scholarly journals Automatic extraction of digital elevation from IKONOS in-track stereo images

2021 ◽  
Author(s):  
Xu Sun
Keyword(s):  
Physical Model ◽  
Stereo Images ◽  
Digital Elevation ◽  
Erdas Imagine ◽  
Systematic Biases ◽  
The Difference ◽  
Dem Accuracy ◽  
Preliminary Planning ◽  
Potential Use ◽  
Final Alignment

This Thesis addresses the topic of the extraction of Digital Elevation Models (DEMs) from the in-track stereo images acquired by IKONOS satellite. Research on this topic is mainly motivated by the need of DEMs in trasportation and the potential use of very high resolution satellite stereo images to replace the traditional aerial photography to generate the DEMs that may be used for preliminary planning and location issues, limiting expensive and time consuming photogrammetry work to the final alignment corridor. In this thesis, two methods for DEM extraction from IKONOS stereo images using a modified Rational Function Model (RFM) and the 3D physical model developed at the Canada Centre for Remote Sensing (CCRS) are used and the accuracy of the DEMs generated using these two models are evaluated. The nominal accuracy of ground points determined with the vendor-supplied RPCs is evaluated and systematic biases are found. A significant improvement in the DEM accuracy is made by removing the biases in both the image and ground domain with the information of ground control. DEMs are automatically generated bya chain of processes using the PCI Geomatica OrthoEngine software package with the refined RFM and 3D physical model, respectively. The DEMs from these two methods are then compared in a desktop ERDAS Imagine environment and the accuracy of the DEMs is evaluated by comparing the extracted DEMs with the DEM from airphotos. The DEMs generated using different mathematical models have a very good consistence and more than 97% of the difference between the generated DEMs and the DEM from airphotos is between -2 m to 2m.

scholarly journals Automatic extraction of digital elevation from IKONOS in-track stereo images

2021 ◽  
Author(s):  
Xu Sun
Keyword(s):  
Physical Model ◽  
Stereo Images ◽  
Digital Elevation ◽  
Erdas Imagine ◽  
Systematic Biases ◽  
The Difference ◽  
Dem Accuracy ◽  
Preliminary Planning ◽  
Potential Use ◽  
Final Alignment

This Thesis addresses the topic of the extraction of Digital Elevation Models (DEMs) from the in-track stereo images acquired by IKONOS satellite. Research on this topic is mainly motivated by the need of DEMs in trasportation and the potential use of very high resolution satellite stereo images to replace the traditional aerial photography to generate the DEMs that may be used for preliminary planning and location issues, limiting expensive and time consuming photogrammetry work to the final alignment corridor. In this thesis, two methods for DEM extraction from IKONOS stereo images using a modified Rational Function Model (RFM) and the 3D physical model developed at the Canada Centre for Remote Sensing (CCRS) are used and the accuracy of the DEMs generated using these two models are evaluated. The nominal accuracy of ground points determined with the vendor-supplied RPCs is evaluated and systematic biases are found. A significant improvement in the DEM accuracy is made by removing the biases in both the image and ground domain with the information of ground control. DEMs are automatically generated bya chain of processes using the PCI Geomatica OrthoEngine software package with the refined RFM and 3D physical model, respectively. The DEMs from these two methods are then compared in a desktop ERDAS Imagine environment and the accuracy of the DEMs is evaluated by comparing the extracted DEMs with the DEM from airphotos. The DEMs generated using different mathematical models have a very good consistence and more than 97% of the difference between the generated DEMs and the DEM from airphotos is between -2 m to 2m.

scholarly journals Evaluation of Atmospheric Effects on Interferograms Using DEM Errors of Fixed Ground Points

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2336 ◽  
Author(s):  
Takashi Nonaka ◽  
Tomohito Asaka ◽  
Keishi Iwashita
Keyword(s):  
Phase Noise ◽  
Atmospheric Effects ◽  
Sar Images ◽  
Single Pass ◽  
Digital Elevation ◽  
Total Phase ◽  
Disaster Monitoring ◽  
The Difference ◽  
Elevation Model ◽  
Interferometric Sar

