a high-risk hazard due to its continuous advance; iii) geomorphic reclamation succeeded in stabilizing the landslide during the monitoring period; iv) SfM-UAV-based topographies offer better accuracy and higher resolution, are cheaper and are obtained faster than TLS for mine areas.

Improving the Accuracy of Hydrodynamic Simulations in Data Scarce Environments Using Bayesian Model Averaging: A Case Study of the Inner Niger Delta, Mali, West Africa

In this paper, the study area was the Inner Niger Delta (IND) in Mali, West Africa. The IND is threatened by climate change, increasing irrigation, and dam operations. 2D hydrodynamic modelling was used to simulate water levels, discharge, and inundation extent in the IND. Three different digital elevation models (DEM) (SRTM, MERIT, and a DEM derived from satellite images were used as a source of elevation data. Six different models were created, with different sources of elevation data and different downstream boundary conditions. Given that the performance of the models varies according to the location in the IND, the variable under consideration and the performance criteria, Bayesian Model Averaging (BMA) was used to assess the relative performance of each of the six models. The BMA weights, along with deterministic performance measures, such as the Nash Sutcliffe coefficient (NS) and the Pearson’s correlation coefficient (r), provide quantitative evidence as to which model is the best when simulating a particular hydraulic variable at a particular location. After the models were combined with BMA, both discharge and water levels could be simulated with reasonable precision (NS &gt; 0.8). The results of this work can contribute to the more efficient management of water resources in the IND.

Volumetric Analysis of Reservoirs in Drought-Prone Areas Using Remote Sensing Products

Globally, the number of dams increased dramatically during the 20th century. As a result, monitoring water levels and storage volume of dam-reservoirs has become essential in order to understand water resource availability amid changing climate and drought patterns. Recent advancements in remote sensing data show great potential for studies pertaining to long-term monitoring of reservoir water volume variations. In this study, we used freely available remote sensing products to assess volume variations for Lake Mead, Lake Powell and reservoirs in California between 1984 and 2015. Additionally, we provided insights on reservoir water volume fluctuations and hydrological drought patterns in the region. We based our volumetric estimations on the area–elevation hypsometry relationship, by combining water areas from the Global Surface Water (GSW) monthly water history (MWH) product with corresponding water surface median elevation values from three different digital elevation models (DEM) into a regression analysis. Using Lake Mead and Lake Powell as our validation reservoirs, we calculated a volumetric time series for the GSWMWH–DEMmedian elevation combinations that showed a strong linear ‘area (WA) – elevation (WH)’ (R2 &gt; 0.75) hypsometry. Based on ‘WA-WH’ linearity and correlation analysis between the estimated and in situ volumetric time series, the methodology was expanded to reservoirs in California. Our volumetric results detected four distinct periods of water volume declines: 1987–1992, 2000–2004, 2007–2009 and 2012–2015 for Lake Mead, Lake Powell and in 40 reservoirs in California. We also used multiscalar Standardized Precipitation Evapotranspiration Index (SPEI) for San Joaquin drainage in California to assess regional links between the drought indicators and reservoir volume fluctuations. We found highest correlations between reservoir volume variations and the SPEI at medium time scales (12–18–24–36 months). Our work demonstrates the potential of processed, open source remote sensing products for reservoir water volume variations and provides insights on usability of these variations in hydrological drought monitoring. Furthermore, the spatial coverage and long-term temporal availability of our data presents an opportunity to transfer these methods for volumetric analyses on a global scale.

