scholarly journals A Strip Adjustment Method of UAV-Borne LiDAR Point Cloud Based on DEM Features for Mountainous Area

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2782
Author(s):  
Zequan Chen ◽  
Jianping Li ◽  
Bisheng Yang
Keyword(s):  
Laser Scanning ◽  
Ground Truth ◽  
Point Clouds ◽  
Mountainous Area ◽  
Mountainous Areas ◽  
Registration Method ◽  
Digital Elevation ◽  
Global Consistency ◽  
Manual Registration ◽  
Elevation Model

Due to the trajectory error of the low-precision position and orientation system (POS) used in unmanned aerial laser scanning (ULS), discrepancies usually exist between adjacent LiDAR (Light Detection and Ranging) strips. Strip adjustment is an effective way to eliminate these discrepancies. However, it is difficult to apply existing strip adjustment methods in mountainous areas with few artificial objects. Thus, digital elevation model-iterative closest point (DEM-ICP), a pair-wise registration method that takes topography features into account, is proposed in this paper. First, DEM-ICP filters the point clouds to remove the non-ground points. Second, the ground points are interpolated to generate continuous DEMs. Finally, a point-to-plane ICP algorithm is performed to register the adjacent DEMs with the overlapping area. A graph-based optimization is utilized following DEM-ICP to estimate the correction parameters and achieve global consistency between all strips. Experiments were carried out using eight strips collected by ULS in mountainous areas to evaluate the proposed method. The average root-mean-square error (RMSE) of all data was less than 0.4 m after the proposed strip adjustment, which was only 0.015 m higher than the result of manual registration (ground truth). In addition, the plane fitting accuracy of lateral point clouds was improved 4.2-fold, from 1.565 to 0.375 m, demonstrating the robustness and accuracy of the proposed method.

scholarly journals Terrestrial Laser Scanning for the Detection of Coarse Grain Size Movement in a Mountain Riverbed

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2199 ◽  
Author(s):  
Walicka ◽  
Jóźków ◽  
Kasprzak ◽  
Borkowski
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Horizontal Displacement ◽  
Mountain Stream ◽  
Limited Information ◽  
Fluvial Transport ◽  
Digital Elevation ◽  
Load Transport ◽  
Elevation Model

Fluvial transport is a natural process that shapes riverbeds and the surrounding terrain surface, particularly in mountainous areas. Since the traditional techniques used for fluvial transport investigation provide only limited information about the bed load transport, recently, laser scanning technology has been increasingly incorporated into research to investigate this issue in depth. In this study, a terrestrial laser scanning technique was used to investigate the transport of individual boulders. The measurements were carried out annually from 2011 to 2016 on the Łomniczka River, which is a medium-sized mountain stream. The main goal of this research was to detect and determine displacements of the biggest particles in the mountain riverbed. The methodology was divided into two steps. First, the change zones were detected using two strategies. The first strategy was based on differential digital elevation model (DEM) creation and the second involved the calculation of differences between point clouds instead of DEMs. The experiments show that the second strategy was more efficient. In the second step, the displacements of the boulders were determined based on the detected areas of change. Using the proposed methodology, displacements for individual stones in each year were determined. Most of the changes took place in 2012–2014, which correlates well with the hydrological observations. During the six-year period, movements of individual particles with diameters less than 0.8 m were observed. Maximal displacements in the observed period reached 3 m. Therefore, it is possible to determine both vertical and horizontal displacement in the riverbed using multitemporal TLS.

scholarly journals Fusion of high resolution remote sensing images and terrestrial laser scanning for improved biomass estimation of maize

2014 ◽  
Vol XL-7 ◽  
pp. 101-108 ◽  
Author(s):  
C. Hütt ◽  
H. Schiedung ◽  
N. Tilly ◽  
G. Bareth
Keyword(s):  
High Resolution ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Satellite System ◽  
Biomass Estimation ◽  
Digital Elevation ◽  
Elevation Model ◽  
In The Beginning

