Presenting a morphological based approach for filtering the point cloud to extract the digital terrain model

2018 ◽  
Vol 6 (3) ◽  
pp. 75-99
Author(s):  
Behnaz Bigdeli ◽  
Hamed Amini Amirkolaee Amini Amirkolaee ◽  
Parham Pahlavani ◽  
◽  
◽  
...  
Keyword(s):  
Point Cloud ◽  
Digital Terrain Model ◽  
Terrain Model ◽  
Digital Terrain

scholarly journals Modeling Streamflow and Sediment Loads with a Photogrammetrically Derived UAS Digital Terrain Model: Empirical Evaluation from a Fluvial Aggregate Excavation Operation

Drones ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 20
Author(s):  
Joseph P. Hupy ◽  
Cyril O. Wilson
Keyword(s):  
Soil Erosion ◽  
Point Cloud ◽  
Empirical Evaluation ◽  
Digital Terrain Model ◽  
Surface Flow ◽  
Sediment Loading ◽  
Terrain Model ◽  
Digital Terrain ◽  
Statistical Measures ◽  
Geospatial Datasets

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.

scholarly journals ASSESSMENT OF THE QUALITY OF DIGITAL TERRAIN MODEL PRODUCED FROM UNMANNED AERIAL SYSTEM IMAGERY

2016 ◽  
Vol XLI-B1 ◽  
pp. 893-899
Author(s):  
M. Kosmatin Fras ◽  
A. Kerin ◽  
M. Mesarič ◽  
V. Peterman ◽  
D. Grigillo
Keyword(s):  
Quality Assessment ◽  
Point Cloud ◽  
Digital Terrain Model ◽  
Quality Parameter ◽  
Unmanned Aerial System ◽  
Test Field ◽  
Absolute Deviation ◽  
Terrain Model ◽  
Digital Terrain

Production of digital terrain model (DTM) is one of the most usual tasks when processing photogrammetric point cloud generated from Unmanned Aerial System (UAS) imagery. The quality of the DTM produced in this way depends on different factors: the quality of imagery, image orientation and camera calibration, point cloud filtering, interpolation methods etc. However, the assessment of the real quality of DTM is very important for its further use and applications. In this paper we first describe the main steps of UAS imagery acquisition and processing based on practical test field survey and data. The main focus of this paper is to present the approach to DTM quality assessment and to give a practical example on the test field data. For data processing and DTM quality assessment presented in this paper mainly the in-house developed computer programs have been used. The quality of DTM comprises its accuracy, density, and completeness. Different accuracy measures like RMSE, median, normalized median absolute deviation and their confidence interval, quantiles are computed. The completeness of the DTM is very often overlooked quality parameter, but when DTM is produced from the point cloud this should not be neglected as some areas might be very sparsely covered by points. The original density is presented with density plot or map. The completeness is presented by the map of point density and the map of distances between grid points and terrain points. The results in the test area show great potential of the DTM produced from UAS imagery, in the sense of detailed representation of the terrain as well as good height accuracy.

scholarly journals Presenting a Morphological Based Approach for Filtering The Point Cloud to Extract the Digital Terrain Model

2019 ◽  
Vol 6 (4) ◽  
pp. 73-96
Author(s):  
Parham Pahlavani ◽  
Hamid Reza Sahraiian ◽  
Behnaz Bigdeli ◽  
◽  
◽  
...  
Keyword(s):  
Point Cloud ◽  
Digital Terrain Model ◽  
Terrain Model ◽  
Digital Terrain

scholarly journals Reduction Method for Mobile Laser Scanning Data

2018 ◽  
Vol 7 (7) ◽  
pp. 285 ◽  
Author(s):  
Wioleta Błaszczak-Bąk ◽  
Zoltan Koppanyi ◽  
Charles Toth
Keyword(s):  
Data Reduction ◽  
Point Cloud ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
New Approach ◽  
Terrain Model ◽  
Digital Terrain ◽  
Airborne Laser ◽  
Short Time ◽  
Mls Method

