scholarly journals CROSS VALIDATION ON THE EQUALITY OF UAV-BASED AND CONTOUR-BASED DEMS

2018 ◽  
Vol XLII-3 ◽  
pp. 1245-1248
Author(s):  
R. Ma ◽  
Z. Xu ◽  
L. Wu ◽  
S. Liu
Keyword(s):  
Flight Control ◽  
Point Clouds ◽  
Time Saving ◽  
Ground Control Points ◽  
Digital Elevation ◽  
Irregular Networks ◽  
Feature Based ◽  
Elevation Model ◽  
Uav Images

Unmanned Aerial Vehicles (UAV) have been widely used for Digital Elevation Model (DEM) generation in geographic applications. This paper proposes a novel framework of generating DEM from UAV images. It starts with the generation of the point clouds by image matching, where the flight control data are used as reference for searching for the corresponding images, leading to a significant time saving. Besides, a set of ground control points (GCP) obtained from field surveying are used to transform the point clouds to the user’s coordinate system. Following that, we use a multi-feature based supervised classification method for discriminating non-ground points from ground ones. In the end, we generate DEM by constructing triangular irregular networks and rasterization. The experiments are conducted in the east of Jilin province in China, which has been suffered from soil erosion for several years. The quality of UAV based DEM (UAV-DEM) is compared with that generated from contour interpolation (Contour-DEM). The comparison shows a higher resolution, as well as higher accuracy of UAV-DEMs, which contains more geographic information. In addition, the RMSE errors of the UAV-DEMs generated from point clouds with and without GCPs are ±0.5 m and ±20 m, respectively.

scholarly journals Quality of Digital Elevation Models obtained from Unmanned Aerial Vehicles for Precision Viticulture

OENO One ◽  
2016 ◽  
Vol 50 (3) ◽  
Author(s):  
Léo Pichon ◽  
Arnaud Ducanchez ◽  
Hélène Fonta ◽  
Bruno Tisseyre
Keyword(s):  
Low Cost ◽  
Wine Industry ◽  
Image Capture ◽  
Digital Elevation ◽  
Elevation Data ◽  
Aerial Vehicle ◽  
Elevation Model ◽  
Uav Images ◽  
Data Acquisition And Processing

<p style="text-align: justify;"><strong>Aims:</strong> This work aims to study the quality of low cost Digital Surface Models (DSMs) obtained with Unmanned Aerial Vehicle (UAV) images and to test whether these DSMs meet common requirements of the wine industry.</p><p style="text-align: justify;"><strong>Methods and results: </strong>Experiments were carried out on a 4-ha vineyard located 10 km north of Beziers (France). The experimental site presents slope and aspect variations representative of mechanised commercial vineyards in Languedoc Roussillon. DSMs were provided by three UAV companies selected for the diversity of their solutions in terms of image capture altitude, type of UAV and image processing software. DSMs were obtained by photogrammetry and correspond to commercial products usually delivered by UAV companies. DSMs from UAV were compared to a reference Digital Elevation Model (DEM) acquired by a laser tachymeter. Four indicators were used to test the quality of DSMs: the mean error and its dispersion in the XY plane and in elevation Z. Results show a good georeferencing of the DSMs (MeanErrorXY&lt;10 cm) and a similar quality in elevation (MeanErrorZ&lt;10 cm) estimation. Results also show that the error in elevation is highly spatially structured. The spatial patterns observed did not depend on the elevation and could be related to algorithms used to compute the DSMs.</p><p style="text-align: justify;"><strong>Conclusion: </strong>Data acquisition and processing methods have an impact on the quality of the DSMs provided by the UAV companies. DSM qualities are good enough to meet commercial vineyard requirements. The tested DSMs fit the requirements to assess field characteristics (elevation, slope, aspects) which may be important for terroir characterisation purposes.</p><p style="text-align: justify;"><strong>Significance and impact of the study:</strong> This study proves that elevation data derived from UAV present an accuracy equivalent to the reference system used in this study. The rapidity, the low cost and the high spatial resolution of these data offer significant opportunities for the development of new services for the wine industry for field characterisation.</p>

scholarly journals Digital elevation model validation with no ground control: application to the topodata dem in Brazil

