scholarly journals KOMPSAT-3 Digital Elevation Model Correction Based on Point-to-Surface Matching

2019 ◽  
Vol 11 (20) ◽  
pp. 2340 ◽  
Author(s):  
Hyoseong Lee ◽  
Michael Hahn
Keyword(s):  
Satellite Images ◽  
Surface Matching ◽  
Control Points ◽  
Polynomial Coefficients ◽  
Ground Control Points ◽  
Rational Polynomial ◽  
Digital Elevation ◽  
High Resolution Satellite Images ◽  
Coordinate Measurements ◽  
Elevation Model

In order to generate digital elevation models (DEMs) from high-resolution satellite images, the vendor-provided rational polynomial coefficients (RPCs) are commonly used. This results in a level of accuracy that can be improved by using ground control points (GCPs). The integration of the GCPs into the processing chain is associated with additional effort, since it requires the provision of GCPs as well as the measurement of its image coordinates. In this paper, the authors avoid the measurement of GCP image coordinates and propose a point-to-surface matching method to correct the DEM produced from KOMPSAT-3 satellite images and the provided RPCs. For point-to-surface matching, an existing network of GCPs was used in South Korea, the so-called united control points and the triangulation control points. Practical testing was summarized with the proposed method in which the root mean square error with respect to the horizontal position and the height reduced from 20 m and 6 m to 3 m and 2 m, respectively. This demonstrates that neither image coordinate measurements nor additional GCP point acquisition, e.g., by GPS, are necessary to convert a DEM generated from KOMPSAT-3 images and vendor-provided RPCs into a highly accurate DEM by using existing GCPs and point-to-surface matching.

scholarly journals POINT-TO-SURFACE MATCHING FOR DEM CORRECTION USING ICESAT DATA

2020 ◽  
Vol XLIII-B4-2020 ◽  
pp. 715-720
Author(s):  
H. Lee ◽  
M. Hahn
Keyword(s):  
Satellite Images ◽  
Experimental Investigations ◽  
Surface Matching ◽  
Satellite Mission ◽  
Polynomial Coefficients ◽  
Rational Polynomial ◽  
Sensor Orientation ◽  
Digital Elevation ◽  
High Resolution Satellite Images ◽  
Starting Point

Abstract. Vendor-provided rational polynomial coefficients (RPCs) are commonly used to generate digital elevation models (DEMs) from high-resolution satellite images. This results in a level of accuracy that can be improved using ground control points (GCPs). It is well known that due to the inherent bias of sensor orientation the generated DEM is distorted. In the traditional way of working, the bias is corrected by integrating GCPs into the standard processing chain. This involves additional effort, since the provision of GCPs and the measurement of their image coordinates are required.In this paper, we examine whether and how the data recorded by NASA's ICESat (Ice, Cloud, and Land Elevation Satellite) mission can be used as GCPs without measuring image coordinates. The starting point are DEMs that are generated by image matching from KOMPSAT-3 satellite images with given RPCs. We developed a point-to-surface matching method that matches the ICESat points to the DEM in order to correct the DEM and improve its precision. For the experimental investigations a KOMPSAT 3 image pair is used that covers an area of 20 by 16 km2 in the Yangsan city regions. The generated DEM has a height accuracy of about 9 m. The point-to-surface algorithm with 505 ICESat points led to an improvement of the DEM height accuracy to about 2 m.

scholarly journals THE RATIONAL POLYNOMIAL COEFFICIENTS MODIFICATION USING DIGITAL ELEVATION MODELS

2015 ◽  
Vol XL-1-W5 ◽  
pp. 47-50 ◽  
Author(s):  
F. Alidoost ◽  
A. Azizi ◽  
H. Arefi
Keyword(s):  
Point Cloud ◽  
Digital Elevation Models ◽  
Ground Control ◽  
Control Points ◽  
Polynomial Coefficients ◽  
Ground Control Points ◽  
Rational Polynomial ◽  
Digital Elevation ◽  
Elevation Model ◽  
Parameters Calculation

The high-resolution satellite imageries (HRSI) are as primary dataset for different applications such as DEM generation, 3D city mapping, change detection, monitoring, and deformation detection. The geo-location information of HRSI are stored in metadata called Rational Polynomial Coefficients (RPCs). There are many methods to improve and modify the RPCs in order to have a precise mapping. In this paper, an automatic approach is presented for the RPC modification using global Digital Elevation Models. The main steps of this approach are: relative digital elevation model generation, shift parameters calculation, sparse point cloud generation and shift correction, and rational polynomial fitting. Using some ground control points, the accuracy of the proposed method is evaluated based on statistical descriptors in which the results show that the geo-location accuracy of HRSI can be improved without using Ground Control Points (GCPs).

