{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T02:48:45Z","timestamp":1772765325821,"version":"3.50.1"},"reference-count":23,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2020,8,21]],"date-time":"2020-08-21T00:00:00Z","timestamp":1597968000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2019ZY33"],"award-info":[{"award-number":["2019ZY33"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2016ZCQ06"],"award-info":[{"award-number":["2016ZCQ06"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["41807500"],"award-info":[{"award-number":["41807500"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Optical remote sensing images can be used to monitor slope deformation in mountain regions. Abundant optical sensors onboard various platforms were designed to provide increasingly high spatial\u2013temporal resolution images at low cost; however, finding the best image pairs to derive slope deformation remains difficult. By selecting a location in the east Tibetan Plateau, this work used the co-registration of optically sensed images and correlation (COSI-Corr) method to analyze 402 Sentinel-2 images from August 2015 to February 2020, to quantify temporal patterns of uncertainty in deriving slope deformation. By excluding 66% of the Sentinel-2 images that were contaminated by unfavorable weather, uncertainties were found to fluctuate annually, with the least uncertainty achieved in image pairs of similar dates in different years. Six image pairs with the least uncertainties were selected to derive ground displacement for a moving slope in the study area. Cross-checks among these image pairs showed consistent results, with uncertainties less than 1\/10 pixels in length. The findings from this work could help in the selection of the best image pairs to derive reliable slope displacement from large numbers of optical images.<\/jats:p>","DOI":"10.3390\/s20174721","type":"journal-article","created":{"date-parts":[[2020,8,21]],"date-time":"2020-08-21T09:21:51Z","timestamp":1598001711000},"page":"4721","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Selecting the Best Image Pairs to Measure Slope Deformation"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7253-7814","authenticated-orcid":false,"given":"Wentao","family":"Yang","sequence":"first","affiliation":[{"name":"Three-Gorges Reservoir Area (Chongqing) Forest Ecosystem Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2357","DOI":"10.1007\/s10346-018-1037-6","article-title":"Spatial and temporal analysis of a fatal landslide inventory in China from 1950 to 2016","volume":"15","author":"Lin","year":"2018","journal-title":"Landslides"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1130\/G33217.1","article-title":"Global patterns of loss of life from landslides","volume":"40","author":"Petley","year":"2012","journal-title":"Geology"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.geomorph.2015.03.016","article-title":"Spatial and temporal analysis of a global landslide catalog","volume":"249","author":"Kirschbaum","year":"2015","journal-title":"Geomorphology"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"105436","DOI":"10.1016\/j.enggeo.2019.105436","article-title":"Quantification of human vulnerability to earthquake-induced landslides using Bayesian network","volume":"265","author":"Zhang","year":"2020","journal-title":"Eng. Geol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1038\/s41561-019-0444-1","article-title":"Earthquake-triggered 2018 Palu Valley landslides enabled by wet rice cultivation","volume":"12","author":"Bradley","year":"2019","journal-title":"Nat. Geosci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1038\/s41561-019-0500-x","article-title":"Irrigation-triggered landslides in a Peruvian desert caused by modern intensive farming","volume":"13","author":"Lacroix","year":"2020","journal-title":"Nat. Geosci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.rse.2016.11.007","article-title":"Correlation of satellite image time-series for the detection and monitoring of slow-moving landslides","volume":"189","author":"Stumpf","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1007\/s10346-019-01311-7","article-title":"Retrospective deformation of the Baige landslide using optical remote sensing images","volume":"17","author":"Yang","year":"2020","journal-title":"Landslides"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.rse.2015.05.010","article-title":"Earthquake-driven acceleration of slow-moving landslides in the Colca valley, Peru, detected from Pl\u00e9iades images","volume":"165","author":"Lacroix","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1016\/j.rse.2018.03.042","article-title":"Use of Sentinel-2 images for the detection of precursory motions before landslide failures","volume":"215","author":"Lacroix","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1016\/j.rse.2018.02.023","article-title":"Inversion of deformation fields time-series from optical images, and application to the long term kinematics of slow-moving landslides in Peru","volume":"210","author":"Bontemps","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1529","DOI":"10.1109\/TGRS.2006.888937","article-title":"Automatic and precise orthorectification, coregistration, and subpixel correlation of satellite images, application to ground deformation measurements","volume":"45","author":"Leprince","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1003","DOI":"10.1007\/s10346-019-01159-x","article-title":"Successive landsliding and damming of the Jinsha River in eastern Tibet, China: Prime investigation, early warning, and emergency response","volume":"16","author":"Fan","year":"2019","journal-title":"Landslides"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1782","DOI":"10.1029\/2019JF005035","article-title":"Widespread initiation, reactivation, and acceleration of landslides in the Northern California Coast Ranges due to extreme rainfall","volume":"124","author":"Handwerger","year":"2019","journal-title":"J. Geophys. Res. Earth Surf."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"e2020GL087452","DOI":"10.1029\/2020GL087452","article-title":"Rheology of a debris slide from the joint analysis of UAVSAR and LiDAR data","volume":"47","author":"Hu","year":"2020","journal-title":"Geophys. Res. Lett."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"111738","DOI":"10.1016\/j.rse.2020.111738","article-title":"Forecasting the magnitude of potential landslides based on InSAR techniques","volume":"241","author":"Zhang","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1144\/qjegh2014-040","article-title":"Ground instability detection using PS-InSAR in Lanzhou, China","volume":"47","author":"Zeng","year":"2014","journal-title":"Q. J. Eng. Geol. Hydrogeol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/s10346-017-0915-7","article-title":"The Maoxian landslide as seen from space: Detecting precursors of failure with Sentinel-1 data","volume":"15","author":"Intrieri","year":"2018","journal-title":"Landslides"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1007\/s10346-010-0225-9","article-title":"Integration of GPS with InSAR to monitoring of the Jiaju landslide in Sichuan, China","volume":"7","author":"Yin","year":"2010","journal-title":"Landslides"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Stumpf, A., Malet, J.P., Puissant, A., and Travelletti, J. (2016). Monitoring of earth surface motion and geomorphologic processes by optical image correlation. Land Surf. Remote Sens., 147\u2013190.","DOI":"10.1016\/B978-1-78548-105-5.50005-0"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Gascon, F., Bouzinac, C., Th\u00e9paut, O., Jung, M., Francesconi, B., Louis, J., Lonjou, V., Lafrance, B., Massera, S., and Gaudel-Vacaresse, A. (2017). Copernicus Sentinel-2A Calibration and Products Validation Status. Remote Sens., 9.","DOI":"10.3390\/rs9060584"},{"key":"ref_22","unstructured":"Yang, W., Liu, L., and Shi, P. (2020). A downstream landslide along the Jinsha river initiated by the 2018 Baige floods. Nat. Hazards Earth Syst. Sci. Discuss., under review."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.rse.2017.10.038","article-title":"Interferometric synthetic aperture radar atmospheric correction using a GPS-based iterative tropospheric decomposition model","volume":"204","author":"Yu","year":"2018","journal-title":"Remote Sens. Environ."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/17\/4721\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:04:37Z","timestamp":1760177077000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/17\/4721"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,21]]},"references-count":23,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2020,9]]}},"alternative-id":["s20174721"],"URL":"https:\/\/doi.org\/10.3390\/s20174721","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,8,21]]}}}