{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T15:52:43Z","timestamp":1776181963959,"version":"3.50.1"},"reference-count":95,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2021,9,6]],"date-time":"2021-09-06T00:00:00Z","timestamp":1630886400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shenzhen Special Project for Innovation and Entrepreneurship","award":["JSGG20191129103003903"],"award-info":[{"award-number":["JSGG20191129103003903"]}]},{"name":"Basic scientific research project of Chinese Academy of Surveying and Mapping","award":["AR2002 and AR2016"],"award-info":[{"award-number":["AR2002 and AR2016"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate geopositioning of optical satellite imagery is a fundamental step for many photogrammetric applications. Considering the imaging principle and data processing manner, SAR satellites can achieve high geopositioning accuracy. Therefore, SAR data can be a reliable source for providing control information in the orientation of optical satellite images. This paper proposes a practical solution for an accurate orientation of optical satellite images using SAR reference images to take advantage of the merits of SAR data. Firstly, we propose an accurate and robust multimodal image matching method to match the SAR and optical satellite images. This approach includes the development of a new structural-based multimodal applicable feature descriptor that employs angle-weighted oriented gradients (AWOGs) and the utilization of a three-dimensional phase correlation similarity measure. Secondly, we put forward a general optical satellite imagery orientation framework based on multiple SAR reference images, which uses the matches of the SAR and optical satellite images as virtual control points. A large number of experiments not only demonstrate the superiority of the proposed matching method compared to the state-of-the-art methods but also prove the effectiveness of the proposed orientation framework. In particular, the matching performance is improved by about 17% compared with the latest multimodal image matching method, namely, CFOG, and the geopositioning accuracy of optical satellite images is improved, from more than 200 to around 8 m.<\/jats:p>","DOI":"10.3390\/rs13173535","type":"journal-article","created":{"date-parts":[[2021,9,6]],"date-time":"2021-09-06T21:47:38Z","timestamp":1630964858000},"page":"3535","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":39,"title":["Exploiting High Geopositioning Accuracy of SAR Data to Obtain Accurate Geometric Orientation of Optical Satellite Images"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5765-4070","authenticated-orcid":false,"given":"Zhongli","family":"Fan","sequence":"first","affiliation":[{"name":"Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping (CASM), Beijing 100036, China"}]},{"given":"Li","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping (CASM), Beijing 100036, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4394-1989","authenticated-orcid":false,"given":"Yuxuan","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping (CASM), Beijing 100036, China"}]},{"given":"Qingdong","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping (CASM), Beijing 100036, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8766-0487","authenticated-orcid":false,"given":"Sisi","family":"Zlatanova","sequence":"additional","affiliation":[{"name":"Department of Built Environment, University of New South Wales (UNSW), Sydney 2052, Australia"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1016\/j.isprsjprs.2017.12.006","article-title":"Towards automatic SAR-optical stereogrammetry over urban areas using very high resolution imagery","volume":"138","author":"Qiu","year":"2018","journal-title":"ISPRS J. 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