Accuracy Assessment of Digital Elevation Models Using GPS

Farah, Ashraf; Talaat, Ashraf; Farrag, Farrag A.

doi:10.2478/v10018-009-0014-7

Cited by 8 publications

(4 citation statements)

References 4 publications

(4 reference statements)

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“…For instance, [39] stated that the use of total station provided accuracy with an error of approximately 1 cm in horizontal position and about 2 cm in vertical position (elevation). The studies [40,41] used total station ground-truthed data to assess the accuracy of LiDAR, and [42] used it to assess the accuracy of GPS.…”

Section: Discussionmentioning

confidence: 99%

Accuracy of Reconstruction of the Tree Stem Surface Using Terrestrial Close-Range Photogrammetry

2016

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Airborne laser scanning (ALS) allows for extensive coverage, but the accuracy of tree detection and form can be limited. Although terrestrial laser scanning (TLS) can improve on ALS accuracy, it is rather expensive and area coverage is limited. Multi-view stereopsis (MVS) techniques combining computer vision and photogrammetry may offer some of the coverage benefits of ALS and the improved accuracy of TLS; MVS combines computer vision research and automatic analysis of digital images from common commercial digital cameras with various algorithms to reconstruct three-dimensional (3D) objects with realistic shape and appearance. Despite the relative accuracy (relative geometrical distortion) of the reconstructions available in the processing software, the absolute accuracy is uncertain and difficult to evaluate. We evaluated the data collected by a common digital camera through the processing software (Agisoft PhotoScan ©) for photogrammetry by comparing those by direct measurement of the 3D magnetic motion tracker. Our analyses indicated that the error is mostly concentrated in the portions of the tree where visibility is lower, i.e., the bottom and upper parts of the stem. For each reference point from the digitizer we determined how many cameras could view this point. With a greater number of cameras we found increasing accuracy of the measured object space point positions (as expected), with a significant positive change in the trend beyond five cameras; when more than five cameras could view this point, the accuracy began to increase more abruptly, but eight cameras or more provided no increases in accuracy. This method allows for the retrieval of larger datasets from the measurements, which could improve the accuracy of estimates of 3D structure of trees at potentially reduced costs.

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Section: Discussionmentioning

confidence: 99%

Accuracy of Reconstruction of the Tree Stem Surface Using Terrestrial Close-Range Photogrammetry

2016

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“…Walker and Willgoose [45] assessed the accuracy of their Total Station data using error propagation theory and found that uncertainty in position is ∼1 cm and uncertainty in elevation is ∼2 cm. Shrestha et al [46] used traditional surveying techniques to acquire profiles to assess the accuracy of LiDAR; Töyrä et al [47] used Total Station elevation data to assess LiDAR; and Farah et al [48] used Total Station data to assess the accuracy of DEMs derived from GPS. In a number of these studies the Root Mean Squared Error (RMSE) for each dimension and the total RMSE have been used as accuracy metrics.…”

Section: Georeferenced Point Clouds and Reference Datamentioning

confidence: 99%

Assessing the Accuracy of Georeferenced Point Clouds Produced via Multi-View Stereopsis from Unmanned Aerial Vehicle (UAV) Imagery

2012

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Sensor miniaturisation, improved battery technology and the availability of low-cost yet advanced Unmanned Aerial Vehicles (UAV) have provided new opportunities for environmental remote sensing. The UAV provides a platform for close-range aerial photography. Detailed imagery captured from micro-UAV can produce dense point clouds using multi-view stereopsis (MVS) techniques combining photogrammetry and computer vision. This study applies MVS techniques to imagery acquired from a multi-rotor micro-UAV of a natural coastal site in southeastern Tasmania, Australia. A very dense point cloud (<1-3 cm point spacing) is produced in an arbitrary coordinate system using full resolution imagery, whereas other studies usually downsample the original imagery. The point cloud is sparse in areas of complex vegetation and where surfaces have a homogeneous texture. Ground control points collected with Differential Global Positioning System (DGPS) are identified and used for georeferencing via a Helmert transformation. This study compared georeferenced point clouds to a Total Station survey in order to assess and quantify their geometric accuracy. The results indicate that a georeferenced point cloud accurate to 25-40 mm can be obtained from imagery acquired from ∼50 m. UAV-based image capture provides the spatial and temporal resolution required to map and monitor natural landscapes. This paper assesses the accuracy of the generated point clouds based on field survey points. Based on our key findings we conclude that sub-decimetre terrain change (in this case coastal erosion) can be monitored.Remote Sens. 2012, 4 1574

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“…The elevations were collected using two GPS instruments (Topcon Hiper GGD; model Lite Plus) with dual-frequency receivers in a real-time kinematic (RTK) configuration. The application of GPS RTK has proven effective as a fast, precise method to collect reference data for studies that investigate terrain elevation (FARAH et al, 2008;KIZIL & TISOR, 2011). One GPS unit (termed Base) was installed near the center of the study area, and the other (termed Rover) was carried throughout the study area to a maximum distance of 2 km from the Base.…”

Section: Methodsmentioning

confidence: 99%

Quality of a Digital Terrain Model for Santa Catarina State

et al. 2016

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Relief characterization using a digital terrain model (DTM) is widely applied in erosion, soil and vegetation modeling. However, factors, such as acquisition technology and the spatial resolution of the digital model, affect modeling results. The aim of this study was to characterize noises in a DTM of the entire state of Santa Catarina recently made available through the state's Sustainable Economic Development Secretary and to evaluate different methods of interpolation and smoothing of the original 1 m resolution to a new digital model with a spatial resolution of 15 m. Using the SAGA GIS program, spurious data that appeared as peaks and sinks were removed from the digital model. Of five processing procedures, the following three were used for smoothing: a Gaussian filter, a Lee filter, and mesh denoising. The remaining two were for interpolation: nearest-neighbor, and ordinary kriging. Altimetric reference data were collected in the study area of 11,597 km² with two dual-frequency GPS RTK receivers located in the Celso Ramos community in the municipality of Frei Rogério (SC). The root mean square error showed that the documented values of the aerial survey report were consistent with the findings of this study. However, the GPS RTK data showed a difference of 1.07 m compared with the original DTM with 1 m spatial resolution. There were pixels with peaks and sinks in the digital model of the Santa Catarina State.

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Accuracy Assessment of Digital Elevation Models Using GPS

Cited by 8 publications

References 4 publications

Accuracy of Reconstruction of the Tree Stem Surface Using Terrestrial Close-Range Photogrammetry

Accuracy of Reconstruction of the Tree Stem Surface Using Terrestrial Close-Range Photogrammetry

Assessing the Accuracy of Georeferenced Point Clouds Produced via Multi-View Stereopsis from Unmanned Aerial Vehicle (UAV) Imagery

Quality of a Digital Terrain Model for Santa Catarina State

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