Mobile Laser Scanning (MLS) technology acquires a huge volume of data in a very short time. In many cases, it is reasonable to reduce the size of the dataset with eliminating points in such a way that the datasets, after reduction, meet specific optimization criteria. Various methods exist to decrease the size of point cloud, such as raw data reduction, Digital Terrain Model (DTM) generalization or generation of regular grid. These methods have been successfully applied on data captured from Airborne Laser Scanning (ALS) and Terrestrial Laser Scanning (TLS), however, they have not been fully analyzed on data captured by an MLS system. The paper presents our new approach, called the Optimum Single MLS Dataset method (OptD-single-MLS), which is an algorithm for MLS data reduction. The tests were carried out in two variants: (1) for raw sensory measurements and (2) for a georeferenced 3D point cloud. We found that the OptD-single-MLS method provides a good solution in both variants; therefore, the choice of the reduction variant depends only on the user.

scholarly journals BADANIE MOŻLIWOŚCI WYKORZYSTANIA ZOBRAZOWAŃ DYNAMICZNYCH (WIDEO) Z NISKIEGO PUŁAPU LOTNICZEGO (BSP) DO OPRACOWAŃ FOTOGRAMETRYCZNYCH

1970 ◽  
pp. 53-64
Author(s):  
ADAM MŁYNARCZYK ◽  
SŁAWOMIR KRÓLEWICZ ◽  
PAWEŁ RUTKOWSKI
Keyword(s):  
High Altitude ◽  
Unmanned Aerial Vehicles ◽  
Point Cloud ◽  
Digital Terrain Model ◽  
Image Data ◽  
Terrain Model ◽  
Digital Terrain ◽  
Aerial Vehicles ◽  
The Creation ◽  
Recorded Image

The use of unmanned aerial vehicles is becoming more and more popular for making high-altitude and orthophotomap models. In this process, series of images are taken at specific intervals, usually lasting several seconds. This article demonstrates the ability to make models and orthophotomaps from dynamic images – video recorded from UAV. The best mutual coverage of photographs was indicated (95–96%) and the photogrammetric process for joining images was presented, through the creation of a point cloud to obtain a digital terrain model and the orotfotomap. The data was processed in 150 different variants and the usefulness of this method was demonstrated. Problems and errors that may occur during the processing of recorded image data are also described.

scholarly journals What should a bare earth digital terrain model (DTM) portray?

2018 ◽  
Author(s):  
Peter L Guth
Keyword(s):  
Point Cloud ◽  
Western Europe ◽  
Digital Terrain Model ◽  
Point Clouds ◽  
Noise Removal ◽  
Free Software ◽  
Surface Generation ◽  
Classification Algorithms ◽  
Terrain Model ◽  
Digital Terrain

National mapping agencies in North American and western Europe have released free lidar point clouds with densities of 2-23 points/m², and derived terrain grids. Geomorphometric processing uses a bare earth digital terrain model (DTM), which can be acquired from mapping agencies or created from the point cloud to better control its characteristics. Free software provides tools for noise removal, ground classification, surface generation, void filling, surface smoothing, and hydraulic conditioning. Tests with three ground classification algorithms, and four surface generation algorithms show that they produced very similar results. The main issues for geomorphometric operations on DTMs involve whether the highest and lowest ground points should be in the DTM if they are not on a grid node, how water, buildings, and roads should be treated, if using a DTM of lower resolution will effectively filter out noise and allow much faster processing, and if lower resolution DTMs should be created directly from the point cloud or by processing a higher resolution DTM.

scholarly journals What should a bare earth digital terrain model (DTM) portray?

