scholarly journals Optimization of Ground Control Point (GCP) and Independent Control Point (ICP) on Orthorectification of High Resolution Satellite Imagery

2019 ◽  
Vol 94 ◽  
pp. 02008
Author(s):  
Teguh Hariyanto ◽  
Akbar Kurniawan ◽  
Cherie Bhekti Pribadi ◽  
Rizal Al Amin
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Survey Methods ◽  
Control Point ◽  
Satellite Image ◽  
Geometric Distortion ◽  
Ground Control ◽  
Geometric Correction ◽  
Space Utilization ◽  
Ground Control Point

In the rapidly evolving technology era, various survey methods have been widely used one of them by remote sensing using satellite. It is known that the satellite image recording process is covered by rides (satellites) moving over the Earth's surface at hundreds of kilometers, causing satellite imagery to have geometric distortion. To reduce the effect of geometric distortion of objects on the image, geometric correction by orthorectification is done. Pleiades is a satellite of high resolution satellite image producer made by Airbus Defense & Space company. The resulting satellite imagery has a 0.5 meter spatial resolution. As a reference for the more detailed space utilization activities of space utilization arranged in the Regional Spatial Plans, Detailed Spatial Plans was created with the 1: 5000 scale map which has been governed by the Geospatial Information Agency. In the process of orthorectifying satellite imagery for this 1: 5000 scale map, ground control or Ground Control Point (GCP) is used for geometric correction and Digital Elevation Model (DEM) data. In this research, the optimal number of GCP usage for orthorectification process in Rational Function method is 21 GCP using 2nd order polynomial

An Optimization Method on Ground Control Point Distribution

2011 ◽  
Vol 268-270 ◽  
pp. 1092-1095
Author(s):  
Guang Yang ◽  
Wei Li Jiao
Keyword(s):  
Remote Sensing ◽  
Control Point ◽  
Optimization Method ◽  
Ground Control ◽  
Geometric Correction ◽  
Importance Value ◽  
Point Distribution ◽  
Ground Control Point ◽  
Thiessen Polygon ◽  
Automatic Optimization

With the development of remote sensing, the data quantity of remote sensing image is increasing tremendously. It brings a huge workload to the image geometric correction through manual ground control point (GCP) selection. GCPs automatically selected based on software is one of the effective methods to cut down manual operation. The GCPs obtained from that way is generally redundant. This paper deeply comprehends some existing methods about automatic optimization of GCP, and puts forward a new method of automatic optimization of GCP based on Thiessen Polygon to filter ground control points from the overfull ones without manual subjectivity for better accuracy. Experiments in this paper also demonstrated the relationship between the accuracy of geometric correction and the distribution of GCP. It advances the conception of single GCP’s importance value based on Thiessen Polygon. The paper gives the theory and the flow of automatic optimization of GCPs as well. It also presents an example of the application of this method. In the conclusion, this paper points out the advantages of this method .

Robust ground control point-matching algorithm for multichannel radar image geometric correction

2003 ◽  
Author(s):  
Gennady P. Kulemin ◽  
Andrei A. Kurekin ◽  
Alexander A. Zelensky ◽  
Vladimir V. Lukin
Keyword(s):  
Control Point ◽  
Radar Image ◽  
Ground Control ◽  
Geometric Correction ◽  
Point Matching ◽  
Ground Control Point ◽  
Matching Algorithm

Monitoring of a landslide through the use of UAV survey

2020 ◽  
Author(s):  
Simone Pillon ◽  
Davide Martinucci ◽  
Annelore Bezzi ◽  
Giulia Casagrande ◽  
Giorgio Fontolan ◽  
...  
Keyword(s):  
High Resolution ◽  
Control Point ◽  
Ground Control ◽  
Surface Model ◽  
Ground Control Point ◽  
North East ◽  
Active Portion ◽  
High Resolution Images ◽  
Precise Assessment ◽  
Friuli Venezia Giulia

