Alternative Methods for Developing and Assessing the Accuracy of UAV-Derived DEMs

2019 ◽  
pp. 249-270
Author(s):  
Dion J. Wiseman ◽  
Jurjen van der Sluijs

Digital terrain models are invaluable datasets that are frequently used for visualizing, modeling, and analyzing Earth surface processes. Accurate models covering local scale landscape features are often very expensive and have poor temporal resolution. This research investigates the utility of UAV acquired imagery for generating high resolution terrain models and provides a detailed accuracy assessment according to recommended protocols. High resolution UAV imagery was acquired over a localized dune complex in southwestern Manitoba, Canada and two alternative workflows were evaluated for extracting point clouds. UAV-derived data points were then compared to reference data sets acquired using mapping grade GPS receivers and a total station. Results indicated that the UAV imagery was capable of producing dense point clouds and high resolution terrain models with mean errors as low as -0.15 m and RMSE values of 0.42 m depending on the resolution of the image dataset and workflow employed.

2019 ◽  
pp. 1175-1196
Author(s):  
Dion J. Wiseman ◽  
Jurjen van der Sluijs

Digital terrain models are invaluable datasets that are frequently used for visualizing, modeling, and analyzing Earth surface processes. Accurate models covering local scale landscape features are often very expensive and have poor temporal resolution. This research investigates the utility of UAV acquired imagery for generating high resolution terrain models and provides a detailed accuracy assessment according to recommended protocols. High resolution UAV imagery was acquired over a localized dune complex in southwestern Manitoba, Canada and two alternative workflows were evaluated for extracting point clouds. UAV-derived data points were then compared to reference data sets acquired using mapping grade GPS receivers and a total station. Results indicated that the UAV imagery was capable of producing dense point clouds and high resolution terrain models with mean errors as low as -0.15 m and RMSE values of 0.42 m depending on the resolution of the image dataset and workflow employed.


2015 ◽  
Vol 6 (3) ◽  
pp. 58-77 ◽  
Author(s):  
Dion J. Wiseman ◽  
Jurjen van der Sluijs

Digital terrain models are invaluable datasets that are frequently used for visualizing, modeling, and analyzing Earth surface processes. Accurate models covering local scale landscape features are often very expensive and have poor temporal resolution. This research investigates the utility of UAV acquired imagery for generating high resolution terrain models and provides a detailed accuracy assessment according to recommended protocols. High resolution UAV imagery was acquired over a localized dune complex in southwestern Manitoba, Canada and two alternative workflows were evaluated for extracting point clouds. UAV-derived data points were then compared to reference data sets acquired using mapping grade GPS receivers and a total station. Results indicated that the UAV imagery was capable of producing dense point clouds and high resolution terrain models with mean errors as low as -0.15 m and RMSE values of 0.42 m depending on the resolution of the image dataset and workflow employed.


Author(s):  
L. Gézero ◽  
C. Antunes

In the last few years, LiDAR sensors installed in terrestrial vehicles have been revealed as an efficient method to collect very dense 3D georeferenced information. The possibility of creating very dense point clouds representing the surface surrounding the sensor, at a given moment, in a very fast, detailed and easy way, shows the potential of this technology to be used for cartography and digital terrain models production in large scale. However, there are still some limitations associated with the use of this technology. When several acquisitions of the same area with the same device, are made, differences between the clouds can be observed. The range of that differences can go from few centimetres to some several tens of centimetres, mainly in urban and high vegetation areas where the occultation of the GNSS system introduces a degradation of the georeferenced trajectory. Along this article a different method point cloud registration is proposed. In addition to the efficiency and speed of execution, the main advantages of the method are related to the fact that the adjustment is continuously made over the trajectory, based on the GPS time. The process is fully automatic and only information recorded in the standard LAS files is used, without the need for any auxiliary information, in particular regarding the trajectory.


Drones ◽  
2019 ◽  
Vol 3 (2) ◽  
pp. 35 ◽  
Author(s):  
Jonathan P. Resop ◽  
Laura Lehmann ◽  
W. Cully Hession

Lidar remote sensing has been used to survey stream channel and floodplain topography for decades. However, traditional platforms, such as aerial laser scanning (ALS) from an airplane, have limitations including flight altitude and scan angle that prevent the scanner from collecting a complete survey of the riverscape. Drone laser scanning (DLS) or unmanned aerial vehicle (UAV)-based lidar offer ways to scan riverscapes with many potential advantages over ALS. We compared point clouds and lidar data products generated with both DLS and ALS for a small gravel-bed stream, Stroubles Creek, located in Blacksburg, VA. Lidar data points were classified as ground and vegetation, and then rasterized to produce digital terrain models (DTMs) representing the topography and canopy height models (CHMs) representing the vegetation. The results highlighted that the lower-altitude, higher-resolution DLS data were more capable than ALS of providing details of the channel profile as well as detecting small vegetation on the floodplain. The greater detail gained with DLS will provide fluvial researchers with better estimates of the physical properties of riverscape topography and vegetation.


