Open AccessBlock Adjustment of Large-scale Domestic Optical Satellite Remote Sensing Imagery without GCP in Antarctic
Author(s) -
Yi Wang,
Mingyuan He,
Jie Xiang,
Junxiang Ge
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/428/1/012082
Subject(s) - remote sensing , pixel , residual , block (permutation group theory) , computer science , satellite , satellite imagery , mean squared error , scale (ratio) , image resolution , artificial intelligence , computer vision , algorithm , geography , mathematics , cartography , engineering , statistics , geometry , aerospace engineering
Aiming to the difficult area of surveying and mapping, such as Antarctic, it is difficult to guarantee favourable observation condition for traditional mapping methods. Large-scale block adjustment (BA) without ground control point (GCP) is carried out by using domestic high-resolution satellite remote sensing imagery. The key technologies of BA model construction based on virtual control point (VCP), gross error detection and elimination, and robust and fast method of large-scale BA are studied in this paper. On this basis, the experimental analysis and validation of 13pairs (39 images) of ZY-3 satellite imagery in Antarctic are carried out. The results show that the sparse matrix technology can effectively reduce the memory requirement. The combined matrix block and GPU parallel technology can solve the problem of large-scale BA computational efficiency. In addition, after BA, the maximum residual is 3.920 pixel, the root mean square error (RMSE) is 0.169 pixel in the X (flight) direction, the maximum residual error is 5.933 pixel, and the RMSE is 0.191 pixel in the Y (scan) direction. The proposed method has certain accuracy and stability in large-scale BA without GCP using high-resolution satellite remote sensing imagery in Antarctica. The relative positioning accuracy can reach sub-pixel level, which can meet the requirements of cartographic splicing.