scholarly journals EVALUATION DIGITAL ELEVATION MODEL GENERATED BY SYNTHETIC APERTURE RADAR DATA

2016 ◽  
Vol XLI-B1 ◽  
pp. 57-62
Author(s):  
H. B. Makineci ◽  
H. Karabörk
Keyword(s):  
Remote Sensing ◽  
Digital Elevation Model ◽  
Interpolation Method ◽  
Digital Elevation Models ◽  
European Space Agency ◽  
Mountain Area ◽  
Synthetic Aperture Radar Data ◽  
Radar Images ◽  
Digital Elevation ◽  
Elevation Model

Digital elevation model, showing the physical and topographical situation of the earth, is defined a tree-dimensional digital model obtained from the elevation of the surface by using of selected an appropriate interpolation method. DEMs are used in many areas such as management of natural resources, engineering and infrastructure projects, disaster and risk analysis, archaeology, security, aviation, forestry, energy, topographic mapping, landslide and flood analysis, Geographic Information Systems (GIS). Digital elevation models, which are the fundamental components of cartography, is calculated by many methods. Digital elevation models can be obtained terrestrial methods or data obtained by digitization of maps by processing the digital platform in general. Today, Digital elevation model data is generated by the processing of stereo optical satellite images, radar images (radargrammetry, interferometry) and lidar data using remote sensing and photogrammetric techniques with the help of improving technology. <br><br> One of the fundamental components of remote sensing radar technology is very advanced nowadays. In response to this progress it began to be used more frequently in various fields. Determining the shape of topography and creating digital elevation model comes the beginning topics of these areas. <br><br> It is aimed in this work , the differences of evaluation of quality between Sentinel-1A SAR image ,which is sent by European Space Agency ESA and Interferometry Wide Swath imaging mode and C band type , and DTED-2 (Digital Terrain Elevation Data) and application between them. The application includes RMS static method for detecting precision of data. Results show us to variance of points make a high decrease from mountain area to plane area.

scholarly journals EVALUATION DIGITAL ELEVATION MODEL GENERATED BY SYNTHETIC APERTURE RADAR DATA

2016 ◽  
Vol XLI-B1 ◽  
pp. 57-62
Author(s):  
H. B. Makineci ◽  
H. Karabörk
Keyword(s):  
Remote Sensing ◽  
Digital Elevation Model ◽  
Interpolation Method ◽  
Digital Elevation Models ◽  
European Space Agency ◽  
Mountain Area ◽  
Synthetic Aperture Radar Data ◽  
Radar Images ◽  
Digital Elevation ◽  
Elevation Model

Digital elevation model, showing the physical and topographical situation of the earth, is defined a tree-dimensional digital model obtained from the elevation of the surface by using of selected an appropriate interpolation method. DEMs are used in many areas such as management of natural resources, engineering and infrastructure projects, disaster and risk analysis, archaeology, security, aviation, forestry, energy, topographic mapping, landslide and flood analysis, Geographic Information Systems (GIS). Digital elevation models, which are the fundamental components of cartography, is calculated by many methods. Digital elevation models can be obtained terrestrial methods or data obtained by digitization of maps by processing the digital platform in general. Today, Digital elevation model data is generated by the processing of stereo optical satellite images, radar images (radargrammetry, interferometry) and lidar data using remote sensing and photogrammetric techniques with the help of improving technology. &lt;br&gt;&lt;br&gt; One of the fundamental components of remote sensing radar technology is very advanced nowadays. In response to this progress it began to be used more frequently in various fields. Determining the shape of topography and creating digital elevation model comes the beginning topics of these areas. &lt;br&gt;&lt;br&gt; It is aimed in this work , the differences of evaluation of quality between Sentinel-1A SAR image ,which is sent by European Space Agency ESA and Interferometry Wide Swath imaging mode and C band type , and DTED-2 (Digital Terrain Elevation Data) and application between them. The application includes RMS static method for detecting precision of data. Results show us to variance of points make a high decrease from mountain area to plane area.