<p>The monitoring of landslides using UAVs is particularly convenient as these are dangerous areas that present access difficulties. This study aims to integrate monitoring carried out via traditional techniques (GNSS and total station surveys of benchmarks) with UAV photogrammetric survey, as the latter allows for a precise assessment of the volumes affected by movement. The Masarach landslide, located in Friuli Venezia Giulia (north east Italy), covers an area of approximately 200 ha. Two surveys were carried out two years apart in order to measure displacements of much greater magnitude than instrumental errors. In the first survey, restricted to the most active area, a six rotor UAV was used, with a maximum take-off mass of 4 kg, which carried a 20 Mpixel APS-C camera. 243 high resolution images were captured and 27 GCPs (Ground Control Point) were surveyed with a GNSS RTK reciever. In the second survey a DJI Phantom 4 Pro UAV was used, carrying a 20 Mpixel 1“ sensor camera. 978 high resolution images were captured and 40 GCPs (Ground Control Point) were surveyed with a GNSS RTK reciever. Data were analyzed using Agisoft Metashape Professional to produce an orthophoto and a DSM (Digital Surface Model) with a ground resolution of 0.02 m and 0.04 m respectively. The DSMs were compared in ArcGIS to calculate the moving masses and highlight the areas of greatest instability. It emerged that approximately 10,000 cubic meters of landslide material were transported to the Arzino stream below, with verified displacements on the control point ranging from meters to centimeters. This work made it possible to accurately define the most active portion of the landslide.</p>

VERY HIGH RESOLUTION SATELLITE IMAGERY UTILIZATION STANDARD FOR LARGE SCALE TOPOGRAPHIC MAPPING

2021 ◽  
pp. 939
Author(s):  
Winhard Tampubolon ◽  
Wolfgang Reinhardt ◽  
Franz Josef Behr
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Large Scale ◽  
Local Coordinate System ◽  
Control Point ◽  
Least Square ◽  
Topographic Mapping ◽  
Geometric Correction ◽  
High Resolution Satellite Imagery ◽  
Very High

Due to its large area Large Scale Topographic Mapping (LSTM) for Indonesia requires acceleration strategies that must be innovative enough to take into account the production efficiency. Satellite-based technologies are still a preferable choice especially in conjunction with the security clearance and weather. Standards for the Very High-Resolution Satellite Imagery (VHRS) utilization are essential, especially in a situation where there are so many available sensors and processing methods implemented. Hence, the selection of a proper geometric correction method is fundamental in order to utilize the VHRS imagery as one source of geospatial data especially for LSTM production and updating purposes. For CSRT geometric correction, an orthorectification process is required, where this process requires input data from the Ground Control Point (TKT) and the Digital Elevation Model (DEM). Therefore, the Least Square Adjustment (LSA) method is implemented to be able to include 8-9 GCPs per-scene (orbital and sensor parameters) and the DEM with a maximum resolution 4 times of the VHRS imagery’s Ground Sampling Distance (GSD) in the process of producing VHRS orthoimages. In addition, the role of orbital and sensor parameters is also essential for the geometric correction because its relation to the Direct Georeferencing (DG) of each pixel by Rigorous Sensor Model (RSM) approach. However, in the situation where the reliable orbital and sensor parameters are not available, the Rational Function Model (RFM) can be used as an alternative solution for the geometric correction of VHRS imagery. This paper discusses the VHRS utilization with a comprehensive approach that can be implemented in a local coordinate system i.e. the Indonesian Geospatial Reference System for the production of the reliable VHRS imageries.

scholarly journals Urban Mapping Accuracy Enhancement in High-Rise Built-Up Areas Deployed by 3D-Orthorectification Correction from WorldView-3 and LiDAR Imageries

2019 ◽  
Vol 11 (6) ◽  
pp. 692 ◽  
Author(s):  
Hossein Rizeei ◽  
Biswajeet Pradhan
Keyword(s):  
Control Point ◽  
Satellite Image ◽  
Ground Control ◽  
Surface Model ◽  
Lidar Data ◽  
Ground Control Point ◽  
Combination Technique ◽  
High Rise ◽  
Urban Mapping ◽  
Very High