High-resolution synthetic aperture radar (SAR) data are widely used for disaster monitoring. To extract damaged areas automatically, it is essential to understand the relationships among the sensor specifications, acquisition conditions, and land cover. Our previous studies developed a method for estimating the phase noise of interferograms using several pairs of TerraSAR-X series (TerraSAR-X and TanDEM-X) datasets. Atmospheric disturbance data are also necessary to interpret the interferograms; therefore, the purpose of this study is to estimate the atmospheric effects by focusing on the difference in digital elevation model (DEM) errors between repeat-pass (two interferometric SAR images acquired at different times) and single-pass (two interferometric SAR images acquired simultaneously) interferometry. Single-pass DEM errors are reduced due to the lack of temporal decorrelation and atmospheric disturbances. At a study site in the city of Tsukuba, a quantitative analysis of DEM errors at fixed ground objects shows that the atmospheric effects are estimated to contribute 75% to 80% of the total phase noise in interferograms.

scholarly journals OPTIMIZATION OF THE WAVECAT WAVE ENERGY CONVERTER

2012 ◽  
Vol 1 (33) ◽  
pp. 5 ◽  
Author(s):  
Hernan Fernandez ◽  
Gregorio Iglesias ◽  
Rodrigo Carballo ◽  
Alberte Castro ◽  
Marcos Sánchez ◽  
...  
Keyword(s):  
Physical Model ◽  
Wave Energy ◽  
Model Tests ◽  
Irregular Waves ◽  
Intermediate Water ◽  
Plan View ◽  
Santiago De Compostela ◽  
Wave Energy Converters ◽  
Physical Model Tests ◽  
The Difference

The development of efficient, reliable Wave Energy Converters (WECs) is a prerequisite for wave energy to become a commercially viable energy source. Intensive research is currently under way on a number of WECs, among which WaveCat©—a new WEC recently patented by the University of Santiago de Compostela. In this sense, this paper describes the WaveCat concept and its ongoing development and optimization. WaveCat is a floating WEC intended for operation in intermediate water depths (50–100 m). Like a catamaran, it consists of two hulls—from which it derives its name. The difference with a conventional catamaran is that the hulls are not parallel but convergent; they are joined at the stern, forming a wedge in plan view. Physical model tests of a 1:30 model were conducted in a wave tank using both regular and irregular waves. In addition to the waves and overtopping rates, the model displacements were monitored using a non-intrusive system. The results of the physical model tests will be used to validate the 3D numerical model, which in turn will be used to optimize the design of WaveCat for best performance under a given set of wave conditions.

scholarly journals ANALYSIS OF INFLUENCE OF TERRAIN RELIEF ROUGHNESS ON DEM ACCURACY GENERATED FROM LIDAR IN THE CZECH REPUBLIC TERRITORY

2016 ◽  
Vol XLI-B4 ◽  
pp. 25-30 ◽  
Author(s):  
M. Hubacek ◽  
V. Kovarik ◽  
V. Kratochvil
Keyword(s):  
Czech Republic ◽  
Laser Scanning ◽  
Vegetation Coverage ◽  
The Czech Republic ◽  
Digital Elevation ◽  
Lower Accuracy ◽  
Check Points ◽  
Elevation Data ◽  
Dem Accuracy ◽  
Elevation Model

Digital elevation models are today a common part of geographic information systems and derived applications. The way of their creation is varied. It depends on the extent of area, required accuracy, delivery time, financial resources and technologies available. The first model covering the whole territory of the Czech Republic was created already in the early 1980's. Currently, the 5th DEM generation is being finished. Data collection for this model was realized using the airborne laser scanning which allowed creating the DEM of a new generation having the precision up to a decimetre. Model of such a precision expands the possibilities of employing the DEM and it also offers new opportunities for the use of elevation data especially in a domain of modelling the phenomena dependent on highly accurate data. The examples are precise modelling of hydrological phenomena, studying micro-relief objects, modelling the vehicle movement, detecting and describing historical changes of a landscape, designing constructions etc. <br><br> Due to a nature of the technology used for collecting data and generating DEM, it is assumed that the resulting model achieves lower accuracy in areas covered by vegetation and in built-up areas. Therefore the verification of model accuracy was carried out in five selected areas in Moravia. The network of check points was established using a total station in each area. To determine the reference heights of check points, the known geodetic points whose heights were defined using levelling were used. Up to several thousands of points were surveyed in each area. Individual points were selected according to a different configuration of relief, different surface types, and different vegetation coverage. The sets of deviations were obtained by comparing the DEM 5G heights with reference heights which was followed by verification of tested elevation model. Results of the analysis showed that the model reaches generally higher precision than the declared one in majority of areas. This applies in particular to areas covered by vegetation. By contrast, the larger deviations occurred in relation to the slope of the terrain, in particular in the micro-relief objects. The results are presented in this article.