Assessing geomorphic changes induced by a debris-flow: a case study in the Dolomites

The study of landscapes and of their dynamics has become fundamental to understand natural hazard mechanisms and the better planning of mitigation measures to prevent damages and losses. Debris flows are a common natural hazard for mountain areas. One major event occurred on the August 5th, 2017 in the Prags-Braies valley (Italian Alps). Heavy rainfall triggered the movement of loosesediments from talus slopes within the Schade catchment into the village of Schmieden-Ferrara. This study aims to analyze the debrisflow event by using a DEM of Difference (DoD) approach to estimate the mobilized materials and identify the spatial patterns of erosion and deposition in the catchment. Two different methods to estimate the error and propagate uncertainty of DTMs into the DoD were tested and compared: i) spatially uniform constant error threshold, and ii) spatially variable uncertainty through a fuzzy approach. The elaboration was carried out using the fuzzy approach as this was considered the most reliable for the study case. The result showed a net balance of –115,719 ± 46,043 m3. This value was taken as a reference for the design of a sediment retention basin at the catchment outlet, currently under construction by the local Civil Protection Agency.

Accounting for permafrost creep in high-resolution snow depth mapping by modelling sub-snow ground deformation

Snow depth estimation derived from high-resolution digital elevation models (DEMs) can lead to improved understanding of the spatially highly heterogeneous nature of snow distribution, as well as help us improve our knowledge of how snow patterns influence local geomorphic processes. Slope deformation processes such as permafrost creep can make it challenging to acquire a snow-free DEM that matches the sub-snow topography at the time of the associated snow-covered DEM, which can cause errors in the computed snow depths. In this study, we illustrate how modelling changes in the sub-snow topography can reduce errors in snow depths derived from DEM differencing in an area of permafrost creep. To model the sub-snow topography, a surface deformation model was constructed by performing non-rigid registration based on B-splines of two snow-free DEMs. Seasonal variations in creep were accounted for by using an optimization approach to find a suitable value to scale the deformation model based on in-situ snow depth measurements or the presence of snow-free areas corresponding to the date of the snow-covered DEM. This scaled deformation model was used to transform one of the snow-free DEMs to estimate the sub-snow topography corresponding to the date of the snow-covered DEM. The performance of this method was tested on an active rock glacier in the southern French Alps for two surveys dates, which were conducted in the winter and spring of 2017.By accounting for surface displacements caused by permafrost creep, we found that our method was able to reduce the errors in the estimated snow depths by up to 33% (an interquartile range reduction of 11 cm) compared to using the untransformed snow-free DEM. The accuracy of the snow depths only slightly improved (root-mean-square error decrease of up to 3 cm). Greater reductions in error were observed for the snow depths calculated for the date that was furthest (i.e., the winter survey) in time from the snow-free DEM. Additionally, we found that our approach to scaling the deformation model has promising potential to be adapted for monitoring seasonal variations in permafrost creep by combining in-situ snow depth measurements with high-resolution surface deformation models.

Quantitative Analysis of Anthropogenic Morphologies Based on Multi-Temporal High-Resolution Topography

Human activities have reshaped the geomorphology of landscapes and created vast anthropogenic geomorphic features, which have distinct characteristics compared with landforms produced by natural processes. High-resolution topography from LiDAR has opened avenues for the analysis of anthropogenic geomorphic signatures, providing new opportunities for a better understanding of Earth surface processes and landforms. However, quantitative identification and monitoring of such anthropogenic signature still represent a challenge for the Earth science community. The purpose of this contribution is to explore a method for monitoring geomorphic changes and identifying the driving forces of such changes. The study was carried out on the Eibar watershed in Spain. The proposed method is able to quantitatively detect anthropogenic geomorphic changes based on multi-temporal LiDAR topography, and it is based on a combination of two techniques: the DEM of Difference (DoD) and the Slope Local Length of Auto-correlation (SLLAC). First, we tested the capability of the SLLAC and derived parameters to distinguish different types of anthropogenic geomorphologies in 5 study case at a small scale. Second, we calculated the DoD to quantify the geomorphic changes between 2008 and 2016. Based on the proposed approach, we classified the whole basin into three categories of geomorphic changes (natural, urban or mosaic areas). The urban area had the most clustered and largest geomorphic changes, followed by the mosaic area and the natural area. This research might help to identify and monitoring anthropogenic geomorphic changes over large areas, to schedule sustainable environmental planning, and to mitigate the consequences of anthropogenic alteration.

