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.

scholarly journals The draa Cerro Medanoso (Atacama, Chile) and its importance in the study of desert

2016 ◽  
pp. 25
Author(s):  
José F. Araya Vergara ◽  
Ricardo Vilaró
Keyword(s):  
Digital Elevation Model ◽  
Satellite Imagery ◽  
Morphological Analysis ◽  
Aerial Photos ◽  
Desert Pavement ◽  
Aster Gdem ◽  
Digital Elevation ◽  
The World ◽  
Long Time ◽  
Elevation Model

This work presents a morphological analysis of the Cerro Medanoso draa (Atacama Marginal Desert) and the type of contact with the desert pavements of neighboring glacis and piedmont. This study is based on an analysis of aerial photos, and a digital elevation model. Aster GDEM was used as a basis for the survey. Fieldwork observations covered two principal zones: the nucleus and the envelope. Following fieldwork, analysis of satellite imagery was conducted. It was possible to identify the following phases of formation: construction of a stellate nucleus, merging of the eastern envelope, merging of the southern envelope and merging of a complex western envelope. The southeastern facing envelope is much bigger than the northwestern facing one. Consequently, the construction of the complex draa is asymmetric. The correlation of this megadune with similar star and compound draas to other deserts in the world indicates that the closest analogue exists in Namibia, but without merging signals between the envelope and the nucleus. Star draas observed in other deserts exhibit a lack of this envelope. With reference to the neighboring piedmont, the beginning of its deflation must be necessarily correlative to the initial construction of the nuclear twin star draa. The later deflation could be responsible for the pulses, which formed the envelope. Therefore, the neighboring desert pavement and the draa are correlative landforms, which represent a very long time formation, in an important part of the desert history, as evidenced by the cited and referenced research works.

scholarly journals On the Vertical Accuracy of the ALOS World 3D-30m Digital Elevation Model

2017 ◽  
Author(s):  
Çaglar Bayık ◽  
Kazimierz Becek ◽  
Çetin Mekik ◽  
Mustafa Özendi
Keyword(s):  
Digital Elevation Model ◽  
Reference Data ◽  
Accuracy Assessment ◽  
Reference Dataset ◽  
Digital Elevation ◽  
The World ◽  
Vertical Accuracy ◽  
Longitudinal Profiles ◽  
Elevation Model ◽  
Resolution Data

The digital elevation model (DEM) is one of the key geospatial datasets used in many fields of engineering and science for countless applications. In this contribution, we assess the vertical accuracy of the Advanced Land Observing Satellite (ALOS) World 3D-30m (AW3D30) DEM using the runway method (RWYM). The RWYM utilizes the longitudinal profiles of runways which are reliable and ubiquitous reference data. A reference dataset used in this project consists of 36 runways located at various points throughout the world. The same dataset was previously used to test the accuracy of WorldDEMTM.  Our study indicates that AW3D30 has a remarkably high RMSE of 1.78 m (one σ). However, while analyzing the results, it has become apparent that it also contains a widespread elevation anomaly. We conclude that this anomaly is the result of uncompensated sensor noise and the data processing algorithm (downsampling of the higher resolution data). We believe that this issue should be communicated to the user community. Also, we would like to note that the traditional accuracy assessment of a DEM, e.g., statistical assessment of the elevation differences = model – reference, does not allow for identification of these type of anomalies in a DEM.

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 Accuracy assessment of the global TanDEM-X Digital Elevation Model with GPS data

2018 ◽  
Vol 139 ◽  
pp. 171-182 ◽  
Author(s):  
Birgit Wessel ◽  
Martin Huber ◽  
Christian Wohlfart ◽  
Ursula Marschalk ◽  
Detlev Kosmann ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Accuracy Assessment ◽  
Gps Data ◽  
Digital Elevation ◽  
Elevation Model

Calculating the prominence and isolation of every mountain in the world

2017 ◽  
Vol 41 (6) ◽  
pp. 788-802 ◽  
Author(s):  
Andrew Kirmse ◽  
Jonathan de Ferranti
Keyword(s):  
Digital Elevation Model ◽  
Global Scale ◽  
Digital Elevation ◽  
The World ◽  
Elevation Data ◽  
Elevation Model

A global-scale calculation identifies peaks in a digital elevation model (DEM) and computes their isolation and topographic prominence. A new DEM is presented that covers the entire globe at 90 meter resolution with no substantial voids or artifacts. All peaks with at least 1 kilometer of isolation are found, and the closest higher ground is identified. For prominence, all peaks with at least ∼30 meters are found, and the key saddle is identified. The prominence algorithm uses results from Morse–Smale topology to run in parallel on standard, freely available elevation data. Thirteen previously unknown “ultra-prominent” mountains with at least 1500 meters of prominence are listed.

scholarly journals SENTINEL-1 IMAGE MATCHING USING STRONG SCATTERS

2015 ◽  
Vol XL-1-W5 ◽  
pp. 233-235
Author(s):  
M. A. Ghannadi ◽  
M. Saadatseresht ◽  
M. Motagh
Keyword(s):  
Change Detection ◽  
Digital Elevation Model ◽  
Image Matching ◽  
Temporal Change ◽  
Stereo Images ◽  
Digital Elevation ◽  
The World ◽  
Spatial And Temporal Change ◽  
Elevation Model

The availability of new radar spaceborne sensors offers new interesting potentialities for the geomatics application: spatial and temporal change detection, generation of Digital Elevation Model(DEM) using radargrametry and interferometry. Since the start of the sentinel-1 mission to take images from different regions all over the world, the ability to use these images in variety domains has been treasured. This paper suggests a method for image matching using strong scatters. all the experiments are done on sentinel-1 stereo images from Jam, Bushehr, Iran.

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.

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