2018 ◽  
Author(s):  
Peter L Guth
Keyword(s):  
Point Cloud ◽  
Western Europe ◽  
Digital Terrain Model ◽  
Point Clouds ◽  
Noise Removal ◽  
Free Software ◽  
Surface Generation ◽  
Classification Algorithms ◽  
Terrain Model ◽  
Digital Terrain

National mapping agencies in North American and western Europe have released free lidar point clouds with densities of 2-23 points/m², and derived terrain grids. Geomorphometric processing uses a bare earth digital terrain model (DTM), which can be acquired from mapping agencies or created from the point cloud to better control its characteristics. Free software provides tools for noise removal, ground classification, surface generation, void filling, surface smoothing, and hydraulic conditioning. Tests with three ground classification algorithms, and four surface generation algorithms show that they produced very similar results. The main issues for geomorphometric operations on DTMs involve whether the highest and lowest ground points should be in the DTM if they are not on a grid node, how water, buildings, and roads should be treated, if using a DTM of lower resolution will effectively filter out noise and allow much faster processing, and if lower resolution DTMs should be created directly from the point cloud or by processing a higher resolution DTM.

scholarly journals Presenting a morphological based approach for filtering the point cloud to extract the digital terrain model

2018 ◽  
Vol 6 (3) ◽  
pp. 67-91
Author(s):  
Behnaz Bigdeli ◽  
Hamed Amini Amirkolaee ◽  
Parham Pahlavani ◽  
◽  
◽  
...  
Keyword(s):  
Point Cloud ◽  
Digital Terrain Model ◽  
Terrain Model ◽  
Digital Terrain

scholarly journals Effects of Structure from Motion Data Density, Interpolation Method and Grid Size on Micro Topography Digital Terrain Model Accuracy

2019 ◽  
Author(s):  
Francisco Agüera-Vega ◽  
Marta Agüera-Puntas ◽  
Francesco Mancini ◽  
Patricio Martínez-Carricondo ◽  
Fernando Carvajal-Ramírez
Keyword(s):  
Structure From Motion ◽  
Point Cloud ◽  
Interpolation Method ◽  
Digital Terrain Model ◽  
Grid Size ◽  
Ground Sample ◽  
Terrain Model ◽  
Digital Terrain ◽  
Cloud Density ◽  
Sample Distance

The objective of this study is to evaluate the effects of the 3D point cloud density derived from unmanned aerial vehicle (UAV) photogrammetry and structure from motion (SfM) and multi-view stereopsis (MVS) techniques, the interpolation method for generating a digital terrain model (DTM), and the resolution (grid size) of the derived DTM on the accuracy of estimated heights in small areas, where a very accurate high spatial resolution is required. A UAV-photogrammetry project was carried out on a bare soil of 13 × 13 m with a rotatory wing UAV at 10 m flight altitude (equivalent ground sample distance = 0.4 cm). The 3D point cloud was derived, and five sample replications representing 1, 2, 3, 4, 5, 10, 15, 20, 30, 40, 50, 60, 70, 80 and 90% of the original cloud were extracted to analyze the effect of cloud density on DTM accuracy. For each of these samples, DTMs were derived using four different interpolation methods (Inverse Distance Weighted (IDW), Multiquadric Radial Basis Function (MRBF), Kriging (KR), and Triangulation with Linear Interpolation (TLI)) and 15 DTM grid size (GS) values (20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0.67, 0.5, and 0.4 cm). Then, 675 DTMs were analyzed. The results showed, for each interpolation method and each density, an optimal GS value (most of the cases equal to 1 cm) for which the Root Mean Square Error (RMSE) is minimum. IDW was the interpolator which yielded best accuracies for all combination of densities and GS. Its RMSE, considering the raw cloud, was 1.054 cm. The RMSE increased 3% when a point cloud with 80% extracted from the raw cloud was used to generate the DTM. When the point cloud included the 40% of the raw cloud, RMSE increased 5%. For densities lower than 15%, RMSE increased exponentially (45% for 1% of raw cloud). The grid size minimizing RMSE for densities of 20% or higher was 1 cm, which represents 2.5 times the ground sample distance of the pictures used for developing the photogrammetry project.

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