2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Andrey Medvedev ◽  
Arseny Kudikov ◽  
Natalia Telnova ◽  
Olga Tutubalina ◽  
Elena Golubeva ◽  
...  

<p><strong>Abstract.</strong> The algorithms for quantitative estimates of various structural and functional parameters of forest ecosystems, particularly boreal forests, on high resolution remote sensing data are actively developing since the mid-2000s. For monitoring of forest ecosystems located at the Northern limit of distribution, effective not only lidar data but also the optical data obtained by unmanned aerial vehicles (UAV’s) with ultra-low altitude photography and derived products resulting from modern algorithms for the photogrammetric processing.</p><p>High-detail remote sensing from UAV’s is a key level of monitoring of Northern forests at a large-scale level, ensuring the correct transition from sub - satellite ground-based studies to thematic products obtained from multi-time Hyper-and multispectral data of medium and relatively high resolution (MODIS, LANDSAT, Sentinel-2).</p><p>When planning and conducting specific case studies based on UAV data, special attention should be paid to the justification of the survey methodology. In particular, the choice of a strictly defined high-altitude echelon of the survey determines the recognition of the objects of study and the possibility of reliable determination of its properties and features. To study the parameters of forest ecosystems at the level of individual trees and at the level of forest plantations, we selected two different-height echelons of survey from ultra-low altitudes: from 50 m, which allowed us to obtain ultra-high-detailed data for each sample area provided by detailed ground-based studies with sub-tree account, and from 100 m-to obtain derived characteristics of forest communities within the area equivalent to 3 pixels of thematic MODIS products with a spatial resolution of 250 m. The data of optical survey with UAV were obtained in July 2018 for 22 plots located in the central part of the Kola Peninsula and representative of different types of North taiga stands and their dynamics under climate change.</p><p>At the stage of preprocessing images were obtained dense point clouds, characterizing both vertical and horizontal structure of stands. Digital terrain and terrain models and tree canopy models were obtained after cloud filtering and classification. Algorithms of automated segmentation and classification have been developed and tested to obtain such characteristics of stands as the height of individual trees, the area of crown projections, the projective cover of the tree-shrub layer. The obtained characteristics are aggregated by cells of a regular network with the dimension corresponding to the spatial resolution of Sentinel-2 and Landsat-8 data.</p><p>The main results of the works are digital spatial datasets for 22 sample plots: raw data with very high resolution imagery (optical images with very high resolution, dense point clouds, RGB-orthophoto) and create based on a thematic derivative products (digital terrain model, topography, tree canopy cover; map of the heights and projections of the crowns of trees, percent cover of tree and shrub vegetation).</p>


Author(s):  
L. Gézero ◽  
C. Antunes

The digital terrain models (DTM) assume an essential role in all types of road maintenance, water supply and sanitation projects. The demand of such information is more significant in developing countries, where the lack of infrastructures is higher. In recent years, the use of Mobile LiDAR Systems (MLS) proved to be a very efficient technique in the acquisition of precise and dense point clouds. These point clouds can be a solution to obtain the data for the production of DTM in remote areas, due mainly to the safety, precision, speed of acquisition and the detail of the information gathered. However, the point clouds filtering and algorithms to separate “terrain points” from “no terrain points”, quickly and consistently, remain a challenge that has caught the interest of researchers. This work presents a method to create the DTM from point clouds collected by MLS. The method is based in two interactive steps. The first step of the process allows reducing the cloud point to a set of points that represent the terrain’s shape, being the distance between points inversely proportional to the terrain variation. The second step is based on the Delaunay triangulation of the points resulting from the first step. The achieved results encourage a wider use of this technology as a solution for large scale DTM production in remote areas.


2020 ◽  
Author(s):  
Dick M. A. Schaap ◽  
Thierry Schmitt

&lt;p&gt;Access to marine data is a key issue for the &lt;strong&gt;EU&lt;/strong&gt; &lt;strong&gt;Marine Strategy Framework Directive&lt;/strong&gt; and the &lt;strong&gt;EU&lt;/strong&gt; &lt;strong&gt;Marine Knowledge 2020 agenda &lt;/strong&gt;and includes the &lt;strong&gt;European Marine Observation and Data Network (EMODnet)&lt;/strong&gt; initiative. EMODnet aims at assembling European marine data, data products and metadata from diverse sources in a uniform way.&lt;/p&gt;&lt;p&gt;The EMODnet Bathymetry project is active since 2008 and has developed Digital Terrain Models (DTM) for the European seas, which are published at a regular interval, each time improving quality and precision, and expanding functionalities for viewing, using, and downloading. The DTMs are produced from survey and aggregated data sets that are referenced with metadata adopting the SeaDataNet Catalogue services. SeaDataNet is a network of major oceanographic data centres around the European seas that manage, operate and further develop a pan-European infrastructure for marine and ocean data management. The latest EMODnet Bathymetry DTM release also includes Satellite Derived Bathymetry and has a grid resolution of 1/16 arcminute (circa 125 meters), covering all European sea regions. Use has been made of circa 9400 gathered survey datasets, composite DTMs and SDB bathymetry. Catalogues and the EMODnet DTM are published at the dedicated EMODnet Bathymetry portal including a versatile DTM viewing and downloading service.&amp;#160;&amp;#160;&lt;/p&gt;&lt;p&gt;As part of the expansion and innovation, more focus has been directed towards bathymetry for near coastal waters and coastal zones. And Satellite Derived Bathymetry data have been produced and included to fill gaps in coverage of the coastal zones. The Bathymetry Viewing and Download service has been upgraded to provide a multi-resolution map and including versatile 3D viewing. Moreover, best-estimates have been determined of the European coastline for a range of tidal levels (HAT, MHW, MSL, Chart Datum, LAT), thereby making use of a tidal model for Europe. In addition, a Quality Index layer has been formulated with indicators derived from the source data and which can be queried in the The Bathymetry Viewing and Download service. Finally, extra functonality has been added to the mechanism for downloading DTM tiles in various formats and special high-resolution DTMs for interesting areas. &amp;#160;&lt;/p&gt;&lt;p&gt;This results in many users visiting the portal, browsing the DTM Viewer, downloading the DTM tiles and making use of the OGC Web services for using the EMODnet Bathymetry in their applications.&lt;/p&gt;&lt;p&gt;The presentation will highlight key details of the EMODnet Bathymetry DTM production process and the Bathymetry portal with its extensive functionality.&lt;/p&gt;