In this study, images from the satellite system WorldView-2 in combination with terrestrial laser scanning (TLS) over a maize field in Germany are investigated. Simultaneously to the measurements a biomass field campaigns was carried out. From the point clouds of the terrestrial laser scanning campaigns crop surface models (CSM) from each scanning date were calculate to model plant growth over time. These results were resampled to match the spatial resolution of the WorldView-2 images, which had to orthorectified using a high resolution digital elevation model and atmosphere corrected using the ATCOR Software package. A high direct correlation of the NDVI calculated from the WorldView-2 sensor and the dry biomass was found in the beginning of June. At the same date, the heights from laser scanning can also explain a certain amount of the biomass variation (<i>r</i><sup>2</sup> = 0.6). By combining the NDVI from WorldView-2 and the height from the laser scanner with a linear model, the R2 reaches higher values of 0.86. To further understand the relationship between CSM derived crop heights and reflection indices, a comparison on a pixel basis was performed. Interestingly, the correlation of the NDVI and the crop height is rather low at the beginning of June (<i>r</i><sup>2</sup> = 0,4, <i>n</i> = 1857) and increases significantly (<i>R</i><sup>2</sup> = 0,79, <i>N</i> = 1857) at a later stage.

Development on Filtering Algorithms of Airborne LiDAR Point Clouds

2012 ◽  
Vol 226-228 ◽  
pp. 1892-1898
Author(s):  
Jian Qing Shi ◽  
Ting Chen Jiang ◽  
Ming Lian Jiao
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Filtering Algorithms ◽  
Filtering Algorithm ◽  
Digital Elevation ◽  
City Model ◽  
Elevation Model

Airborne LiDAR is a new kind of surveying technology of remote sensing which developed rapidly during recent years. Raw laser scanning point clouds data include terrain points, building points, vegetation points, outlier points, etc.. In order to generate digital elevation model (DEM) and three-dimensional city model,these point clouds data must be filtered. Mathematical morphology based filtering algorithm, slope based filtering algorithm, TIN based filtering algorithm, moving surface based filtering algorithm, scanning lines based filtering algorithm and so on several representative filtering algorithms for LiDAR point clouds data have been introduced and discussed and contrasted in this paper. Based on these algorithms summarize the studying progresss about the filtering algorithm of airborne LiDAR point clouds data in home and abroad. In the end, the paper gives an expectation which will provides a reference for the following relative study.

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

2019 ◽  
Vol 11 (5) ◽  
pp. 586 ◽  
Author(s):  
Samira Nourbakhshbeidokhti ◽  
Alicia Kinoshita ◽  
Anne Chin ◽  
Joan Florsheim
Keyword(s):  
Laser Scanning ◽  
Point Clouds ◽  
Multiple Model ◽  
Stream Channels ◽  
Change Analysis ◽  
Volumetric Change ◽  
Analytic Methods ◽  
Digital Elevation ◽  
Elevation Data ◽  
Elevation Model

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.

scholarly journals VO-SMOG: A VERSATILE, SMOOTH SEGMENT-BASED GROUND FILTER FOR POINT CLOUDS VIA MULTI-SCALE VOXELIZATION

2021 ◽  
Vol VIII-4/W2-2021 ◽  
pp. 59-66
Author(s):  
E. Che ◽  
A. Senogles ◽  
M. J. Olsen
Keyword(s):  
Laser Scanning ◽  
Large Scale ◽  
Mean Squared Error ◽  
Point Clouds ◽  
Process Data ◽  
Multi Scale ◽  
Digital Elevation ◽  
Real World Datasets ◽  
Aircraft System ◽  
Elevation Model

Abstract. Point clouds acquired by light detection and ranging (lidar) and photogrammetry technology (e.g., structure from motion/multi-view stereo-SfM/MVS) are widely used for various applications such topographic mapping due to their high resolution and accuracy. To generate a digital elevation model (DEM) or extract other features in the data, the ground points and non-ground points usually need to be separated first. This process, called ground filtering, can be tedious and time consuming as it requires substantial manual effort for high quality results. Although many have developed automated ground filtering algorithms, very few have the versatility to process data acquired from different scenes and systems. In this paper, we propose a versatile ground filter based on multi-scale voxelization and smooth segments, named Vo-SmoG. The proposed method introduces a novel voxelization approach, followed by isolated voxel filtering, lowest point filtering, local smooth filtering, and ground clustering. The result of the Vo-SmoG ground filtering is a classified point cloud. The effectiveness and efficiency of our method are demonstrated qualitatively and quantitatively. The quantitative evaluation consists of both point-wise and grid-wise comparisons. The recall, precision, and F1-score are over 97% in terms of classification while the root mean squared error (RMSE) of the DEM is within 0.1 m, which is on par with the reported vertical accuracy of the tested data. We further demonstrate the versatility of the Vo-SmoG via large-scale, real-world datasets collected from different environments with mobile laser scanning, airborne laser scanning, terrestrial laser scanning, uncrewed aircraft system (UAS)-SfM, and UAS-lidar.

