scholarly journals Detection of Levee Damage Based on UAS Data—Optical Imagery and LiDAR Point Clouds

2020 ◽  
Vol 9 (4) ◽  
pp. 248
Author(s):  
Krzysztof Bakuła ◽  
Magdalena Pilarska ◽  
Adam Salach ◽  
Zdzisław Kurczyński
Keyword(s):  
Laser Scanning ◽  
Vegetation Index ◽  
Laser Scanner ◽  
Digital Terrain Model ◽  
Point Clouds ◽  
Optical Data ◽  
Terrain Model ◽  
Digital Terrain ◽  
Levee Failure ◽  
Multi Temporal

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.

scholarly journals TECHNIQUE OF AUTOMATIC MOBILE LASER SCANNING DATA FILTERING

2021 ◽  
Vol 26 (3) ◽  
pp. 5-19
Author(s):  
Maxim A. Altyntsev ◽  
◽  
Hamid Majid Saber Karkokli ◽  
Keyword(s):  
Laser Scanning ◽  
Single Point ◽  
Laser Scanner ◽  
Digital Terrain Model ◽  
Weather Conditions ◽  
Automatic Generation ◽  
Data Filtering ◽  
Terrain Model ◽  
Digital Terrain ◽  
Filtration Technique

The result of laser scanning is an array of laser points. The generation of a single point cloud in a given coordinate system is carried out during the registration process at the stage of preliminary field data processing. At this stage it is also often necessary to filter the data. Laser points with an erroneous position are eliminated during the data filleting. The number of erroneous laser points is determined by the of the laser scanner characteristics, surveyed area peculiarities and weather conditions. The devel-opment of methods and algorithms for filtering laser scanning data is carried out based on the analysis of the laser point spatial position and a certain set of additional characteristics, such as intensity value, echo signal, color value. The technique of mobile laser scanning data filtering for the territory of the road passing among the forest and close to individual industrial facilities and building. The main goal of the proposed filtration technique is to obtain data for automatic generation of an accurate digital terrain model. The filtration technique was developed for data acquired under the least favorable con-ditions – in wet weather. Accuracy estimation of generating digital terrain model based on filtered data was carried out.

scholarly journals Aerial Laser Scanning Data as a Source of Terrain Modeling in a Fluvial Environment: Biasing Factors of Terrain Height Accuracy

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 2063 ◽  
Author(s):  
Zsuzsanna Szabó ◽  
Csaba Albert Tóth ◽  
Imre Holb ◽  
Szilárd Szabó
Keyword(s):  
Laser Scanning ◽  
Digital Terrain Model ◽  
Point Clouds ◽  
Threshold Value ◽  
Noise Filtering ◽  
Terrain Model ◽  
Digital Terrain ◽  
Natural Neighbor ◽  
Wide Range ◽  
Ground Point

Airborne light detection and ranging (LiDAR) scanning is a commonly used technology for representing the topographic terrain. As LiDAR point clouds include all surface features present in the terrain, one of the key elements for generating a digital terrain model (DTM) is the separation of the ground points. In this study, we intended to reveal the efficiency of different denoising approaches and an easy-to-use ground point classification technique in a floodplain with fluvial forms. We analyzed a point cloud from the perspective of the efficiency of noise reduction, parametrizing a ground point classifier (cloth simulation filter, CSF), interpolation methods and resolutions. Noise filtering resulted a wide range of point numbers in the models, and the number of points had moderate correlation with the mean accuracies (r = −0.65, p < 0.05), indicating that greater numbers of points had larger errors. The smallest differences belonged to the neighborhood-based noise filtering and the larger cloth size (5) and the smaller threshold value (0.2). The most accurate model was generated with the natural neighbor interpolation with the cloth size of 5 and the threshold of 0.2. These results can serve as a guide for researchers using point clouds when considering the steps of data preparation, classification, or interpolation in a flat terrain.

scholarly journals Terrestrial Laser Scanning (TLS) as a detection method of the natural river valley microtopography – case study of the Upper Biebrza