Orthorectification is an important step in generating accurate land use/land cover (LULC) from satellite imagery, particularly in urban areas with high-rise buildings. Such buildings generally appear as oblique shapes on very-high-resolution (VHR) satellite images, which reflect a bigger area of coverage than the real built-up area on LULC mapping. This drawback can cause not only uncertainties in urban mapping and LULC classification, but can also result in inaccurate urban change detection. Overestimating volume or area of high-rise buildings has a negative impact on computing the exact amount of environmental heat and emission. Hence, in this study, we propose a method of orthorectfiying VHR WorldView-3 images by integrating light detection and ranging (LiDAR) data to overcome the aforementioned problems. A 3D rational polynomial coefficient (RPC) model was proposed with respect to high-accuracy ground control points collected from the LiDAR data derived from the digital surface model. Multiple probabilities for generating an orthrorectified image from WV-3 were assessed using 3D RCP model to achieve the optimal combination technique, with low vertical and horizontal errors. Ground control point (GCPs) collection is sensitive to variation in number and data collection pattern. These steps are important in orthorectification because they can cause the morbidity of a standard equation, thereby interrupting the stability of 3D RCP model by reducing the accuracy of the orthorectified image. Hence, we assessed the maximum possible scenarios of resampling and ground control point collection techniques to bridge the gap. Results show that the 3D RCP model accurately orthorectifies the VHR satellite image if 20 to 100 GCPs were collected by convenience pattern. In addition, cubic conventional resampling algorithm improved the precision and smoothness of the orthorectified image. According to the root mean square error, the proposed combination technique enhanced the vertical and horizontal accuracies of the geo-positioning process to up to 0.8 and 1.8 m, respectively. Such accuracy is considered very high in orthorectification. The proposed technique is easy to use and can be replicated for other VHR satellite and aerial photos.

EVALUASI KETELITIAN HORIZONTAL DARI CITRA TEGAK SATELIT RESOLUSI SANGAT TINGGI MENGGUNAKAN SRTM DAN TERRASAR-X UNTUK PEMETAAN SKALA BESAR

2018 ◽  
Vol 2 ◽  
pp. 535
Author(s):  
Maundri Prihanggo
Keyword(s):  
Control Point ◽  
Ground Control ◽  
Surface Model ◽  
Digital Surface Model ◽  
Check Point ◽  
Ground Control Point

<p>Saat ini, citra satelit resolusi sangat tinggi digunakan dalam berbagai macam aplikasi, terutama pemetaan skala besar. Sebelum dapat digunakan, citra satelit tersebut harus diorthorektifikasi terlebih dahulu. Data <em>Digital Surface Model </em>(DSM) dan <em>Ground Control Point</em> (GCP) adalah dua data utama yang diperlukan saat melakukan orthorektifikasi. Perbedaan data DSM yang digunakan akan menghasilkan perbedaan nilai ketelitian horizontal pada kedua citra tegak hasil orthorektifikasi. Pada penelitian ini digunakan dua jenis DSM yaitu SRTM dan Terrasar-X. Ketelitian vertikal dari SRTM adalah 90 m sedangkan ketelitian vertikal dari Terrasar-X adalah 12,5 m. Penelitian ini berlokasi di Wilayah Buli, Kabupaten Halmahera Timur, Provinsi Maluku. Terdapat tiga sensor citra satelit yang digunakan yaitu Pleiades, Quickbird dan Worldview-2 yang digunakan pada lokasi penelitian. Total GCP yang digunakan adalah 33 titik, tiap titiknya diukur dengan melakukan pengamatan geodetik dan memiliki ketelitian horizontal ≤15 cm dan ketelitian vertikal ≤30 cm. Ketelitian horizontal dari citra tegak satelit resolusi sangat tinggi diperoleh dengan melakukan uji terhadap Independent Check Point (ICP). Total ICP yang digunakan adalah 12 titik, tiap titik ICP diukur dengan metode dan standar yang sama dengan titik GCP. Ketelitian horizontal dengan Circular Error (CE 90) dari citra tegak satelit menggunakan data SRTM adalah 18,856 m sedangkan ketelitian horizontal dengan Circular Error (CE 90) dari citra tegak satelit menggunakan data Terrasar-X adalah 2.168 m . Hasil dari penelitian ini membuktikan bahwa ketelitian vertikal data DSM yang digunakan memberikan pengaruh pada citra tegak satelit hasil orthorektifikasi tersebut. Mengacu pada Peraturan Kepala BIG nomor 15 tahun 2014, citra tegak satelit hasil orthorektifikasi menggunakan data Terrasar-X sebagai DSM memenuhi ketelitian horizontal peta dasar kelas 3 skala 1:5.000 sedangkan citra tegak satelit hasil orthorektifikasi menggunakan data SRTM sebagai DSM tidak dapat memenuhi ketelitian horizontal peta dasar skala besar.</p><p><strong>Kata kunci:</strong> orthorektifikasi, DSM, ketelitian horizontal</p>

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