scholarly journals Correction of Very High-Resolution Satellite Images using Control Points Captured by Web Map Service (WMS) server: Google Earth

2020 ◽  
Vol 9 (8) ◽  
pp. 188-194
Keyword(s):  
Large Scale ◽  
Satellite Images ◽  
Google Earth ◽  
Ground Control ◽  
Control Points ◽  
Web Map ◽  
Ground Control Points ◽  
High Resolution Satellite Images ◽  
Map Scale ◽  
Map Service

The recent progress for spatial resolution of remote sensing imagery led to generate many types of Very HighResolution (VHR) satellite images, consequently, general speaking, it is possible to prepare accurate base map larger than 1:10,000 scale. One of these VHR satellite image is WorldView-3 sensor that launched in August 2014. The resolution of 0.31m makes WorldView-3 the highest resolution commercial satellite in the world. In the current research, a pan-sharpen image from that type, covering an area at Giza Governorate in Egypt, used to determine the suitable large-scale map that could be produced from that image. To reach this objective, two different sources for acquiring Ground Control Points (GCPs). Firstly, very accurate field measurements using GPS and secondly, Web Map Service (WMS) server (in the current research is Google Earth) which is considered a good alternative when GCPs are not available, are used. Accordingly, three scenarios are tested, using the same set of both 16 Ground Control Points (GCPs) as well as 14 Check Points (CHKs), used for evaluation the accuracy of geometric correction of that type of images. First approach using both GCPs and CHKs coordinates acquired by GPS. Second approach using GCPs coordinates acquired by Google Earth and CHKs acquired by GPS. Third approach using GCPs and CHKs coordinates by Google Earth. Results showed that, first approach gives Root Mean Square Error (RMSE) planimeteric discrepancy for GCPs of 0.45m and RMSE planimeteric discrepancy for CHKs of 0.69m. Second approach gives RMSE for GCPs of 1.10m and RMSE for CHKs of 1.75m. Third approach gives RMSE for GCPs of 1.10m and RMSE for CHKs of 1.40m. Taking map accuracy specification of 0.5mm of map scale, the worst values for CHKs points (1.75m&1,4m) resulted from using Google Earth as a source, gives the possibility of producing 1:5000 large-scale map compared with the best value of (0.69m) (map scale 1:2500). This means, for the given parameters of the current research, large scale maps could be produced using Google Earth, in case of GCPs are not available accurately from the field surveying, which is very useful for many users.

scholarly journals GEOMETRIC STITCHING METHOD FOR DOUBLE CAMERAS WITH WEAK CONVERGENCE GEOMETRY

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 71-74
Author(s):  
N. Zhou ◽  
H. He ◽  
Y. Bao ◽  
C. Yue ◽  
K. Xing ◽  
...  
Keyword(s):  
Weak Convergence ◽  
Relative Orientation ◽  
Test Results ◽  
Polynomial Coefficients ◽  
Aster Gdem ◽  
Rational Polynomial ◽  
Digital Elevation ◽  
Transform Coefficients ◽  
Elevation Model ◽  
Orientation Parameters

In this paper, a new geometric stitching method is proposed which utilizes digital elevation model (DEM)-aided block adjustment to solve relative orientation parameters for dual-camera with weak convergence geometry. A rational function model (RFM) with affine transformation is chosen as the relative orientation model. To deal with the weak geometry, a reference DEM is used in this method as an additional constraint in the block adjustment, which only calculates the planimetry coordinates of tie points (TPs). After that we can use the obtained affine transform coefficients to generate virtual grid, and update rational polynomial coefficients (RPCs) to complete the geometric stitching. Our proposed method was tested on GaoFen-2(GF-2) dual-camera panchromatic (PAN) images. The test results show that the proposed method can achieve an accuracy of better than 0.5 pixel in planimetry and have a seamless visual effect. For regions with small relief, when global DEM with 1 km grid, SRTM with 90 m grid and ASTER GDEM V2 with 30 m grid replaced DEM with 1m grid as elevation constraint， it is almost no loss of accuracy. The test results proved the effectiveness and feasibility of the stitching method.