2014 ◽  
Vol 20 (2) ◽  
pp. 467-479 ◽  
Author(s):  
Laurent Polidori ◽  
Mhamad El Hage ◽  
Márcio De Morisson Valeriano
Keyword(s):  
Digital Elevation Model ◽  
Visual Analysis ◽  
Ground Control ◽  
Ground Control Points ◽  
Geostatistical Approach ◽  
Digital Elevation ◽  
Elevation Model ◽  
Control Application ◽  
Statistical Indicators

Digital Elevation Model (DEM) validation is often carried out by comparing the data with a set of ground control points. However, the quality of a DEM can also be considered in terms of shape realism. Beyond visual analysis, it can be verified that physical and statistical properties of the terrestrial relief are fulfilled. This approach is applied to an extract of Topodata, a DEM obtained by resampling the SRTM DEM over the Brazilian territory with a geostatistical approach. Several statistical indicators are computed, and they show that the quality of Topodata in terms of shape rendering is improved with regards to SRTM.

scholarly journals EVALUATION OF ASTER GDEM V3 USING ICESAT LASER ALTIMETRY

2016 ◽  
Vol XLI-B4 ◽  
pp. 117-124
Author(s):  
C. C. Carabajal ◽  
J.-P. Boy
Keyword(s):  
Thermal Emission ◽  
Ground Control ◽  
Control Points ◽  
Ice Cloud ◽  
Aster Gdem ◽  
Ground Control Points ◽  
Digital Elevation ◽  
Elevation Model ◽  
Globally Distributed

We have used a set of Ground Control Points (GCPs) derived from altimetry measurements from the Ice, Cloud and land Elevation Satellite (ICESat) to evaluate the quality of the 30 m posting ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) Global Digital Elevation Model (GDEM) V3 elevation products produced by NASA/METI for Greenland and Antarctica. These data represent the highest quality globally distributed altimetry measurements that can be used for geodetic ground control, selected by applying rigorous editing criteria, useful at high latitudes, where other topographic control is scarce. Even if large outliers still remain in all ASTER GDEM V3 data for both, Greenland and Antarctica, they are significantly reduced when editing ASTER by number of scenes (N≥5) included in the elevation processing. For 667,354 GCPs in Greenland, differences show a mean of 13.74 m, a median of -6.37 m, with an RMSE of 109.65 m. For Antarctica, 6,976,703 GCPs show a mean of 0.41 m, with a median of -4.66 m, and a 54.85 m RMSE, displaying smaller means, similar medians, and less scatter than GDEM V2. Mean and median differences between ASTER and ICESat are lower than 10 m, and RMSEs lower than 10 m for Greenland, and 20 m for Antarctica when only 9 to 31 scenes are included.

scholarly journals PERFORMANCE EVALUATION OF DIFFERENT GROUND FILTERING ALGORITHMS FOR UAV-BASED POINT CLOUDS

2016 ◽  
Vol XLI-B1 ◽  
pp. 245-251 ◽  
Author(s):  
C. Serifoglu ◽  
O. Gungor ◽  
V. Yilmaz
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
Good Alternative ◽  
Lidar Data ◽  
Filtering Algorithms ◽  
Aerial Photos ◽  
Digital Elevation ◽  
Aerial Vehicle ◽  
Elevation Model ◽  
Uav Images