scholarly journals A Comparative Study of Three Non-Geostatistical Methods for Optimising Digital Elevation Model Interpolation

2018 ◽  
Vol 7 (8) ◽  
pp. 300 ◽  
Author(s):  
Serajis Salekin ◽  
Jack Burgess ◽  
Justin Morgenroth ◽  
Euan Mason ◽  
Dean Meason
Keyword(s):  
Digital Elevation Model ◽  
Spatial Resolution ◽  
Laser Scanning ◽  
Interpolation Method ◽  
Digital Elevation Models ◽  
Global Navigation Satellite Systems ◽  
Digital Elevation ◽  
Dem Accuracy ◽  
Elevation Model ◽  
Gnss Data

It is common to generate digital elevation models (DEMs) from aerial laser scanning (ALS) data. However, cost and lack of knowledge may preclude its use. In contrast, global navigation satellite systems (GNSS) are seldom used to collect and generate DEMs. These receivers have the potential to be considered as data sources for DEM interpolation, as they can be inexpensive, easy to use, and mobile. The data interpolation method and spatial resolution from this method needs to be optimised to create accurate DEMs. Moreover, the density of GNSS data is likely to affect DEM accuracy. This study investigates three different deterministic approaches, in combination with spatial resolution and data thinning, to determine their combined effects on DEM accuracy. Digital elevation models were interpolated, with resolutions ranging from 0.5 m to 10 m using natural neighbour (NaN), topo to raster (ANUDEM), and inverse distance weighted (IDW) methods. The GNSS data were thinned by 25% (0.389 points m−2), 50% (0.259 points m−2), and 75% (0.129 points m−2) and resulting DEMs were contrast against a DEM interpolated from unthinned data (0.519 points m−2). Digital elevation model accuracy was measured by root mean square error (RMSE) and mean absolute error (MAE). It was found that the highest resolution, 0.5 m, produced the lowest errors in resulting DEMs (RMSE = 0.428 m, MAE = 0.274 m). The ANUDEM method yielded the greatest DEM accuracy from a quantitative perspective (RMSE = 0.305 m and MAE = 0.197 m); however, NaN produced a more visually appealing surface. In all the assessments, IDW showed the lowest accuracy. Thinning the input data by 25% and even 50% had relatively little impact on DEM quality; however, accuracy decreased markedly at 75% thinning (0.129 points m−2). This study showed that, in a time where ALS is commonly used to generate DEMs, GNSS-surveyed data can be used to create accurate DEMs. This study confirmed the need for optimization to choose the appropriate interpolation method and spatial resolution in order to produce a reliable DEM.

A robust interpolation method for constructing digital elevation models from remote sensing data

Geomorphology ◽  
2016 ◽  
Vol 268 ◽  
pp. 275-287 ◽  
Author(s):  
Chuanfa Chen ◽  
Fengying Liu ◽  
Yanyan Li ◽  
Changqing Yan ◽  
Guolin Liu
Keyword(s):  
Remote Sensing ◽  
Interpolation Method ◽  
Digital Elevation Models ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Digital Elevation

scholarly journals Remote sensing of terrestrial impact craters: The TanDEM-X digital elevation model

2016 ◽  
Vol 52 (7) ◽  
pp. 1412-1427 ◽  
Author(s):  
Manfred Gottwald ◽  
Thomas Fritz ◽  
Helko Breit ◽  
Birgit Schättler ◽  
Alan Harris
Keyword(s):  
Remote Sensing ◽  
Digital Elevation Model ◽  
Impact Craters ◽  
Digital Elevation ◽  
Elevation Model

scholarly journals DEMNAS: MODEL DIGITAL KETINGGIAN NASIONAL UNTUK APLIKASI KEPESISIRAN