2014 ◽  
Vol 46 (4) ◽  
pp. 276-278 ◽  
Author(s):  
Marcin Brach ◽  
Jarosław Chormański
Keyword(s):  
Laser Scanning ◽  
Detection Method ◽  
Laser Scanner ◽  
Digital Terrain Model ◽  
Terrestrial Laser Scanning ◽  
River Valley ◽  
Gis Analysis ◽  
Terrain Model ◽  
Digital Terrain

Abstract Terrestrial Laser Scanning (TLS) as a detection method of the natural river valley microtopography - case study of the Upper Biebrza. This paper concerns the use of Terrestrial Laser Scanning (TLS) methods and the Geographic Information Systems (GIS) analysis to determine microtopography of a natural river valley, case study of the upper Biebrza valley. The scientific problem analyzed in this paper is a morphology of the selected segments of the valley covered by sedge ecosystems which in natural stage form a characteristic tussocks from their root systems. In order to capture the microtopography it was necessary to remove vegetation from the selected areas, and then, for a five typical location, registration of its structure using the laser scanner. As a result the point cloud was generated for each of the selected area and after GIS analysis the microtopography was obtained in form of digital terrain model (DTM). The DTM of each area represents valleys microstructure possible to obtain by use of TLS (TLS DTM), is usually not registered by the Airborne Laser Scanning (ALS), and is the main reason of inaccuracy of the DTM obtained based on ALS. The resulting TLS DTM has been processed by various filtering methods to lower the noise and fill the voids from blocking the laser beam by a tussocks. Finally, this allowed to determine the spatial structure of each measurement field.

scholarly journals Integrated Laser Scanner Techniques to Produce High-Resolution DTM of Vegetated Territory

2021 ◽  
Vol 13 (13) ◽  
pp. 2504
Author(s):  
Federica Marotta ◽  
Simone Teruggi ◽  
Cristiana Achille ◽  
Giorgio Paolo Maria Vassena ◽  
Francesco Fassi
Keyword(s):  
High Resolution ◽  
Laser Scanner ◽  
Digital Terrain Model ◽  
Point Clouds ◽  
Terrain Model ◽  
Digital Terrain ◽  
3D Data ◽  
Detection And Identification ◽  
Geological Features ◽  
The Creation

The paper presents the first part of a research project concerning the creation of 3D terrain models useful to understand landslide movements. Thus, it illustrates the creation process of a multi-source high-resolution Digital Terrain Model (DTM) in very dense vegetated areas obtained by integrating 3D data coming from three sources, starting from long and medium-range Terrestrial Laser Scanner up to a Backpack Indoor Mobile Mapping System. The point clouds are georeferenced by means of RKT GNSS points and automatically filtered using a Cloth Simulation Filter algorithm to separate points belonging to the ground. Those points are interpolated to produce the DTMs which are then mosaicked to obtain a unique multi-resolution DTM that plays a crucial role in the detection and identification of specific geological features otherwise visible. Standard deviation of residuals of the DTM varies from 0.105 m to 0.176 m for Z coordinate, from 0.065 m to 0.300 m for X and from 0.034 m to 0.175 m for Y. The area under investigation belongs to the Municipality of Piuro (SO) and includes both the town and surrounding valley. It was affected by a dramatic landslide in 1618 that destroyed the entire village. Numerous challenges have been faced, caused both by the characteristics of the area and the processed data. The complexity of the case study turns out to be an excellent test bench for the employed technologies, providing the opportunity to precisely identify the needed direction to obtain future promising results.

scholarly journals Comparing Filtering Techniques for Removing Vegetation from UAV-Based Photogrammetric Point Clouds

Drones ◽  
2019 ◽  
Vol 3 (3) ◽  
pp. 61 ◽  
Author(s):  
Niels Anders ◽  
João Valente ◽  
Rens Masselink ◽  
Saskia Keesstra
Keyword(s):  
Vegetation Index ◽  
Digital Terrain Model ◽  
Point Clouds ◽  
Mediterranean Area ◽  
Alternative Methods ◽  
Terrain Model ◽  
Digital Terrain ◽  
Filter Methods ◽  
Digital Elevation ◽  
Filtering Techniques