scholarly journals Accuracy Evaluation of Four Greenland Digital Elevation Models (DEMs) and Assessment of River Network Extraction

2020 ◽  
Vol 12 (20) ◽  
pp. 3429
Author(s):  
Ziyang Xing ◽  
Zhaohui Chi ◽  
Ying Yang ◽  
Shiyi Chen ◽  
Huabing Huang ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Digital Elevation Models ◽  
Greenland Ice Sheet ◽  
River Network ◽  
The Other ◽  
Time Range ◽  
Accuracy Evaluation ◽  
Digital Elevation ◽  
Dem Accuracy ◽  
The Impact

Digital Elevation Models (DEMs) of Greenland provide the basic data for studying the Greenland ice sheet (GrIS), but little research quantitatively evaluates and compares the accuracy of various Greenland DEMs. This study uses IceBridge elevation data to evaluate the accuracies of the the Greenland Ice Map Project (GIMP)1 DEM, GIMP2 DEM, TanDEM-X, and ArcticDEM in their corresponding time ranges. This study also analyzes the impact of DEM accuracy and resolution on the accuracy of river network extraction. The results show that (1) within the time range covered by each DEM, TanDEM-X with an RMSE of 5.60 m has higher accuracy than the other DEMs in terms of absolute height accuracy, while GIMP1 has the lowest accuracy among the four Greenland DEMs, with an RMSE of 14.34 m. (2) Greenland DEMs are affected by regional errors and interannual changes. The accuracy in areas with elevations above 2000 m is higher than that in areas with elevations below 2000 m, and better accuracy is observed in the north than in the south. The stability of the ArcticDEM product is higher than those of the other three DEM products, and its RMSE standard deviation over multiple years is only 0.14 m. Therefore, the errors caused by the applications of DEMs with longer time spans are smaller. GIMP1 performs in an opposite manner, with a standard deviation of 2.39 m. (3) The river network extracted from TanDEM-X is close to the real river network digitized from remote sensing images, with an accuracy of 50.78%. The river network extracted from GIMP1 exhibits the largest errors, with an accuracy of only 8.83%. This study calculates and compares the accuracy of four Greenland DEMs and indicates that TanDEM-X has the highest accuracy, adding quantitative studies on the accuracy evaluation of various Greenland DEMs. This study also compares the results of different DEM river network extractions, verifies the impact of DEM accuracy on the accuracy of the river network extraction results, and provides an explorable direction for the hydrological analysis of Greenland as a whole.

scholarly journals Predicting Channel Conveyance and Characterizing Planform Using River Bathymetry via Satellite Image Compilation (RiBaSIC) Algorithm for DEM-Based Hydrodynamic Modeling

2020 ◽  
Vol 12 (17) ◽  
pp. 2799
Author(s):  
Md N M Bhuyian ◽  
Alfred Kalyanapu
Keyword(s):  
Mean Squared Error ◽  
Satellite Image ◽  
Shuttle Radar Topography Mission ◽  
Willamette River ◽  
Bathymetric Data ◽  
Digital Elevation ◽  
Channel Slope ◽  
Dem Accuracy ◽  
Landsat Satellite ◽  
Discharge Estimation

Digital Elevation Models (DEMs) are widely used as a proxy for bathymetric data and several studies have attempted to improve DEM accuracy for hydrodynamic (HD) modeling. Most of these studies attempted to quantitatively improve estimates of channel conveyance (assuming a non-braided morphology) rather than accounting for the actual channel planform. Accurate representation of river conveyance and planform in a DEM is critical to HD modeling and can be achieved with a combination of remote sensing (e.g., satellite image) and field data, such as water surface elevation (WSE). Therefore, the objectives of this study are (i) to develop an algorithm for predicting channel conveyance and characterizing planform via satellite images and in situ WSE and (ii) to estimate discharge using the predicted conveyance via an HD model. The algorithm is named River Bathymetry via Satellite Image Compilation (RiBaSIC) and uses Landsat satellite imagery, Shuttle Radar Topography Mission (SRTM) DEM, Multi-Error-Removed Improved-Terrain (MERIT) DEM, and observed WSE. The algorithm is tested on four study areas along the Willamette River, Kushiyara River, Jamuna River, and Solimoes River. Channel slope and predicted hydraulic radius are subsequently estimated for approximating Manning’s roughness factor. Two-dimensional HD models using DEMs modified by the RiBaSIC algorithm and corresponding Manning’s roughness factors are employed for discharge estimation. The proposed algorithm can represent river planform and conveyance in single-channeled, meandering, wandering, and braided river reaches. Additionally, the HD models estimated discharge within 14–19% relative root mean squared error (RRMSE) in simulation of five years period.

