scholarly journals Accuracy Comparison and Assessment of DSM Derived from GFDM Satellite and GF-7 Satellite Imagery

2021 ◽  
Vol 13 (23) ◽  
pp. 4791
Author(s):  
Xiaoyong Zhu ◽  
Xinming Tang ◽  
Guo Zhang ◽  
Bin Liu ◽  
Wenmin Hu
Keyword(s):  
Satellite Imagery ◽  
Reference Data ◽  
Surface Model ◽  
Optical Remote Sensing ◽  
Control Points ◽  
Ground Control Points ◽  
Accuracy Comparison ◽  
Vertical Accuracy ◽  
High Resolution Satellite Imagery ◽  
Slight Advantage

Digital Surface Model (DSM) derived from high resolution satellite imagery is important for various applications. GFDM is China’s first civil optical remote sensing satellite with multiple agile imaging modes and sub-meter resolution. Its panchromatic resolution is 0.5 m and 1.68 m for multi-spectral images. Compared with the onboard stereo viewing instruments (0.8 m for forward image, 0.65 m for back image, and 2.6 m for back multi-spectrum images) of GF-7, a mapping satellite of China in the same period, their accuracy is very similar. However, the accuracy of GFDM DSM has not yet been verified or fully characterized, and the detailed difference between the two has not yet been assessed either. This paper evaluates the DSM accuracy generated by GFDM and GF-7 satellite imagery using high-precision reference DSM and the observations of Ground Control Points (GCPs) as the reference data. A method to evaluate the DSM accuracy based on regional DSM errors and GCPs errors is proposed. Through the analysis of DSM subtraction, profile lines, strips detection and residuals coupling differences, the differences of DSM overall accuracy, vertical accuracy, horizontal accuracy and the strips errors between GFDM DSM and GF-7 DSM are evaluated. The results show that the overall accuracy of both is close while the vertical accuracy is slightly different. When regional DSM is used as the benchmark, the GFDM DSM has a slight advantage in elevation accuracy, but there are some regular fluctuation strips with small amplitude. When GCPs are used as the reference, the elevation Root Mean Square Error (RMSE) of GFDM DSM is about 0.94 m, and that of GF-7 is 0.67 m. GF-7 DSM is more accurate, but both of the errors are within 1 m. The DSM image residuals of the GF-7 are within 0.5 pixel, while the residuals of GFDM are relatively large, reaching 0.8 pixel.

scholarly journals Geometric Accuracy Study of Orthorectification Based on Sensor Model Refinement in Imagery Subset Using ORFEO Toolbox (OTB)

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Andri Suprayogi ◽  
Nurhadi Bashit
Keyword(s):  
Remote Sensing ◽  
Satellite Imagery ◽  
Ground Control ◽  
Surface Model ◽  
Control Points ◽  
Geometric Accuracy ◽  
Model Refinement ◽  
Full Extent ◽  
Sensor Model ◽  
Ground Control Points

