scholarly journals EVALUATION AND ANALYSIS OF A PARAMETRIC APPROACH FOR SIMULTANEOUS SPACE RESECTION-INTERSECTION OF HIGH RESOLUTION SATELLITE IMAGES WITHOUT USING GROUND CONTROL POINTS

2013 ◽  
Vol XL-1/W3 ◽  
pp. 61-66
Author(s):  
A. Azizi ◽  
H. Afsharnia ◽  
A. Hadavand
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
Ground Control ◽  
Control Points ◽  
Parametric Approach ◽  
Ground Control Points ◽  
High Resolution Satellite Images

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 Avaliação de Desempenho no Georreferenciamento de Imagens do Sensor HR CCD (High Resolution Charge-Coupled Device) do Satélite CBERS-1

2005 ◽  
Vol 32 (2) ◽  
pp. 81
Author(s):  
RAFAEL PEREIRA ZANARDI ◽  
SILVIA BEATRIZ ALVES ROLIM ◽  
CLÁUDIO BIELENKI JÚNIOR ◽  
CARLOS ALUISIO MESQUITA DE ALMEIDA
Keyword(s):  
High Resolution ◽  
Geometric Transformation ◽  
Ground Control ◽  
Control Points ◽  
Differential Gps ◽  
Charge Coupled Device ◽  
Qualitative And Quantitative ◽  
Ground Control Points ◽  
Sampling Points ◽  
Nearest Neighborhood

In this work it was analyzed the validation of CBERS-1 (China and Brazillian Earth Resourses Satellite) data related to qualitative and quantitative parameters that define the precision of its georeferencing. A topographical survey was carried out for the acquisition of ground control points spatially well distributed in the study area, employing differential GPS, aiming at the georeferencing of the image. Tests with different numbers of sampling points and several methods of Geometric Transformation and Resampling were made during the georeferencing. These results were statistically analyzed to determine the best method to georeference CBERS-1 images. It was verified that the first-degree polinomial transformation with nearest neighborhood resampling presented the best result, showing a precision of 18,52m.

scholarly journals DESARROLLO DE UNA METODOLOGÍA SENCILLA PARA LA GEORREFERENCIACIÓN Y MEDICIÓN DE DISTANCIAS A PARTIR DE IMÁGENES DE SATÉLITE SISTEMÁTICAMENTE GEORREFERENCIADAS

2016 ◽  
Vol 39 (1) ◽  
Author(s):  
Leonardo Gónima ◽  
Libardo E. Ruiz ◽  
Marcos E. González
Keyword(s):  
Satellite Images ◽  
Control Point ◽  
Ground Control ◽  
Gps Data ◽  
Control Points ◽  
Statistical Validation ◽  
Distance Measurements ◽  
The North ◽  
Ground Control Points ◽  
Representative Points

One of the main problems for a precise georeferencing and distance measurements from satellite images, especially in geographical zones with strong morphologic and environmental dynamics, lies not only in the difficulty for identifying ground control points (GCPs), but also in real limitations for accessing such places. In this work a relatively simple methodology is proposed for georeferencing and distance measuring from satellite images, based on the utilization of previously calculated reflectance images from the surface and then oriented toward the north (systematic georeferencing). From these images and setting a basic control point (pixel) P, measured with GPS, the other GCPs were obtained by measurements of distances defined from the P point to representative points (pixels) on the image, selected for its georeferencing. The statistical validation of the obtained results, using a different sample of GCPs measured with GPS, shows that the precision of the georeferencing and distance measurement utilizing the developed methodology is similar to that obtained by conventional procedures, such as image georeferencing from GPS data.

scholarly journals Matching Confidence Constrained Bundle Adjustment for Multi-View High-Resolution Satellite Images

2019 ◽  
Vol 12 (1) ◽  
pp. 20 ◽  
Author(s):  
Xiao Ling ◽  
Xu Huang ◽  
Yongjun Zhang ◽  
Gang Zhou
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
State Of The Art ◽  
Bundle Adjustment ◽  
Adjustment Process ◽  
Unified Framework ◽  
Adjustment Method ◽  
Ground Control Points ◽  
High Resolution Satellite Images ◽  
Experimental Comparisons

Bundle adjustment of multi-view satellite images is a powerful tool to align the orientations of all the images in a unified framework. However, the traditional bundle adjustment process faces a problem in detecting mismatches and evaluating low/medium/high-accuracy matches, which limits the final bundle adjustment accuracy, especially when the mismatches are several times more than the correct matches. To achieve more accurate bundle adjustment results, this paper formulates the prior knowledge of matching accuracy as matching confidences and proposes a matching confidence based bundle adjustment method. The core algorithm firstly selects several highest-confidence matches to initially correct orientations of all images, then detects and eliminates the mismatches under the initial orientation guesses and finally formulates both the matching confidences and the forward-backward projection errors as weights in an iterative bundle adjustment process for more accurate orientation results. We compared our proposed method with the famous RANSAC strategy as well as a state-of-the-art bundle adjustment method on the high-resolution multi-view satellite images. The experimental comparisons are evaluated by image checking points and ground control points, which shows that our proposed method is able to obtain more robust and more accurate mismatch detection results than the RANSAC strategy, even though the mismatches are four times more than the correct matches and it can also achieve more accurate orientation results than the state-of-the-art bundle adjustment method.

scholarly journals Accuracy of DSM By Using Unmanned Aerial Vehicles on the Downstream of Welang Riverbank, District of Pasuruan, Jawa Timur

UKaRsT ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 49
Author(s):  
Dian Wahyu Khaulan ◽  
Entin Hidayah ◽  
Gusfan Halik
Keyword(s):  
High Resolution ◽  
Vertical Direction ◽  
Sufficient Accuracy ◽  
Ground Control ◽  
Surface Model ◽  
Control Points ◽  
Digital Surface Model ◽  
Ground Control Points ◽  
Aerial Vehicle ◽  
Topography Data

The Digital Surface Model (DSM) is commonly used in studies on flood map modeling. The lack of accurate, high-resolution topography data has hindered flood modeling. The use of the Unmanned Aerial Vehicle (UAV) can help data acquisition with sufficient accuracy. This research aims to provide high-resolution DSM-generated maps by Ground Control Points (GCPs) settings. Improvement of the model's accuracy was pursued by distributing 20 GCPs along the edges of the study area. Agrisoft software was used to generate the DSM. The generated DSM can be used for various planning purposes. The model's accuracy is measured in Root Mean Square Error (RMSE) based on the generated DSM. The RMSE values are 0.488 m for x-coordinates and y-coordinates (horizontal direction) and 0.161 m for z-coordinates (vertical direction).

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