scholarly journals Combination of UAV and terrestrial photogrammetry to assess rapid glacier evolution and map glacier hazards

2018 ◽  
Vol 18 (4) ◽  
pp. 1055-1071 ◽  
Author(s):  
Davide Fugazza ◽  
Marco Scaioni ◽  
Manuel Corti ◽  
Carlo D'Agata ◽  
Roberto Sergio Azzoni ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Point Clouds ◽  
Data Sets ◽  
Survey Techniques ◽  
Digital Elevation ◽  
Standard Tool ◽  
Aerial Vehicle ◽  
Close Range ◽  
Elevation Model ◽  
Thinning Rate

Abstract. Tourists and hikers visiting glaciers all year round face hazards such as sudden terminus collapses, typical of such a dynamically evolving environment. In this study, we analyzed the potential of different survey techniques to analyze hazards of the Forni Glacier, an important geosite located in Stelvio Park (Italian Alps). We carried out surveys in the 2016 ablation season and compared point clouds generated from an unmanned aerial vehicle (UAV) survey, close-range photogrammetry and terrestrial laser scanning (TLS). To investigate the evolution of glacier hazards and evaluate the glacier thinning rate, we also used UAV data collected in 2014 and a digital elevation model (DEM) created from an aerial photogrammetric survey of 2007. We found that the integration between terrestrial and UAV photogrammetry is ideal for mapping hazards related to the glacier collapse, while TLS is affected by occlusions and is logistically complex in glacial terrain. Photogrammetric techniques can therefore replace TLS for glacier studies and UAV-based DEMs hold potential for becoming a standard tool in the investigation of glacier thickness changes. Based on our data sets, an increase in the size of collapses was found over the study period, and the glacier thinning rates went from 4.55 ± 0.24 m a−1 between 2007 and 2014 to 5.20 ± 1.11 m a−1 between 2014 and 2016.

scholarly journals Linear-Based Incremental Co-Registration of MLS and Photogrammetric Point Clouds

2021 ◽  
Vol 13 (11) ◽  
pp. 2195
Author(s):  
Shiming Li ◽  
Xuming Ge ◽  
Shengfu Li ◽  
Bo Xu ◽  
Zhendong Wang
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Registration Method ◽  
Cloud Data ◽  
Linear Feature ◽  
Data Registration ◽  
Source Point ◽  
Urban Remote Sensing ◽  
Single Data

Today, mobile laser scanning and oblique photogrammetry are two standard urban remote sensing acquisition methods, and the cross-source point-cloud data obtained using these methods have significant differences and complementarity. Accurate co-registration can make up for the limitations of a single data source, but many existing registration methods face critical challenges. Therefore, in this paper, we propose a systematic incremental registration method that can successfully register MLS and photogrammetric point clouds in the presence of a large number of missing data, large variations in point density, and scale differences. The robustness of this method is due to its elimination of noise in the extracted linear features and its 2D incremental registration strategy. There are three main contributions of our work: (1) the development of an end-to-end automatic cross-source point-cloud registration method; (2) a way to effectively extract the linear feature and restore the scale; and (3) an incremental registration strategy that simplifies the complex registration process. The experimental results show that this method can successfully achieve cross-source data registration, while other methods have difficulty obtaining satisfactory registration results efficiently. Moreover, this method can be extended to more point-cloud sources.

scholarly journals Geomorphometric analysis of cave ceiling channels mapped with 3D terrestrial laser scanning

2016 ◽  
Author(s):  
Michal Gallay ◽  
Zdenko Hochmuth ◽  
Ján Kaňuk ◽  
Jaroslav Hofierka
Keyword(s):  
Laser Scanning ◽  
Methodological Approach ◽  
Three Dimensional ◽  
Terrestrial Laser Scanning ◽  
Scalar Fields ◽  
Complex Environments ◽  
Digital Elevation ◽  
Unique Manner ◽  
Elevation Model ◽  
Different Levels