Digital Elevation Models (DEMs) are 3D representations of the Earth’s surface and have numerous applications in geomorphology, hydrology and ecology. Structure-from-Motion (SfM) photogrammetry using photographs obtained by unmanned aerial vehicles (UAVs) have been increasingly used for obtaining high resolution DEMs. These DEMs are interpolated from point clouds representing entire landscapes, including points of terrain, vegetation and infrastructure. Up to date, there has not been any study clearly comparing different algorithms for filtering of vegetation. The objective in this study was, therefore, to assess the performance of various vegetation filter algorithms for SfM-obtained point clouds. The comparison was done for a Mediterranean area in Murcia, Spain with heterogeneous vegetation cover. The filter methods that were compared were: color-based filtering using an excessive greenness vegetation index (VI), Triangulated Irregular Networks (TIN) densification from LAStools, the standard method in Agisoft Photoscan (PS), iterative surface lowering (ISL), and a combination of iterative surface lowering and the VI method (ISL_VI). Results showed that for bare areas there was little to no difference between the filtering methods, which is to be expected because there is little to no vegetation present to filter. For areas with shrubs and trees, the ISL_VI and TIN method performed best. These results show that different filtering techniques have various degrees of success in different use cases. A default filter in commercial software such as Photoscan may not always be the best way to remove unwanted vegetation from a point cloud, but instead alternative methods such as a TIN densification algorithm should be used to obtain a vegetation-less Digital Terrain Model (DTM).

scholarly journals DTM-based analysis of the spatial distribution of topolineaments

2020 ◽  
Vol 12 (1) ◽  
pp. 1185-1199
Author(s):  
Mirosław Kamiński
Keyword(s):  
Laser Scanning ◽  
Digital Terrain Model ◽  
Research Area ◽  
Tectonic Structures ◽  
Empirical Bayesian ◽  
Scanning Method ◽  
Empirical Bayesian Kriging ◽  
Terrain Model ◽  
Digital Terrain ◽  
Airborne Laser

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.

scholarly journals Automated Generation of Digital Terrain Model using Point Clouds of Digital Surface Model in Forest Area

2011 ◽  
Vol 3 (5) ◽  
pp. 845-858 ◽  
Author(s):  
Kande R.M.U. Bandara ◽  
Lal Samarakoon ◽  
Rajendra P. Shrestha ◽  
Yoshikazu Kamiya
Keyword(s):  
Digital Terrain Model ◽  
Point Clouds ◽  
Forest Area ◽  
Surface Model ◽  
Digital Surface Model ◽  
Automated Generation ◽  
Terrain Model ◽  
Digital Terrain

scholarly journals Automating the creation of channel cross section data from aerial laser scanning and hydrological surveying for modeling flood events / Automatická tvorba geometrie vodních toků na základě syntézy dat z leteckého laserového skenování a hydrologického měření pro modelování povodňových událostí. j. hydrol., hydromech., 60, 2012, 4; 25 lit., 8 obr., 5 tab.

2012 ◽  
Vol 60 (4) ◽  
pp. 227-241 ◽  
Author(s):  
Radek Roub ◽  
Tomáš Hejduk ◽  
Pavel Novák
Keyword(s):  
Flow Rate ◽  
Hydrodynamic Model ◽  
Input Data ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
Flood Events ◽  
Hydrodynamic Models ◽  
Terrain Model ◽  
Aerial Laser Scanning ◽  
Digital Terrain