Digital Elevation Model (DEM) generation is one of the leading application areas in geomatics. Since a DEM represents the bare earth surface, the very first step of generating a DEM is to separate the ground and non-ground points, which is called ground filtering. Once the point cloud is filtered, the ground points are interpolated to generate the DEM. LiDAR (Light Detection and Ranging) point clouds have been used in many applications thanks to their success in representing the objects they belong to. Hence, in the literature, various ground filtering algorithms have been reported to filter the LiDAR data. Since the LiDAR data acquisition is still a costly process, using point clouds generated from the UAV images to produce DEMs is a reasonable alternative. In this study, point clouds with three different densities were generated from the aerial photos taken from a UAV (Unmanned Aerial Vehicle) to examine the effect of point density on filtering performance. The point clouds were then filtered by means of five different ground filtering algorithms as Progressive Morphological 1D (PM1D), Progressive Morphological 2D (PM2D), Maximum Local Slope (MLS), Elevation Threshold with Expand Window (ETEW) and Adaptive TIN (ATIN). The filtering performance of each algorithm was investigated qualitatively and quantitatively. The results indicated that the ATIN and PM2D algorithms showed the best overall ground filtering performances. The MLS and ETEW algorithms were found as the least successful ones. It was concluded that the point clouds generated from the UAVs can be a good alternative for LiDAR data.

scholarly journals Suggestions to Limit Geometric Distortions in the Reconstruction of Linear Coastal Landforms by SfM Photogrammetry with PhotoScan® and MicMac® for UAV Surveys with Restricted GCPs Pattern

Drones ◽  
2018 ◽  
Vol 3 (1) ◽  
pp. 2 ◽  
Author(s):  
Marion Jaud ◽  
Sophie Passot ◽  
Pascal Allemand ◽  
Nicolas Le Dantec ◽  
Philippe Grandjean ◽  
...  
Keyword(s):  
Low Cost ◽  
Software Tool ◽  
Rapid Acquisition ◽  
Geometric Distortions ◽  
Ground Control Points ◽  
Digital Elevation ◽  
Coastal Landforms ◽  
Elevation Model ◽  
Camera Distortion

Owing to the combination of technological progress in Unmanned Aerial Vehicles (UAVs) and recent advances in photogrammetry processing with the development of the Structure-from-Motion (SfM) approach, UAV photogrammetry enables the rapid acquisition of high resolution topographic data at low cost. This method is particularly widely used for geomorphological surveys of linear coastal landforms. However, linear surveys are generally pointed out as problematic cases because of geometric distortions creating a “bowl effect” in the computed Digital Elevation Model (DEM). Secondly, the survey of linear coastal landforms is associated with peculiar constraints for Ground Control Points (GCPs) measurements and for the spatial distribution of the tie points. This article aims to assess the extent of the bowl effects affecting the DEM generated above a linear beach with a restricted distribution of GCPs, using different acquisition scenarios and different processing procedures, both with PhotoScan® software tool and MicMac® software tool. It appears that, with a poor distribution of the GCPs, a flight scenario that favors viewing angles diversity can limit DEM’s bowl effect. Moreover, the quality of the resulting DEM also depends on the good match between the flight plan strategy and the software tool via the choice of a relevant camera distortion model.

scholarly journals PERFORMANCE EVALUATION OF DIFFERENT GROUND FILTERING ALGORITHMS FOR UAV-BASED POINT CLOUDS

2016 ◽  
Vol XLI-B1 ◽  
pp. 245-251 ◽  
Author(s):  
C. Serifoglu ◽  
O. Gungor ◽  
V. Yilmaz
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
Good Alternative ◽  
Lidar Data ◽  
Filtering Algorithms ◽  
Aerial Photos ◽  
Digital Elevation ◽  
Aerial Vehicle ◽  
Elevation Model ◽  
Uav Images

Digital Elevation Model (DEM) generation is one of the leading application areas in geomatics. Since a DEM represents the bare earth surface, the very first step of generating a DEM is to separate the ground and non-ground points, which is called ground filtering. Once the point cloud is filtered, the ground points are interpolated to generate the DEM. LiDAR (Light Detection and Ranging) point clouds have been used in many applications thanks to their success in representing the objects they belong to. Hence, in the literature, various ground filtering algorithms have been reported to filter the LiDAR data. Since the LiDAR data acquisition is still a costly process, using point clouds generated from the UAV images to produce DEMs is a reasonable alternative. In this study, point clouds with three different densities were generated from the aerial photos taken from a UAV (Unmanned Aerial Vehicle) to examine the effect of point density on filtering performance. The point clouds were then filtered by means of five different ground filtering algorithms as Progressive Morphological 1D (PM1D), Progressive Morphological 2D (PM2D), Maximum Local Slope (MLS), Elevation Threshold with Expand Window (ETEW) and Adaptive TIN (ATIN). The filtering performance of each algorithm was investigated qualitatively and quantitatively. The results indicated that the ATIN and PM2D algorithms showed the best overall ground filtering performances. The MLS and ETEW algorithms were found as the least successful ones. It was concluded that the point clouds generated from the UAVs can be a good alternative for LiDAR data.