Large scale base map can be obtained by various methods, one of them is orthorectification process of remote sensing satellite imagery to eliminate the relief displacement caused by height variation of earth surface. To obtain a  map images with good quality,  it requires additional data such as sensor model in the form of rational polynomial coefficients (RPC), surface model data, and ground control points Satellite imageries with high resolution  file size are relatively large.  In order to process them,  high specification of hardwares were required. To overcome this by cutting only a portion of the images, based on certain study areas were suffer from of georeference lost so it would not be able to orthorectified. On the other hand,  in several remote sensing software such as ESA SNAP and Orfeo Toolbox (OTB)  subset or pixel extraction from satellite imagery,  preserve the imagery geometric sensor models. This research aimed at geometric accuracy of orthorectification carried out in a single scene of Pleiades Imagery within the Kepahiang Subdistrict, located at Kepahiang Regency, Bengkulu Province, by using DEMNAS and the imagery refined sensor mode, and ground control points taken using GPS Survey. Related with the raw imagery condition which consists of Panchromatic and multispectral bands, this study were separated to assembly, pan sharpening , and sensor model refinement stages prior to orthorectification carried out both in the original or full extent imagery and the result of subset extent imagery. After  these processses taken place, we measure the accuracy of each full and subset imagery.These procedures were carried out using Orfeo toolbox 6.6.0 in the Linux Mint 19 Operating system. From the process log, running time in total  were 7814.518  second for the full extent and 4321.95 seconds for the subset processess. And as a big data process, the total of full extent imageries was 83.15 GB  while the subset size  was  only 30.73 GB.  The relative accuracy of the full extent and its subset imagery were 0.431 meters. Accuracy of the  sensor model refinement process are  1.217 meters and 1.550 meters with GCP added, while the accuracu of  the orthorectifications results were  0.416 meters and 0.751 meters by using ICP.  Variation of execution time may caused by the data input size and complexity of the mathematical process carried out in each stages. Meanwhile,  the variation of accuracy may  caused by the check or control points placements above satellite Imagery which suffer from uncertainty when dealing with  the sub-pixel position or under 0.5 meters.

scholarly journals Geometric Potential of Pléiades 1A Satellite Imagery

2014 ◽  
Vol 60 (3) ◽  
pp. 19-27 ◽  
Author(s):  
Andrii Postelniak
Keyword(s):  
Satellite Imagery ◽  
Surface Model ◽  
Stereo Pair ◽  
Strong Positive Correlation ◽  
Control Points ◽  
Shuttle Radar Topographic Mission ◽  
Sensor Model ◽  
Ground Control Points ◽  
Sensor Models ◽  
Bias Compensation

Abstract In this paper, the geometrical characteristics of Pléiades 1A satellite imagery (both single and stereo) are analysed. At first the process of digital surface model (DSM) extraction from a Pléiades 1A stereo pair is described and analysed. After that geometric an accuracy of imagery, orthorectified using the extracted DSM and using the SRTM (Shuttle radar topographic mission) was analysed. The Pléiades 1A stereo pair was acquired on October 22, 2012 from the same orbital pass over an urban zone (Kiev, Ukraine). The study area is heterogeneous: there are both built-up and flat areas. The iImage orientation, DSM extraction and orthorectified images generation were performed using the PCI Geomatica 2013 software. The results showed that a strong, positive correlation between reference-derived elevations and DSM-derived elevations can be observed, and the orthorectified image accuracy, generated using that DSM, approximately equal to 1 m can be achieved using a bias compensation sensor model. Different sensor models were used for orthorectification using the SRTM. In this case, the geometric accuracy is а function of a chosen sensor model and a number of ground control points (GCP).

scholarly journals On-Orbit Calibration of Installation Parameter of Multiple Star Sensors System for Optical Remote Sensing Satellite with Ground Control Points

2020 ◽  
Vol 12 (7) ◽  
pp. 1055
Author(s):  
Yanli Wang ◽  
Mi Wang ◽  
Ying Zhu
Keyword(s):  
Remote Sensing ◽  
Coordinate System ◽  
Statistical Characteristics ◽  
Optical Remote Sensing ◽  
Star Sensor ◽  
Control Points ◽  
Remote Sensing Images ◽  
Multiple Star ◽  
Ground Control Points ◽  
Combination Modes

