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Selecting the Best Image Pairs to Measure Slope Deformation
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–temporal resolution images at low cost; however, finding the best image pairs to derive slope deformation...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506728/ https://www.ncbi.nlm.nih.gov/pubmed/32825606 http://dx.doi.org/10.3390/s20174721 |
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author | Yang, Wentao |
author_facet | Yang, Wentao |
author_sort | Yang, Wentao |
collection | PubMed |
description | 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–temporal 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. |
format | Online Article Text |
id | pubmed-7506728 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75067282020-09-26 Selecting the Best Image Pairs to Measure Slope Deformation Yang, Wentao Sensors (Basel) Letter 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–temporal 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. MDPI 2020-08-21 /pmc/articles/PMC7506728/ /pubmed/32825606 http://dx.doi.org/10.3390/s20174721 Text en © 2020 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Letter Yang, Wentao Selecting the Best Image Pairs to Measure Slope Deformation |
title | Selecting the Best Image Pairs to Measure Slope Deformation |
title_full | Selecting the Best Image Pairs to Measure Slope Deformation |
title_fullStr | Selecting the Best Image Pairs to Measure Slope Deformation |
title_full_unstemmed | Selecting the Best Image Pairs to Measure Slope Deformation |
title_short | Selecting the Best Image Pairs to Measure Slope Deformation |
title_sort | selecting the best image pairs to measure slope deformation |
topic | Letter |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506728/ https://www.ncbi.nlm.nih.gov/pubmed/32825606 http://dx.doi.org/10.3390/s20174721 |
work_keys_str_mv | AT yangwentao selectingthebestimagepairstomeasureslopedeformation |