scholarly journals Quality of Digital Elevation Models obtained from Unmanned Aerial Vehicles for Precision Viticulture

OENO One ◽  
2016 ◽  
Vol 50 (3) ◽  
Author(s):  
Léo Pichon ◽  
Arnaud Ducanchez ◽  
Hélène Fonta ◽  
Bruno Tisseyre
Keyword(s):  
Low Cost ◽  
Wine Industry ◽  
Image Capture ◽  
Digital Elevation ◽  
Elevation Data ◽  
Aerial Vehicle ◽  
Elevation Model ◽  
Uav Images ◽  
Data Acquisition And Processing

Aims: This work aims to study the quality of low cost Digital Surface Models (DSMs) obtained with Unmanned Aerial Vehicle (UAV) images and to test whether these DSMs meet common requirements of the wine industry.Methods and results: Experiments were carried out on a 4-ha vineyard located 10 km north of Beziers (France). The experimental site presents slope and aspect variations representative of mechanised commercial vineyards in Languedoc Roussillon. DSMs were provided by three UAV companies selected for the diversity of their solutions in terms of image capture altitude, type of UAV and image processing software. DSMs were obtained by photogrammetry and correspond to commercial products usually delivered by UAV companies. DSMs from UAV were compared to a reference Digital Elevation Model (DEM) acquired by a laser tachymeter. Four indicators were used to test the quality of DSMs: the mean error and its dispersion in the XY plane and in elevation Z. Results show a good georeferencing of the DSMs (MeanErrorXY<10 cm) and a similar quality in elevation (MeanErrorZ<10 cm) estimation. Results also show that the error in elevation is highly spatially structured. The spatial patterns observed did not depend on the elevation and could be related to algorithms used to compute the DSMs.Conclusion: Data acquisition and processing methods have an impact on the quality of the DSMs provided by the UAV companies. DSM qualities are good enough to meet commercial vineyard requirements. The tested DSMs fit the requirements to assess field characteristics (elevation, slope, aspects) which may be important for terroir characterisation purposes.Significance and impact of the study: This study proves that elevation data derived from UAV present an accuracy equivalent to the reference system used in this study. The rapidity, the low cost and the high spatial resolution of these data offer significant opportunities for the development of new services for the wine industry for field characterisation.

scholarly journals EVALUATION OF ASTER GDEM V3 USING ICESAT LASER ALTIMETRY

2016 ◽  
Vol XLI-B4 ◽  
pp. 117-124 ◽  
Author(s):  
C. C. Carabajal ◽  
J.-P. Boy
Keyword(s):  
Thermal Emission ◽  
Ground Control ◽  
Control Points ◽  
Ice Cloud ◽  
Aster Gdem ◽  
Ground Control Points ◽  
Digital Elevation ◽  
Elevation Model ◽  
Globally Distributed

We have used a set of Ground Control Points (GCPs) derived from altimetry measurements from the Ice, Cloud and land Elevation Satellite (ICESat) to evaluate the quality of the 30 m posting ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) Global Digital Elevation Model (GDEM) V3 elevation products produced by NASA/METI for Greenland and Antarctica. These data represent the highest quality globally distributed altimetry measurements that can be used for geodetic ground control, selected by applying rigorous editing criteria, useful at high latitudes, where other topographic control is scarce. Even if large outliers still remain in all ASTER GDEM V3 data for both, Greenland and Antarctica, they are significantly reduced when editing ASTER by number of scenes (N≥5) included in the elevation processing. For 667,354 GCPs in Greenland, differences show a mean of 13.74 m, a median of -6.37 m, with an RMSE of 109.65 m. For Antarctica, 6,976,703 GCPs show a mean of 0.41 m, with a median of -4.66 m, and a 54.85 m RMSE, displaying smaller means, similar medians, and less scatter than GDEM V2. Mean and median differences between ASTER and ICESat are lower than 10 m, and RMSEs lower than 10 m for Greenland, and 20 m for Antarctica when only 9 to 31 scenes are included.