scholarly journals 3-D modelling and visualization of large building using photogrammetric approach

2021 ◽  
Author(s):  
Raad Awad Kattan ◽  
◽  
Farsat Heeto Abdulrahman ◽  
Sami Mamlook Gilyana ◽  
Yousif Youkhna Zaya ◽  
...  
Keyword(s):  
Bundle Adjustment ◽  
Ground Control ◽  
Control Points ◽  
Distance Measurements ◽  
Ground Control Points ◽  
Digital Elevation ◽  
Elevation Model ◽  
College Of Engineering ◽  
User Friendly ◽  
D Model

The progress in modern technologies such as precise lightweight cameras mounted on unmanned aerial vehicles (UAV) and the more user-friendly software in the photogrammetric field, allows for 3-D model construction of any structure or shape. Software now achieves in sequence the processes of matching, generating tie points, block bundle adjustment, and generating digital elevation models.The aim of this study is to make a virtual 3-D model of the college of engineering /University of Duhok. Kurdistan Region, Iraq. The data input is vertical and oblique imagery acquired by UAV, ground control points distributed on the surrounded ground, facades, and roof. Ground control points were measured by the GPS RTK system in addition to the reflectorless total station instrument. The data is processed mainly using Agisoft PhotoScan software as well as the Global Mapper and the ReCap software. The output is a 3-D model, digital elevation model, and orthomosaic.Geometric and visual inspections were carried out. Some imperfections appeared on the sharp edges and parapets of the building. In the geometric accuracy of selected points on the building, the maximum standard deviation in the coordinates was ±4cm. The relative accuracy in distance measurements were in the range of 0.72% to 4.92 %

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 GENERATION AND EVALUATION OF RADARGRAMMETRIC DEM FROM RADARSAT-1 STANDARD IMAGES IN LOW RELIEF AREA IN THE AMAZON COASTAL PLAIN

2014 ◽  
Vol 32 (3) ◽  
pp. 405 ◽  
Author(s):  
Edson Adjair de Souza Pereira ◽  
Pedro Walfir M. Souza-Filho ◽  
Waldir R. Paradella ◽  
Wilson Da Rocha Nascimento Jr.
Keyword(s):  
Coastal Plain ◽  
Geometric Modeling ◽  
Specific Model ◽  
Depth Information ◽  
Control Points ◽  
Ground Control Points ◽  
Digital Elevation ◽  
Imaging Mode ◽  
Elevation Model ◽  
Relief Area

ABSTRACT. The generation of digital elevation models (DEMs) from the Standard imaging mode of RADARSAT-1 stereo-images was investigated to evaluate theviability of producing 1:100,000 scale altimetric maps in areas with a low topographic relief on the Brazilian Amazon coastal plain. Absolute DEMs were generatedusing RADARSAT-1 Standard stereopairs (S2Asc/S1Des, S6Des/S1Des, and S7Asc/S6Des) with ground control points collected using a Differential Global Positioningsystem. The geometric modeling for the DEM extractions was based on the “RADARSAT Specific Model” from the OrthoEngine Satellite Edition of the PCI Geomaticasoftware; this model is an automated matching solution that considers the slant range distances from sensors and terrain. Thirteen independent control points were usedto validate the accuracy of the absolute DEM. Only the S2Asc/S1Des pair was effective in highlighting depth information, which was a result of the pair’s intermediateintersection angle (47◦) and higher vertical parallax ratio (4.31). Therefore, RADARSAT-1 Standard images are a useful alternative for generating absolute DEM at thescale of 1:100,000 in cartographic gap areas on the Amazon coastal plain.Keywords: digital elevation model, stereoscopy, RADARSAT-1, Amazon, Brazil. RESUMO. A geração de modelos digitais de elevação (MDEs) a partir de pares estereoscópicos RADARSAT-1 modo Standard foi empregada com o objetivo deavaliar a produção de mapa altimétrico na escala de 1:100.000 em uma área de baixo relevo na planície costeira amazônica. MDEs absolutos foram gerados usandopares estereoscópicos RADARSAT-1 Standard (S2Asc/S1Des, S6Des/S1Des e S7Asc/S6Des) com pontos de controle do terreno coletados usando-se um sistema deposicionamento global diferencial. Omodelamento geométrico para extração doMDE foi baseado no “Modelo Específico para o RADARSAT”, do programa PCIGeomatica, através do cálculo que maximiza o coeficiente de correlação e leva em consideração as distâncias no alcance inclinado entre o sensor e o terreno. Para a validação do MDE absoluto foram usados 13 pontos de controle independentes. Apenas o par S2Asc/S1Des foi eficaz no realce da informação de profundidade, devido aos ângulos de intersecção intermediários (47◦), mas principalmente, devido a maior razão da paralaxe vertical observada (4,31). Portanto, as imagens RADARSAT-1 Standard representam uma ótima alternativa para a produção de MDEs absolutos na escala de 1:100.000 em áreas com vazios cartográficos na planície costeira amazônica.Palavras-chave: modelo digital de elevação, estereoscopia, RADARSAT-1,Amazônia, Brasil.