Assessment of Landslide Susceptibility Using Statistical- and Artificial Intelligence-Based FR–RF Integrated Model and Multiresolution DEMs

Landslide is one of the most important geomorphological hazards that cause significant ecological and economic losses and results in billions of dollars in financial losses and thousands of casualties per year. The occurrence of landslide in northern Iran (Alborz Mountain Belt) is often due to the geological and climatic conditions and tectonic and human activities. To reduce or control the damage caused by landslides, landslide susceptibility mapping (LSM) and landslide risk assessment are necessary. In this study, the efficiency and integration of frequency ratio (FR) and random forest (RF) in statistical- and artificial intelligence-based models and different digital elevation models (DEMs) with various spatial resolutions were assessed in the field of LSM. The experiment was performed in Sangtarashan watershed, Mazandran Province, Iran. The study area, which extends to 1072.28 km2, is severely affected by landslides, which cause severe economic and ecological losses. An inventory of 129 landslides that occurred in the study area was prepared using various resources, such as historical landslide records, the interpretation of aerial photos and Google Earth images, and extensive field surveys. The inventory was split into training and test sets, which include 70 and 30% of the landslide locations, respectively. Subsequently, 15 topographic, hydrologic, geologic, and environmental landslide conditioning factors were selected as predictor variables of landslide occurrence on the basis of literature review, field works and multicollinearity analysis. Phased array type L-band synthetic aperture radar (PALSAR), ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), and SRTM (Shuttle Radar Topography Mission) DEMs were used to extract topographic and hydrologic attributes. The RF model showed that land use/land cover (16.95), normalised difference vegetation index (16.44), distance to road (15.32) and elevation (13.6) were the most important controlling variables. Assessment of model performance by calculating the area under the receiving operating characteristic curve parameter showed that FR–RF integrated model (0.917) achieved higher predictive accuracy than the individual FR (0.865) and RF (0.840) models. Comparison of PALSAR, ASTER, and SRTM DEMs with 12.5, 30 and 90 m spatial resolution, respectively, with the FR–RF integrated model showed that the prediction accuracy of FR–RF–PALSAR (0.917) was higher than FR–RF–ASTER (0.865) and FR–RF–SRTM (0.863). The results of this study could be used by local planners and decision makers for planning development projects and landslide hazard mitigation measures.

Glacier mass balance over the central Nyainqentanglha Range during recent decades derived from remote-sensing data

ABSTRACTTo obtain information on changes in glacier mass balance in the central Nyainqentanglha Range, a comprehensive study was carried out based on digital-elevation models derived from the 1968 topographic maps, the Shuttle Radar Topography Mission DEM (2000) and TerraSAR-X/TanDEM-X (2013). Glacier area changes between 1968 and 2016 were derived from topographic maps and Landsat OLI images. This showed the area contained 715 glaciers, with an area of 1713.42 ± 51.82 km2, in 2016. Ice cover has been shrinking by 0.68 ± 0.05% a−1 since 1968. The glacier area covered by debris accounted for 11.9% of the total and decreased in the SE–NW directions. Using digital elevation model differencing and differential synthetic aperture radar interferometry, a significant mass loss of 0.46 ± 0.10 m w.e. a−1 has been recorded since 1968; mass losses accelerated from 0.42 ± 0.20 m w.e. a−1 to 0.60 ± 0.20 m w.e. a−1 between 1968–2000 and 2000–2013, with thinning noticeably greater on the debris-covered ice than the clean ice. Surface-elevation changes can be influenced by ice cliffs, as well as debris cover and land- or lake-terminating glaciers. Changes showed spatial and temporal heterogeneity and a substantial correlation with climate warming and decreased precipitation.

UAVs for Structure-From-Motion Coastal Monitoring: A Case Study to Assess the Evolution of Embryo Dunes over a Two-Year Time Frame in the Po River Delta, Italy.