scholarly journals Terrain-Based Shadow Correction Method for Assessing Supraglacial Features on the Greenland Ice Sheet

2021 ◽  
Vol 2 ◽  
Author(s):  
Sasha. Z. Leidman ◽  
Åsa K. Rennermalm ◽  
Richard G. Lathrop ◽  
Matthew. G. Cooper
Keyword(s):  
Land Surface ◽  
Greenland Ice Sheet ◽  
Correction Method ◽  
Correction Coefficient ◽  
Digital Elevation ◽  
Aerial Vehicle ◽  
Sediment Cover ◽  
Elevation Model ◽  
Uav Images ◽  
Gis Software

The presence of shadows in remotely sensed images can reduce the accuracy of land surface classifications. Commonly used methods for removing shadows often use multi-spectral image analysis techniques that perform poorly for dark objects, complex geometric models, or shaded relief methods that do not account for shadows cast on adjacent terrain. Here we present a new method of removing topographic shadows using readily available GIS software. The method corrects for cast shadows, reduces the amount of over-correction, and can be performed on imagery of any spectral resolution. We demonstrate this method using imagery collected with an uncrewed aerial vehicle (UAV) over a supraglacial stream catchment in southwest Greenland. The structure-from-motion digital elevation model showed highly variable topography resulting in substantial shadowing and variable reflectance values for similar surface types. The distribution of bare ice, sediment, and water within the catchment was determined using a supervised classification scheme applied to the corrected and original UAV images. The correction resulted in an insignificant change in overall classification accuracy, however, visual inspection showed that the corrected classification more closely followed the expected distribution of classes indicating that shadow correction can aid in identification of glaciological features hidden within shadowed regions. Shadow correction also caused a substantial decrease in the areal coverage of dark sediment. Sediment cover was highly dependent on the degree of shadow correction (k coefficient), yet, for a correction coefficient optimized to maximize shadow brightness without over-exposing illuminated surfaces, terrain correction resulted in a 49% decrease in the area covered by sediment and a 29% increase in the area covered by water. Shadow correction therefore reduces the overestimation of the dark surface coverage due to shadowing and is a useful tool for investigating supraglacial processes and land cover change over a wide variety of complex terrain.

scholarly journals Estimation of the HEC-HMS model parameters in data-scarce regions. Application to the Ouergha watershed (Sebou, Morocco)

2021 ◽  
Vol 314 ◽  
pp. 05002
Author(s):  
Hasna Moumni ◽  
Karima Sebari ◽  
Laila Stour ◽  
Abdellatif Ahbari
Keyword(s):  
Remote Sensing ◽  
Hydrological Model ◽  
Model Parameters ◽  
Flow Data ◽  
Random Parameters ◽  
Quality Of Data ◽  
Initial Values ◽  
Digital Elevation ◽  
Elevation Model

The availability, accessibility and quality of data are significant obstacles to hydrological modelling. Estimating the initial values of the hydrological model´’ ’s parameters is a laborious and determining task requiring much attention. Geographic information systems (GIS) and spatial remote sensing are prometting tools for processing and collecting data. In this work, we use an innovative approach to estimate the HEC-HMS hydrological model parameters from the soil map of Africa (250m), the land use map GLC30, the depth to bedrock map, the digital elevation model and observed flow data. The estimation approach is applied to the Ouergha basin (Sebou, Morocco). The proposed approach’s interest is to feed the HEC-HMS hydrological model with initial values of parameters close to the study area reality instead of using random parameters.

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