scholarly journals A comprehensive transferability evaluation of U-Net and ResU-Net for landslide detection from Sentinel-2 data (case study areas from Taiwan, China, and Japan)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Omid Ghorbanzadeh ◽  
Alessandro Crivellari ◽  
Pedram Ghamisi ◽  
Hejar Shahabi ◽  
Thomas Blaschke
Keyword(s):  
Satellite Images ◽  
Patch Size ◽  
Window Size ◽  
Convolutional Network ◽  
Digital Elevation ◽  
High Resolution Satellite Images ◽  
Elevation Model ◽  
Very High ◽  
Sentinel 2

AbstractEarthquakes and heavy rainfalls are the two leading causes of landslides around the world. Since they often occur across large areas, landslide detection requires rapid and reliable automatic detection approaches. Currently, deep learning (DL) approaches, especially different convolutional neural network and fully convolutional network (FCN) algorithms, are reliably achieving cutting-edge accuracies in automatic landslide detection. However, these successful applications of various DL approaches have thus far been based on very high resolution satellite images (e.g., GeoEye and WorldView), making it easier to achieve such high detection performances. In this study, we use freely available Sentinel-2 data and ALOS digital elevation model to investigate the application of two well-known FCN algorithms, namely the U-Net and residual U-Net (or so-called ResU-Net), for landslide detection. To our knowledge, this is the first application of FCN for landslide detection only from freely available data. We adapt the algorithms to the specific aim of landslide detection, then train and test with data from three different case study areas located in Western Taitung County (Taiwan), Shuzheng Valley (China), and Eastern Iburi (Japan). We characterize three different window size sample patches to train the algorithms. Our results also contain a comprehensive transferability assessment achieved through different training and testing scenarios in the three case studies. The highest f1-score value of 73.32% was obtained by ResU-Net, trained with a dataset from Japan, and tested on China’s holdout testing area using the sample patch size of 64 × 64 pixels.

scholarly journals Structure-from-Motion on shallow reefs and beaches: potential and limitations of consumer-grade drones to reconstruct topography and bathymetry

Coral Reefs ◽  
2021 ◽  
Author(s):  
C. Gabriel David ◽  
Nina Kohl ◽  
Elisa Casella ◽  
Alessio Rovere ◽  
Pablo Ballesteros ◽  
...  
Keyword(s):  
Shallow Water ◽  
Structure From Motion ◽  
Water Levels ◽  
Aerial Photographs ◽  
Ground Control ◽  
Control Points ◽  
Ground Control Points ◽  
Digital Elevation ◽  
Nonlinear Distortions ◽  
Elevation Model

AbstractReconstructing the topography of shallow underwater environments using Structure-from-Motion—Multi View Stereo (SfM-MVS) techniques applied to aerial imagery from Unmanned Aerial Vehicles (UAVs) is challenging, as it involves nonlinear distortions caused by water refraction. This study presents an experiment with aerial photographs collected with a consumer-grade UAV on the shallow-water reef of Fuvahmulah, the Maldives. Under conditions of rising tide, we surveyed the same portion of the reef in ten successive flights. For each flight, we used SfM-MVS to reconstruct the Digital Elevation Model (DEM) of the reef and used the flight at low tide (where the reef is almost entirely dry) to compare the performance of DEM reconstruction under increasing water levels. Our results show that differences with the reference DEM increase with increasing depth, but are substantially larger if no underwater ground control points are taken into account in the processing. Correcting our imagery with algorithms that account for refraction did not improve the overall accuracy of reconstruction. We conclude that reconstructing shallow-water reefs (less than 1 m depth) with consumer-grade UAVs and SfM-MVS is possible, but its precision is limited and strongly correlated with water depth. In our case, the best results are achieved when ground control points were placed underwater and no refraction correction is used.

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