Abstract. The change of hydrological conditions during the evolution of caves in carbonate rocks often results in a complex subterranean geomorphology which comprises specific landforms such as ceiling channels, anastomosing half tubes, or speleothems organised vertically in different levels. Studying such complex environments traditionally requires tedious mapping, however, this is being replaced with terrestrial laser scanning technology. Laser scanning overcomes the problem of reaching high ceilings providing new options to map underground landscapes with unprecedented level of detail and accuracy. The acquired point cloud can be handled conveniently with dedicated software, but applying traditional geomorphometry to analyse the cave surface is limited. This is because geomorphometry has been focused on parameterisation and analysis of surficial terrain. The theoretical and methodological concept has been based on two-dimensional scalar fields which is sufficient for most cases of the surficial terrain. The terrain surface is modelled with a bivariate function of altitude (elevation) and represented by a raster digital elevation model. However, the cave is a three-dimensional entity therefore a different approach is required for geomorphometric analysis. In this paper, we demonstrate the benefits of high resolution cave mapping and 3-D modelling to better understand the palaeohydrography of the Domica cave in Slovakia. This methodological approach adopted traditional geomorphometric methods in a unique manner and also new methods used in 3D computer graphics which can be applied to study other 3-D geomorphological forms

scholarly journals ANALYSIS OF INFLUENCE OF TERRAIN RELIEF ROUGHNESS ON DEM ACCURACY GENERATED FROM LIDAR IN THE CZECH REPUBLIC TERRITORY

2016 ◽  
Vol XLI-B4 ◽  
pp. 25-30 ◽  
Author(s):  
M. Hubacek ◽  
V. Kovarik ◽  
V. Kratochvil
Keyword(s):  
Czech Republic ◽  
Laser Scanning ◽  
Vegetation Coverage ◽  
The Czech Republic ◽  
Digital Elevation ◽  
Lower Accuracy ◽  
Check Points ◽  
Elevation Data ◽  
Dem Accuracy ◽  
Elevation Model

Digital elevation models are today a common part of geographic information systems and derived applications. The way of their creation is varied. It depends on the extent of area, required accuracy, delivery time, financial resources and technologies available. The first model covering the whole territory of the Czech Republic was created already in the early 1980's. Currently, the 5th DEM generation is being finished. Data collection for this model was realized using the airborne laser scanning which allowed creating the DEM of a new generation having the precision up to a decimetre. Model of such a precision expands the possibilities of employing the DEM and it also offers new opportunities for the use of elevation data especially in a domain of modelling the phenomena dependent on highly accurate data. The examples are precise modelling of hydrological phenomena, studying micro-relief objects, modelling the vehicle movement, detecting and describing historical changes of a landscape, designing constructions etc. <br><br> Due to a nature of the technology used for collecting data and generating DEM, it is assumed that the resulting model achieves lower accuracy in areas covered by vegetation and in built-up areas. Therefore the verification of model accuracy was carried out in five selected areas in Moravia. The network of check points was established using a total station in each area. To determine the reference heights of check points, the known geodetic points whose heights were defined using levelling were used. Up to several thousands of points were surveyed in each area. Individual points were selected according to a different configuration of relief, different surface types, and different vegetation coverage. The sets of deviations were obtained by comparing the DEM 5G heights with reference heights which was followed by verification of tested elevation model. Results of the analysis showed that the model reaches generally higher precision than the declared one in majority of areas. This applies in particular to areas covered by vegetation. By contrast, the larger deviations occurred in relation to the slope of the terrain, in particular in the micro-relief objects. The results are presented in this article.

scholarly journals CREATING DIGITAL ELEVATION MODEL USING A MOBILE DEVICE

2017 ◽  
Vol IV-4/W4 ◽  
pp. 203-207 ◽  
Author(s):  
A. İ. Durmaz
Keyword(s):  
Mobile Devices ◽  
Digital Elevation Model ◽  
Mobile Device ◽  
Point Clouds ◽  
Lidar Data ◽  
Government Agencies ◽  
Gps Data ◽  
Digital Elevation ◽  
The World ◽  
Elevation Model

DEM (Digital Elevation Models) is the best way to interpret topography on the ground. In recent years, lidar technology allows to create more accurate elevation models. However, the problem is this technology is not common all over the world. Also if Lidar data are not provided by government agencies freely, people have to pay lots of money to reach these point clouds. In this article, we will discuss how we can create digital elevation model from less accurate mobile devices’ GPS data. Moreover, we will evaluate these data on the same mobile device which we collected data to reduce cost of this modeling.

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