Knowing the extent of inundation areas for individual N-year flood events, the specific flood scenarios, and having an idea about the depths and velocities in the longitudinal or transverse water course profile provided by hydrodynamic models is of key importance for protecting peoples’ lives and mitigating damage to property. Input data for creating the watercourse computational geometry are crucial for hydrodynamic models. Requirements for input data vary with respect to the hydrodynamic model used. One-dimensional (1D) hydrodynamic models in which the computing track is formed by cross-sectional profiles of the channel are characterized by lower requirements for input data. In two-dimensional (2D) hydrodynamic models, a digital terrain model is needed for the entire area studied. Financial requirements of the project increase with regard to the input data and the model used. The increase is mainly due to the high cost of the geodetic surveying of the stream channel. The paper aims at a verification and presentation of the suitability of using hydrological measurements in developing a schematization (geometry) of water courses based on topographic data gained from aerial laser scanning provided by the Czech Office for Surveying, Mapping and Cadastre. Taking into account the hydrological measurement during the schematization of the water course into the hydrodynamic model consists in the derivation of flow rate achieved at the time of data acquisition using the method of aerial laser scanning by means of hydrological analogy and in using the established flow rate values as a basis for deepening of the digital terrain model from aerial laser scanning data. Thus, the given principle helps to capture precisely the remaining part of the channel profile which is not reflected in the digital terrain model prepared by the method of aerial laser scanning and fully correct geometry is achieved for the hydrodynamic model.

scholarly journals Threat of Pollution Hotspots Reworking in River Systems: Case Study of the Ploučnice River (Czech Republic)

2019 ◽  
Vol 8 (1) ◽  
pp. 37 ◽  
Author(s):  
Jitka Elznicová ◽  
Tomáš Matys Grygar ◽  
Jan Popelka ◽  
Martin Sikora ◽  
Petr Novák ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Digital Terrain Model ◽  
Terrain Model ◽  
Non Invasive ◽  
Digital Terrain ◽  
Quality Of Water ◽  
Lateral Channel ◽  
Floodplain Development ◽  
Channel Deposits

As fluvial pollution may endanger the quality of water and solids transported by rivers, mapping and evaluation of historically polluted fluvial sediments is an urgent topic. The Ploučnice River and its floodplain were polluted by local uranium mining from 1971–1989. We have studied this river since 2013 using a combination of diverse methods, including geoinformatics, to identify pollution hotspots in floodplains and to evaluate the potential for future reworking. Archival information on pollution history and past flooding was collected to understand floodplain dynamics and pollution heterogeneity. Subsequently, a digital terrain model based on laser scanning data and data analysis were used to identify the sites with river channel shifts. Finally, non-invasive geochemical mapping was employed, using portable X-ray fluorescence and gamma spectrometers. The resulting datasets were processed with geostatistical tools. One of the main outputs of the study was a detailed map of pollution distribution in the floodplain. The results showed a relationship between polluted sediment deposition, past channel shifts and floodplain development. We found that increased concentration of pollution occurred mainly in the cut-off meanders and lateral channel deposits from the mining period, the latter in danger of reworking (reconnecting to the river) in the coming decades.

scholarly journals Photogrammetric surveying forests and woodlands with UAVs: techniques for automatic removal of vegetation and digital terrain model production for hydrological applications

2019 ◽  
Vol 7 (1) ◽  
pp. 1-20
Author(s):  
Fotis Giagkas ◽  
Petros Patias ◽  
Charalampos Georgiadis
Keyword(s):  
Vegetation Type ◽  
Digital Terrain Model ◽  
Point Clouds ◽  
Aerial Images ◽  
Surface Model ◽  
Terrain Model ◽  
Vegetation Height ◽  
Digital Terrain ◽  
Dense Point ◽  
Height Model

The purpose of this study is the photogrammetric survey of a forested area using unmanned aerial vehicles (UAV), and the estimation of the digital terrain model (DTM) of the area, based on the photogrammetrically produced digital surface model (DSM). Furthermore, through the classification of the height difference between a DSM and a DTM, a vegetation height model is estimated, and a vegetation type map is produced. Finally, the generated DTM was used in a hydrological analysis study to determine its suitability compared to the usage of the DSM. The selected study area was the forest of Seih-Sou (Thessaloniki). The DTM extraction methodology applies classification and filtering of point clouds, and aims to produce a surface model including only terrain points (DTM). The method yielded a DTM that functioned satisfactorily as a basis for the hydrological analysis. Also, by classifying the DSM–DTM difference, a vegetation height model was generated. For the photogrammetric survey, 495 aerial images were used, taken by a UAV from a height of ∼200 m. A total of 44 ground control points were measured with an accuracy of 5 cm. The accuracy of the aerial triangulation was approximately 13 cm. The produced dense point cloud, counted 146 593 725 points.

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