OSEANA ◽  
2018 ◽  
Vol 43 (4) ◽  
Author(s):  
Marindah Yulia Iswari ◽  
Kasih Anggraini
Keyword(s):  
Remote Sensing ◽  
Digital Elevation Model ◽  
Spatial Resolution ◽  
Digital Data ◽  
Coastal Hazards ◽  
Remote Sensing Images ◽  
Geospatial Information ◽  
Digital Elevation ◽  
Elevation Data ◽  
Elevation Model

DEMNAS : NATIONAL DIGITAL ELEVATION MODEL FOR COASTAL APPLICATION. DEM is a digital data which contain information about elevation. In Indonesia, DEM can be generated from elevation points or contours in RBI (Rupabumi Indonesia). DEM can be performed to research of coastal application i.e. inundation or tsunami. DEM can help to analyze vulnerability or evacuation zone for coastal hazards. DEMNAS is one product of BIG (Geospatial Information Agency) which consist of elevation data from remote sensing images. DEMNAS data has not been widely used and is still being developed but DEMNAS has an advantage of spatial resolution. DEMNAS has spatial resolution 0.27 arc-second, which is bigger than the spatial resolution of global DEM.

scholarly journals High-Resolution LiDAR Digital Elevation Model Referenced Landslide Slide Observation with Differential Interferometric Radar, GNSS, and Underground Measurements

2021 ◽  
Vol 11 (23) ◽  
pp. 11389
Author(s):  
Kuo-Lung Wang ◽  
Jun-Tin Lin ◽  
Hsun-Kuang Chu ◽  
Chao-Wei Chen ◽  
Chia-Hao Lu ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Solution Process ◽  
Vertical Direction ◽  
Vertical Deformation ◽  
Mountain Area ◽  
Complex Deformation ◽  
Digital Elevation ◽  
Geological Conditions ◽  
Lidar Dem ◽  
Elevation Model

The area of Taiwan is 70% hillsides. In addition, the topography fluctuates wildly, and it is active in earthquakes and young orogenic movements. Landslides are a widespread disaster in Taiwan. However, landslides are not a disaster until someone enters the mountain area for development. Therefore, landslide displacement monitoring is the primary task of this study. Potential landslide areas with mostly slate geological conditions were selected as candidate sites in this study. The slate bedding in this area is approximately 30 to 75 degrees toward the southeast, which means that creep may occur due to gravity deformation caused by high-angle rock formation strikes. In addition, because the research site is located in a densely vegetated area, the data noise is very high, and it is not easy to obtain good results. This study chose ESA Sentinel-1 data for analysis and 1-m LiDAR DEM as reference elevation. The 1-m LiDAR DEM with high accuracy can help to detect more complex deformation from DInSAR. The Sentinel-1 series of satellites have a regular revisit period. In addition, the farm areas of roads, bridges, and buildings in the study area provided enough reflections to produce good coherence. Sentinel-1 images from March 2017 to June 2021 were analyzed, obtaining slope deformation and converting it to the vertical direction. Deformation derived from SAR is compared with other measurements, including GNSS and underground slope inclinometer. The SBAS solution process provides more DInSAR pairs to overcome the problem of tremendous noise and has increased accuracy. Moreover, the SBAS method’s parameter modification derives more candidate points in the vegetated area. The vertical deformation comparison between the GNSS installation location and the ascending SBAS solution’s vertical deformation is consistent. Moreover, the reliable facing of the slope toward the SAR satellite is discussed. Due to the limitations of the GNSS stations, this study proposes a method to convert the observed deformation from the slope inclinometer and convert it to vertical deformation. The displacement of the slope indicator is originally a horizontal displacement. It is assumed that it is fixed at the farthest underground, and the bottom-to-top movement is integrated with depth. The results show that the proposed equation to convert horizontal to vertical displacement fits well in this condition. The activity of landslides within the LiDAR digital elevation model identified as scars is also mapped.

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