Application of a multi-temporal, LiDAR-derived, digital terrain model in a landslide-volume estimation

2013 ◽  
pp. n/a-n/a ◽  
Author(s):  
Chih-Ming Tseng ◽  
Ching-Weei Lin ◽  
Colin P. Stark ◽  
Jin-Kin Liu ◽  
Li-Yuan Fei ◽  
...  
Author(s):  
A. C. Dalagan ◽  
J. A. Principe

Abstract. Southwest Monsoon (Habagat) and Typhoon Luis caused a deep-seated landslide that struck Sitio Kayang, Brgy. Immuli, Pidigan, Abra on August 15, 2018. Rainfall-induced deep-seated landslides displace partially at a time which necessitates the determination of remaining landslide volume along the slope. In this study, the potential landslide volume and mass transport were estimated using several remote sensing products, including SAR (Synthetic Aperture Radar) data and LiDAR-DTM (Light Detection and Ranging-Digital Terrain Model). The post-landslide DTM was generated using Sentinel-1 SAR data. The potential landslide volume and landslide failure surfaces were ascertained through the stability analysis using Scoops3D, while the mass transport volume was obtained from the pre- and post-landslide DTM. Results showed that the estimated total volume in all the landslide areas was 135,962 m3. Meanwhile, the remaining landslide volume (i.e., difference between potential volume from pre-landslide event and volume of transported mass) yielded illogical values due to the derived large mass transport values. This blunder may be attributed to the generalization of the transported volume (due to Sentinel-1 DTM coarse resolution), and decorrelation due to vegetation cover. Overall, the LiDAR-DTM data delivered a high-resolution estimation of the potential landslide volume and proved to be useful for landslide application studies. Future studies may incorporate field data (e.g., geotechnical parameters, groundwater, landslide actual measurements) for more accurate performance of stability analysis and may best to utilize LiDAR-DTM in post-landslide volume computation for a more reliable estimation of mass transport and potentially remaining landslide volume.


2020 ◽  
Vol 9 (4) ◽  
pp. 248
Author(s):  
Krzysztof Bakuła ◽  
Magdalena Pilarska ◽  
Adam Salach ◽  
Zdzisław Kurczyński

This paper presents a methodology for levee damage detection based on Unmanned Aerial System (UAS) data. In this experiment, the data were acquired from the UAS platform, which was equipped with a laser scanner and a digital RGB (Red, Green, Blue) camera. Airborne laser scanning (ALS) point clouds were used for the generation of the Digital Terrain Model (DTM), and images were used to produce the RGB orthophoto. The main aim of the paper was to present a methodology based on ALS and vegetation index from RGB orthophoto which helps in finding potential places of levee failure. Both types of multi-temporal data collected from the UAS platform are applied separately: elevation and optical data. Two DTM models from different time periods were compared: the first one was generated from the ALS point cloud and the second DTM was delivered from the UAS Laser Scanning (ULS) data. Archival and new orthophotos were converted to Green-Red Vegetation Index (GRVI) raster datasets. From the GRVI raster, change detection for unvegetation ground areas was analysed using a dynamically indicated threshold. The result of this approach is the localisation of places, for which the change in height correlates with the appearance of unvegetation ground. This simple, automatic method provides a tool for specialist monitoring of levees, the critical objects protecting against floods.


Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 265
Author(s):  
Mihnea Cățeanu ◽  
Arcadie Ciubotaru

Laser scanning via LiDAR is a powerful technique for collecting data necessary for Digital Terrain Model (DTM) generation, even in densely forested areas. LiDAR observations located at the ground level can be separated from the initial point cloud and used as input for the generation of a Digital Terrain Model (DTM) via interpolation. This paper proposes a quantitative analysis of the accuracy of DTMs (and derived slope maps) obtained from LiDAR data and is focused on conditions common to most forestry activities (rough, steep terrain with forest cover). Three interpolation algorithms were tested: Inverse Distance Weighted (IDW), Natural Neighbour (NN) and Thin-Plate Spline (TPS). Research was mainly focused on the issue of point data density. To analyze its impact on the quality of ground surface modelling, the density of the filtered data set was artificially lowered (from 0.89 to 0.09 points/m2) by randomly removing point observations in 10% increments. This provides a comprehensive method of evaluating the impact of LiDAR ground point density on DTM accuracy. While the reduction of point density leads to a less accurate DTM in all cases (as expected), the exact pattern varies by algorithm. The accuracy of the LiDAR-derived DTMs is relatively good even when LiDAR sampling density is reduced to 0.40–0.50 points/m2 (50–60 % of the initial point density), as long as a suitable interpolation algorithm is used (as IDW proved to be less resilient to density reductions below approximately 0.60 points/m2). In the case of slope estimation, the pattern is relatively similar, except the difference in accuracy between IDW and the other two algorithms is even more pronounced than in the case of DTM accuracy. Based on this research, we conclude that LiDAR is an adequate method for collecting morphological data necessary for modelling the ground surface, even when the sampling density is significantly reduced.