2018 ◽  
Vol 7 (9) ◽  
pp. 342 ◽  
Author(s):  
Adam Salach ◽  
Krzysztof Bakuła ◽  
Magdalena Pilarska ◽  
Wojciech Ostrowski ◽  
Konrad Górski ◽  
...  

In this paper, the results of an experiment about the vertical accuracy of generated digital terrain models were assessed. The created models were based on two techniques: LiDAR and photogrammetry. The data were acquired using an ultralight laser scanner, which was dedicated to Unmanned Aerial Vehicle (UAV) platforms that provide very dense point clouds (180 points per square meter), and an RGB digital camera that collects data at very high resolution (a ground sampling distance of 2 cm). The vertical error of the digital terrain models (DTMs) was evaluated based on the surveying data measured in the field and compared to airborne laser scanning collected with a manned plane. The data were acquired in summer during a corridor flight mission over levees and their surroundings, where various types of land cover were observed. The experiment results showed unequivocally, that the terrain models obtained using LiDAR technology were more accurate. An attempt to assess the accuracy and possibilities of penetration of the point cloud from the image-based approach, whilst referring to various types of land cover, was conducted based on Real Time Kinematic Global Navigation Satellite System (GNSS-RTK) measurements and was compared to archival airborne laser scanning data. The vertical accuracy of DTM was evaluated for uncovered and vegetation areas separately, providing information about the influence of the vegetation height on the results of the bare ground extraction and DTM generation. In uncovered and low vegetation areas (0–20 cm), the vertical accuracies of digital terrain models generated from different data sources were quite similar: for the UAV Laser Scanning (ULS) data, the RMSE was 0.11 m, and for the image-based data collected using the UAV platform, it was 0.14 m, whereas for medium vegetation (higher than 60 cm), the RMSE from these two data sources were 0.11 m and 0.36 m, respectively. A decrease in the accuracy of 0.10 m, for every 20 cm of vegetation height, was observed for photogrammetric data; and such a dependency was not noticed in the case of models created from the ULS data.


2019 ◽  
Vol 7 (1) ◽  
pp. 1-20
Author(s):  
Fotis Giagkas ◽  
Petros Patias ◽  
Charalampos Georgiadis

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.


2019 ◽  
Vol 11 (12) ◽  
pp. 1507 ◽  
Author(s):  
Javier Cardenal ◽  
Tomás Fernández ◽  
José Pérez-García ◽  
José Gómez-López

This paper presents a methodology for measuring road surface deformation due to terrain instability processes. The methodology is based on ultra-high resolution images acquired from unmanned aerial vehicles (UAVs). Flights are georeferenced by means of Structure from Motion (SfM) techniques. Dense point clouds, obtained using the multiple-view stereo (MVS) approach, are used to generate digital surface models (DSM) and high resolution orthophotographs (0.02 m GSD). The methodology has been applied to an unstable area located in La Guardia (Jaen, Southern Spain), where an active landslide was identified. This landslide affected some roads and accesses to a highway at the landslide foot. The detailed road deformation was monitored between 2012 and 2015 by means of eleven UAV flights of ultrahigh resolution covering an area of about 260 m × 90 m. The accuracy of the analysis has been established in 0.02 ± 0.01 m in XY and 0.04 ± 0.02 m in Z. Large deformations in the order of two meters were registered in the total period analyzed that resulted in maximum average rates of 0.62 m/month in the unstable area. Some boundary conditions were considered because of the low required flying height (<50 m above ground level) in order to achieve a suitable image GSD, the fast landslide dynamic, continuous maintenance works on the affected roads and dramatic seasonal vegetation changes throughout the monitoring period. Finally, we have analyzed the relation of displacements to rainfalls in the area, finding a significant correlation between the two variables, as well as two different reactivation episodes.


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