Use of noise reduction filters on stereo images for improving the accuracy and quality of the digital elevation model

2021 ◽  
Vol 15 (01) ◽  
Author(s):  
Litesh Bopche ◽  
Priti P. Rege
Keyword(s):  
Noise Reduction ◽  
Digital Elevation Model ◽  
Stereo Images ◽  
Digital Elevation ◽  
Elevation Model

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 Evaluating the Vertical Accuracy of DEM Generated from ZiYuan-3 Stereo Images in Understanding the Tectonic Morphology of the Qianhe Basin, China

2021 ◽  
Vol 13 (6) ◽  
pp. 1203
Author(s):  
Zhiheng Liu ◽  
Ling Han ◽  
Zhaohui Yang ◽  
Hongye Cao ◽  
Fengcheng Guo ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Tectonic Uplift ◽  
Mountainous Area ◽  
Stereo Images ◽  
Rapid Acquisition ◽  
Aster Gdem ◽  
Digital Elevation ◽  
Evolutionary Response ◽  
Elevation Difference ◽  
Elevation Model

Currently available high-resolution digital elevation model (DEM) is not particularly useful to geologists for understanding the long-term changes in fluvial landforms induced by tectonic uplift, although DEMs that are generated from satellite stereo images such as the ZiYuan-3 (ZY3) satellite include characteristics with significant coverage and rapid acquisition. Since an ongoing analysis of fluvial systems is lacking, the ZY3 DEM was generated from block adjustment to describe the mountainous area of the Qianhe Basin that have been induced by tectonic uplift. Moreover, we evaluated the overall elevation difference in ZY3 DEM, Shuttle Radar Topography Mission (1″ × 1″) (SRTM1), and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) by using the Ice Cloud and Land Elevation Satellite/Geoscience Laser Altimeter (ICESat/GLAH14) point cloud and a DEM of 1:50,000 scale. The values of the root mean square error (RMSE) of the elevation difference for ZY3 DEM were 9.31 and 9.71 m, respectively, and are in good agreement with SRTM1. The river long profiles and terrace heights were also extracted to compare the differences in channel steepness and the incision rates with SRTM1 and ASTER GDEM. Our results prove that ZY3 DEM would be a good alternative to SRTM1 in achieving the 1:50,000 scale for DEM products in China, while ASTER GDEM is unsuitable for extracting river longitudinal profiles. In addition, the northern and southern river incision rates were estimated using the ages and heights of river terraces, demonstrating a range from 0.12–0.45 to 0.10–0.33 m/kyr, respectively. Collectively, these findings suggest that ZY3 DEM is capable of estimating tectonic geomorphological features and has the potential for analyzing the continuous evolutionary response of a landscape to changes in climate and tectonics.

scholarly journals Development of an automatic delineation of cliff top and toe on very irregular planform coastlines (CliffMetrics v1.0)

2018 ◽  
Author(s):  
Andres Payo ◽  
Bismarck Jigena Antelo ◽  
Martin Hurst ◽  
Monica Palaseanu-Lovejoy ◽  
Chris Williams ◽  
...  
Keyword(s):  
Great Britain ◽  
Digital Elevation Model ◽  
Model Output ◽  
Dem Resolution ◽  
M 10 ◽  
Digital Elevation ◽  
Elevation Model

Abstract. We describe a new algorithm that automatically delineates the cliff top and toe of a cliffed coastline from a Digital Elevation Model (DEM). The algorithm builds upon existing methods but is specifically designed to resolve very irregular planform coastlines with many bays and capes, such as parts of the coastline of Great Britain. The algorithm automatically and sequentially delineates and smooth shoreline vectors, generates orthogonal transects and elevation profiles with a minimum spacing equal to the DEM resolution, and extracts the position and elevation of the cliff top and toe. Outputs include the non-smoothed-raster and smoothed-vector coastline, normals to the coastline- (as vector shapefiles), xyz profiles (as comma-separated-value files), and the cliff top and toe (as point shape files). The algorithm also automatically assesses the quality of the profile and omits low-quality profiles (i.e. extraction of cliff top and toe is not possible). The performance of the proposed algorithm is compared with an existing method, which was not specifically designed for very irregular coastlines, and to hand-digitized boundaries by numerous professionals. Also we assess the reproducibility of the results using different DEM resolutions (5 m, 10 m and 50 m), different user defined parameter-sets related to the degree of coastline smoothing, and the threshold used to identify the cliff top and toe. The model output sensitivity is found to be smaller than hand-digitized uncertainty. Code and a manual are publicly available on a github repository.

scholarly journals The Impact of Quality of Digital Elevation Models on the Result of Landslide Susceptibility Modeling Using the Method of Weights of Evidence