Owing to the vibrations and thermal shocks that arise during the launch and orbit penetration process, the on-orbit installation parameters of multiple star sensors are different from the on-ground measured parameters, causing inconsistencies in the attitude determinations from different combination modes and seriously affecting the geometric accuracy of high-resolution optical remote sensing images. This study presents an on-orbit calibration approach for the installation parameters of a multiple star sensors system using ground control points (GCPs). Based on the on-ground installation parameters of the optical axes of conventional star sensors, a fiducial coordinate system is proposed as the calibration coordinate system. The installation parameters of the conventional star sensors are calibrated using the statistical characteristics of angles between axes of the star sensor and three fiducial vectors in the J2000 celestial coordinate system. Based on the GCPs, the relative fiducial parameters are calculated, and the installation parameter of unconventional star sensor is then calibrated with the relative fiducial parameters and statistical characteristics of angles. It can be used for high-resolution optical remote sensing satellite measuring with only two star sensors to unify the fiducial coordinate system. The proposed method is tested using simulated data and on-orbit measurement data. The results demonstrate that the proposed method can calibrate the optical axis of the star sensor without the restriction of the accuracy of horizontal axis. Moreover, the star sensor with a large installation angle error can be calibrated well using the proposed approach. The results of attitude determinations from different star sensor combination modes are consistent, and the geometric accuracy of the remote sensing images is significantly improved.

scholarly journals A Fast, Three-Dimensional, Indirect Geolocation Method Using IAGM and DSM Data without GCPs for Spaceborne SAR Images

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5062
Author(s):  
Liu ◽  
Xiao
Keyword(s):  
Corner Point ◽  
Three Dimensional ◽  
Surface Model ◽  
Control Points ◽  
Sar Image ◽  
Sar Images ◽  
Ground Control Points ◽  
The Earth ◽  
Proportional Relationship ◽  
Geolocation Accuracy

To determine the geolocation of a pixel for spaceborne synthetic aperture radar (SAR) images, traditional indirect geolocation methods can cause great computational complexity. In this paper, a fast, three-dimensional, indirect geolocation method without ground control points (GCPs) is presented. First, the Range-Doppler (RD) geolocation model with all the equations in the Earth-centered rotating (ECR) coordinate system is introduced. By using an iterative analytical geolocation method (IAGM), the corner point locations of a quadrangle SAR image on the Earth’s surface are obtained. Then, a three-dimensional (3D) grid can be built by utilizing the digital surface model (DSM) data in this quadrangle. Through the proportional relationship for every pixel in the 3D grid, the azimuth time can be estimated, which is the key to decreasing the calculation time of the Doppler centroid. The results show that the proposed method is about 12 times faster than the traditional method, and that it maintains geolocation accuracy. After acquiring the precise azimuth time, it is easy to obtain the range location. Therefore, the spaceborne SAR image can be geolocated to the Earth surface precisely based on the high-resolution DSM data.

scholarly journals Geometric Positioning for Satellite Imagery without Ground Control Points by Exploiting Repeated Observation

Sensors ◽  
2017 ◽  
Vol 17 (2) ◽  
pp. 240 ◽  
Author(s):  
Zhenling Ma ◽  
Xiaoliang Wu ◽  
Li Yan ◽  
Zhenliang Xu
Keyword(s):  
Satellite Imagery ◽  
Ground Control ◽  
Control Points ◽  
Ground Control Points ◽  
Repeated Observation

scholarly journals Winter mass balance of Drangajökull ice cap (NW Iceland) derived from satellite sub-meter stereo images

2016 ◽  
Author(s):  
Joaquín M. C. Belart ◽  
Etienne Berthier ◽  
Eyjólfur Magnússon ◽  
Leif S. Anderson ◽  
Finnur Pálsson ◽  
...  
Keyword(s):  
Mass Balance ◽  
Ground Control ◽  
Control Points ◽  
Stereo Images ◽  
Ice Cap ◽  
Ground Control Points ◽  
Digital Elevation ◽  
Lidar Dem ◽  
Vertical Accuracy ◽  
Annual Time

Abstract. Sub-meter resolution satellite stereo images allow the generation of high resolution, accurate digital elevation models (DEMs). Repeated acquisitions of stereo images from Pléiades, in October 2014 and May 2015, and from WorldView2 (WV2), in February 2015, over Drangajökull ice cap (NW-Iceland) are used to estimate the geodetic glacier-wide mass balance on sub-annual time scales. Relative adjustment of the DEMs is performed with and without a pre-existing lidar DEM as source of ground control points (GCPs), and resulting statistics in snow-free and ice-free areas reveal similar vertical accuracy

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