2020 ◽  
Vol 12 (1) ◽  
pp. 1185-1199
Author(s):  
Mirosław Kamiński

AbstractThe research area is located on the boundary between two Paleozoic structural units: the Radom–Kraśnik Block and the Mazovian–Lublin Basin in the southeastern Poland. The tectonic structures are separated by the Ursynów–Kazimierz Dolny fault zone. The digital terrain model obtained by the ALS (Airborne Laser Scanning) method was used. Classification and filtration of an elevation point cloud were performed. Then, from the elevation points representing only surfaces, a digital terrain model was generated. The model was used to visually interpret the course of topolineaments and their automatic extraction from DTM. Two topolineament systems, trending NE–SW and NW–SE, were interpreted. Using the kernel density algorithm, topolineament density models were generated. Using the Empirical Bayesian Kriging, a thickness model of quaternary deposits was generated. A relationship was observed between the course of topolineaments and the distribution and thickness of Quaternary formations. The topolineaments were compared with fault directions marked on tectonic maps of the Paleozoic and Mesozoic. Data validation showed consistency between topolineaments and tectonic faults. The obtained results are encouraging for further research.


2021 ◽  
Vol 10 (2) ◽  
pp. 91
Author(s):  
Triantafyllia-Maria Perivolioti ◽  
Antonios Mouratidis ◽  
Dimitrios Terzopoulos ◽  
Panagiotis Kalaitzis ◽  
Dimitrios Ampatzidis ◽  
...  

Covering an area of approximately 97 km2 and with a maximum depth of 58 m, Lake Trichonis is the largest and one of the deepest natural lakes in Greece. As such, it constitutes an important ecosystem and freshwater reserve at the regional scale, whose qualitative and quantitative properties ought to be monitored. Depth is a crucial parameter, as it is involved in both qualitative and quantitative monitoring aspects. Thus, the availability of a bathymetric model and a reliable DTM (Digital Terrain Model) of such an inland water body is imperative for almost any systematic observation scenario or ad hoc measurement endeavor. In this context, the purpose of this study is to produce a DTM from the only official cartographic source of relevant information available (dating back approximately 70 years) and evaluate its performance against new, independent, high-accuracy hydroacoustic recordings. The validation procedure involves the use of echosoundings coupled with GPS, and is followed by the production of a bathymetric model for the assessment of the discrepancies between the DTM and the measurements, along with the relevant morphometric analysis. Both the production and validation of the DTM are conducted in a GIS environment. The results indicate substantial discrepancies between the old DTM and contemporary acoustic data. A significant overall deviation of 3.39 ± 5.26 m in absolute bottom elevation differences and 0.00 ± 7.26 m in relative difference residuals (0.00 ± 2.11 m after 2nd polynomial model corrector surface fit) of the 2019 bathymetric dataset with respect to the ~1950 lake DTM and overall morphometry appear to be associated with a combination of tectonics, subsidence and karstic phenomena in the area. These observations could prove useful for the tectonics, geodynamics and seismicity with respect to the broader Corinth Rift region, as well as for environmental management and technical interventions in and around the lake. This dictates the necessity for new, extensive bathymetric measurements in order to produce an updated DTM of Lake Trichonis, reflecting current conditions and tailored to contemporary accuracy standards and state-of-the-art research in various disciplines in and around the lake.


Drones ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 20
Author(s):  
Joseph P. Hupy ◽  
Cyril O. Wilson

Soil erosion monitoring is a pivotal exercise at macro through micro landscape levels, which directly informs environmental management at diverse spatial and temporal scales. The monitoring of soil erosion can be an arduous task when completed through ground-based surveys and there are uncertainties associated with the use of large-scale medium resolution image-based digital elevation models for estimating erosion rates. LiDAR derived elevation models have proven effective in modeling erosion, but such data proves costly to obtain, process, and analyze. The proliferation of images and other geospatial datasets generated by unmanned aerial systems (UAS) is increasingly able to reveal additional nuances that traditional geospatial datasets were not able to obtain due to the former’s higher spatial resolution. This study evaluated the efficacy of a UAS derived digital terrain model (DTM) to estimate surface flow and sediment loading in a fluvial aggregate excavation operation in Waukesha County, Wisconsin. A nested scale distributed hydrologic flow and sediment loading model was constructed for the UAS point cloud derived DTM. To evaluate the effectiveness of flow and sediment loading generated by the UAS point cloud derived DTM, a LiDAR derived DTM was used for comparison in consonance with several statistical measures of model efficiency. Results demonstrate that the UAS derived DTM can be used in modeling flow and sediment erosion estimation across space in the absence of a LiDAR-based derived DTM.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 3115-3122
Author(s):  
Danlei Ye ◽  
Xin Jiang ◽  
Guanying Huo ◽  
Cheng Su ◽  
Zehong Lu ◽  
...  

2002 ◽  
Vol 81 (2) ◽  
pp. 211-215 ◽  
Author(s):  
R.T. Van Balen ◽  
R.F. Houtgast ◽  
F.M. Van der Wateren ◽  
J. Vandenberghe

AbstractUsing marine planation surfaces, fluvial terraces and a digital terrain model, the amount of eroded rock volume versus time for the Meuse catchment has been computed. A comparison of the amount of eroded volume with the volume of sediment preserved in the Roer Valley Rift System shows that 12% of the eroded volume is trapped in this rift. The neotectonic uplift evolution of the Ardennes is inferred from the incision history of the Meuse River system and compared to the subsidence characteristics of the Roer Valley Rift System. Both areas are characterized by an early Middle Pleistocene uplift event.


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