Geosciences ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 488
Author(s):  
Mirosław Kamiński
Keyword(s):  
Digital Elevation Model ◽  
Roc Curve ◽  
Landslide Susceptibility ◽  
Weights Of Evidence ◽  
Identification System ◽  
Susceptibility Modeling ◽  
Digital Elevation ◽  
Elevation Model ◽  
The Impact

The paper discusses the impact that the quality of the digital elevation model (DEM) has on the final result of landslide susceptibility modeling (LSM). The landslide map was developed on the basis of the analysis of archival geological maps and the Light Detection and Ranging (LiDAR) digital elevation model. In addition, complementary field studies were conducted. In total, 92 landslides were inventoried and their degree of activity was assessed. An inventory of the landslides was prepared using a 1-m-LiDAR DEM and field research. Two digital photogrammetric elevation models with an elevation pixel resolution of 20 m were used for landslide susceptibility modeling. The first digital elevation model was obtained from a LiDAR point cloud (DEM–airborne laser scanning (ALS)), while the second model was developed based on archival digital stereo-pair aerial images (DEM–Land Parcel Identification System (LPIS)). Both models were subjected to filtration using a Gaussian low-pass filter to reduce errors in their elevation relief. Then, using ArcGIS software, a differential model was generated to illustrate the differences in morphology between the models. The maximum differences in topographic elevations between the DEM–ALS and DEM–LPIS models were calculated. The Weights-of-Evidence model is a geostatistical method used for the landslide susceptibility modeling. Six passive factors were employed in the process of susceptibility generation: elevation, slope gradient, exposure, topographic roughness index (TRI), distance from tectonic lines, and distance from streams. As a result, two landslide susceptibility maps (LSM) were obtained. The accuracy of the landslide susceptibility models was assessed based on the Receiver Operating Characteristic (ROC) curve index. The area under curve (AUC) values obtained from the ROC curve indicate that the accuracy of classification for the LSM–DEM–ALS model was 78%, and for the LSM–LPIS–DEM model was 73%.

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 Experimental Analysis of Srtm Model by Image Processing and Geostatistical Methods

2018 ◽  
Vol 7 (4.7) ◽  
pp. 250 ◽  
Author(s):  
M. V. Kuzyakina ◽  
D. A. Gura ◽  
Yu. A. Mishchenko ◽  
D. A. Gordienko
Keyword(s):  
Image Processing ◽  
Digital Elevation Model ◽  
Experimental Analysis ◽  
Geostatistical Methods ◽  
Digital Elevation ◽  
Different Types ◽  
Elevation Model ◽  
Bicubic Interpolation

This article compares the image processing and geostatistical methods of GIS. They proposed the application of these methods to restore the quality of the well-known digital elevation model SRTM degraded sections using the example of the Krasnodar Territory. The conclusions are drawn also about the quality of modeling for test sites with different types of relief – flat, hilly and mountain. The best results were achieved for the method of bicubic interpolation. 

scholarly journals Development of an automatic delineation of cliff top and toe on very irregular planform coastlines (CliffMetrics v1.0)

2018 ◽  
Vol 11 (10) ◽  
pp. 4317-4337 ◽  
Author(s):  
Andres Payo ◽  
Bismarck Jigena Antelo ◽  
Martin Hurst ◽  
Monica Palaseanu-Lovejoy ◽  
Chris Williams ◽  
...  
Keyword(s):  
Great Britain ◽  
Digital Elevation Model ◽  
Model Output ◽  
Dem Resolution ◽  
Digital Elevation ◽  
Elevation Model

Abstract. We describe a new algorithm that automatically delineates the cliff top and toe of a cliffed coastline from a digital elevation model (DEM). The algorithm builds upon existing methods but is specifically designed to resolve very irregular planform coastlines with many bays and capes, such as parts of the coastline of Great Britain. The algorithm automatically and sequentially delineates and smooths shoreline vectors, generates orthogonal transects and elevation profiles with a minimum spacing equal to the DEM resolution, and extracts the position and elevation of the cliff top and toe. Outputs include the non-smoothed raster and smoothed vector coastlines, normals to the coastline (as vector shape files), xyz profiles (as comma-separated-value, CSV, files), and the cliff top and toe (as point shape files). The algorithm also automatically assesses the quality of the profile and omits low-quality profiles (i.e. extraction of cliff top and toe is not possible). The performance of the proposed algorithm is compared with an existing method, which was not specifically designed for very irregular coastlines, and to manually digitized boundaries by numerous professionals. Also, we assess the reproducibility of the results using different DEM resolutions (5, 10 and 50 m), different user-defined parameter sets related to the degree of coastline smoothing, and the threshold used to identify the cliff top and toe. The model output sensitivity is found to be smaller than the manually digitized uncertainty. The code and a manual are publicly available on a GitHub repository.

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