scholarly journals A Framework for Correcting Ionospheric Artifacts and Atmospheric Effects to Generate High Accuracy InSAR DEM

2020 ◽  
Vol 12 (2) ◽  
pp. 318 ◽  
Author(s):  
Zhiwei Liu ◽  
Cui Zhou ◽  
Haiqiang Fu ◽  
Jianjun Zhu ◽  
Tingying Zuo
Keyword(s):  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Atmospheric Effects ◽  
Interferometric Synthetic Aperture Radar ◽  
Dual Polarization ◽  
Digital Elevation ◽  
Split Spectrum ◽  
Dem Accuracy ◽  
Study Sites ◽  
Aperture Radar

Repeat-pass interferometric synthetic aperture radar is a well-established technology for generating digital elevation models (DEMs). However, the interferogram usually has ionospheric and atmospheric effects, which reduces the DEM accuracy. In this paper, by introducing dual-polarization interferograms, a new approach is proposed to mitigate the ionospheric and atmospheric errors of the interferometric synthetic aperture radar (InSAR) data. The proposed method consists of two parts. First, the range split-spectrum method is applied to compensate for the ionospheric artifacts. Then, a multiresolution correlation analysis between dual-polarization InSAR interferograms is employed to remove the identical atmospheric phases, since the atmospheric delay is independent of SAR polarizations. The corrected interferogram can be used for DEM extraction. Validation experiments, using the ALOS-1 PALSAR interferometric pairs covering the study areas in Hawaii and Lebanon of the U.S.A., show that the proposed method can effectively reduce the ionospheric artifacts and atmospheric effects, and improve the accuracy of the InSAR-derived DEMs by 64.9% and 31.7% for the study sites in Hawaii and Lebanon of the U.S.A., respectively, compared with traditional correction methods. In addition, the assessment of the resulting DEMs also includes comparisons with the high-precision Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) altimetry data. The results show that the selection of reference data will not affect the validation results.

scholarly journals Investigating the Impact of Digital Elevation Models on Sentinel-1 Backscatter and Coherence Observations

2020 ◽  
Vol 12 (18) ◽  
pp. 3016
Author(s):  
Ignacio Borlaf-Mena ◽  
Maurizio Santoro ◽  
Ludovic Villard ◽  
Ovidiu Badea ◽  
Mihai Andrei Tanase
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Digital Elevation Models ◽  
Shuttle Radar Topography Mission ◽  
Synthetic Aperture ◽  
Mountainous Regions ◽  
Aerial Laser Scanning ◽  
Digital Elevation ◽  
The Difference ◽  
The Impact

Spaceborne remote sensing can track ecosystems changes thanks to continuous and systematic coverage at short revisit intervals. Active remote sensing from synthetic aperture radar (SAR) sensors allows day and night imaging as they are not affected by cloud cover and solar illumination and can capture unique information about its targets. However, SAR observations are affected by the coupled effect of viewing geometry and terrain topography. The study aims to assess the impact of global digital elevation models (DEMs) on the normalization of Sentinel-1 backscattered intensity and interferometric coherence. For each DEM, we analyzed the difference between orbit tracks, the difference with results obtained with a high-resolution local DEM, and the impact on land cover classification. Tests were carried out at two sites located in mountainous regions in Romania and Spain using the SRTM (Shuttle Radar Topography Mission, 30 m), AW3D (ALOS (Advanced Land Observation Satellite) World 3D, 30 m), TanDEM-X (12.5, 30, 90 m), and Spain national ALS (aerial laser scanning) based DEM (5 m resolution). The TanDEM-X DEM was the global DEM most suitable for topographic normalization, since it provided the smallest differences between orbital tracks, up to 3.5 dB smaller than with other DEMs for peak landform, and 1.4–1.9 dB for pit and valley landforms.

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