Coastal environments are usually characterized by a brittle balance, especially in terms of sediment transportation. The formation of dunes, as well as their sudden destruction as a result of violent storms, affects this balance in a significant way. Moreover, the growth of vegetation on the top of the dunes strongly influences the consequent growth of the dunes themselves. This work presents the results obtained through a long-term monitoring of a complex dune system by the use of Unmanned Aerial Vehicles (UAVs). Six different surveys were carried out between November 2015 and December 2017 in the littoral of Rosolina Mare (Italy). Aerial photogrammetric data were acquired during flight repetitions by using a DJI Phantom 3 Professional with the camera in a nadiral arrangement. The processing of the captured images consisted of the reconstruction of a three-dimensional model using the Structure-from-Motion (SfM). Each model was framed in the European Terrestrial Reference System (ETRS) using GNSS geodetic receivers in Network Real Time Kinematic (NRTK). Specific data management was necessary due to the vegetation by filtering the dense cloud. This task was performed by both performing a slope detection and a removal of the residual outliers. The final products of this approach were thus represented by Digital Elevation Models (DEMs) of the sandy coastal section. In addition, DEMs of Difference (DoD) were also computed for the purpose of monitoring over time and detecting variations. The accuracy assessment of the DEMs was carried out by an elevation comparison through especially GNSS-surveyed points. Relevant cross sections were also extracted and compared. The use of the Structure-from-Motion approach by UAVs finally proved to be both reliable and time-saving thanks to quicker in situ operations for the data acquisition and an accurate reconstruction of high-resolution elevation models. The low cost of the system and its flexibility represent additional strengths, making this technique highly competitive with traditional ones.

A Workflow to Estimate Topographic and Volumetric Changes and Errors in Channel Sedimentation after Disturbance

Light Detection and Ranging (LiDAR) methods, such as ground-based Terrestrial Laser Scanning (TLS), have enabled collection of high-resolution point clouds of elevation data to calculate changes in fluvial systems after disturbance, but are often accompanied by uncertainty and errors. This paper reviews and compares TLS analysis methods and develops a workflow to estimate topographic and volumetric changes in channel sedimentation after disturbance. Four analytic methods to estimate topographic and volumetric changes were compared by quantifying the uncertainty in TLS-derived products: Digital Elevation Model (DEM) of difference (DOD), Cloud to Cloud (C2C), Cloud to Mesh (C2M), and Multiple Model to Model Cloud Comparison (M3C2). Mean errors across surfaces within each dataset contributed to a propagation error of 0.015–0.016 m and 0.017–0.018 m for the point clouds and derived DEMs, respectively. The estimated error of the total volumetric change implied increased errors in the conversion of point clouds into a surface by C2M and DOD; whereas C2C and M3C2 were generally simpler, efficient, and accurate techniques for evaluating topographic changes. The comparison of methods to analyze TLS data will contribute to applications of remote sensing of hydro-geomorphic processes in stream channels after disturbance. The workflow presented also aids in estimating uncertainties inherent in data collection and analytic methods for topographic and volumetric change analysis.

Landcover-Dependent Assessment of the Relative Height Accuracy in TanDEM-X DEM Products

Digital elevation models (DEMs) are extensively used for a variety of scientific and commercial applications. For the global TanDEM-X DEM, one of the main performance parameters is the relative height accuracy, which is specified to be under 2 m for flat terrain. Land cover types where the radar signal penetrates into a volume, as forest and ice, are excluded from this specification. Knowing the accuracy of the DEM for a specific land cover type is essential for applications relying on it, such as navigation applications, gradient and aspect estimations, and others. This letter is meant to be as add-on the global relative analysis presented in [1] . Here, we present a characterization of the relative height accuracy based on the interferometric coherence assessing the performance for every class defined by the CCI Land Cover Maps at a continental and global basis. This characterization raises the awareness of the advantages and limitations of the DEM for each specific application and helps scientists using the TanDEM-X DEM to interpret their results. In addition, an estimation of the relative height accuracy for acquisitions where volume decorrelation is present is locally performed using the high-frequency component of repeat-pass DEMs differences. For two particular land cover types, both methods are compared. The main source of errors in the DEM generation is clearly associated with strong inhomogeneous signal returns, becoming a driving factor on the actual accuracy of the estimated mean phase center height.

MULTI-SENSOR GEODETIC APPROACH FOR LANDSLIDE DETECTION AND MONITORING

Abstract. The lesser Himalayan region is mostly affected by landslide events occurring due to rainfall, steep slopes and presence of tectonic activity beneath, causing loss of life and property. Some critical zones in the region have encountered recurring landslides over the past and need careful investigation for better planning and rescue operations. This research work presents a geodetic framework comprising multiple sensors to monitor the Sirobagarh landslide in Uttarakhand, India, which is affected by recurring landslides. Three field visits were made to this site for geodetic data collection using Terrestrial Laser Scanner (TLS), Global Navigation Satellite System (GNSS) and Robotic Total Station (RTS). Co-registration and vegetation removal of the TLS scans corresponding to the three visits resulted in generation of three Digital Elevation Models (DEM), which were differenced to estimate temporal movement of the landslide scarp. DEM differences indicate subsidence of the landslide scarp with vertical displacement values ranging from −0.05 to −5.0 m. Rainfall induced debris flow is one of the prominent reason for large displacement magnitude (∼5 m) in the upper landslide scarp. Horizontal displacement estimates obtained by geodetic network analysis of six GNSS stations installed on the study site show movement towards the Alaknanda river. The maximum horizontal and vertical displacement values for the GNSS stations were 0.1305 m and −2.1315 m respectively. Similar pattern is observed by displacement measurements of RTS target reflectors installed on a retaining wall constructed to arrest the debris flow approaorching the National Highway. The displacement estimates obtained from the sensors applied in this study indicate subsidence of the landslide scarp and surroundings. More time series observations can provide better understanding of the overall deformation process.

Modelling the dynamics of a large rock landslide in the Dolomites (eastern Italian Alps) using multi-temporal DEMs.

Latest advances in topographic data acquisition techniques have greatly enhanced the possibility to analyse landscapes in order to understand the processes that shaped them. High-resolution Digital Elevation Models (DEMs), such as LiDAR-derived ones, provide detailed topographic information. In particular, if multi-temporal DEMs are available, it is possible to carry out a detailed geomorphic change detection analysis. This analysis may provide information about the dynamics of large landslides and may thus, be useful for landslide risk assessments. However, LiDAR-derived DEMs are mostly available only as post-event surveys. The technique is relatively recent, and local or national authorities only started widespread surveys in the last decade. Therefore, it is of a certain interest to analyse the effectiveness of DEMs derived from technical cartography to produce reliable volumetric estimates related to large landslides. This study evaluates the use of a multi-source DEM of Difference (DoD) analysis for the investigation of a large landslide –Le Laste–, which occurred on November 12, 2014 on Mount Antelao (eastern Italian Alps). The landslide initiated as a 365,000 m3 rockslide close to the summit of the mountain and transformed into a debris avalanche during its runout. The comparison of pre- and post-event DEMs allowed for the identification and quantification of erosion and deposition areas, and for the estimation of landslide volume. A sound back-analysis of the landslide with the 3D numerical model DAN3D was based on this comparison and on seismic records of the event. These seismic records proved to be remarkably useful, as they allowed for the calibration of the simulated landslide velocity. This ensured the reliability of the model notwithstanding the topographic datasets, intrinsic uncertainties. We found that using a pre-event DEM derived from technical cartography tends to slightly overestimate the volume with respect to the use of the more accurate LiDAR-derived DEM. In recent years, the landslide risk around Mt. Antelao has been increasing alongside the ever-growing population and human activities in the area. Sediment accumulations produced by the Le Laste landslide significantly amplified the debris flow hazard by providing new sediment sources. Therefore, it is crucial to delineate the distribution of this material to enable an adequate debris flow hazard assessment. The material properties derived from the back-analysis of the Le Laste landslide can be used to simulate the runout of possible future events, and to generate reliable hazard zone maps, which are necessary for effective risk mitigation.