Three-dimensional and long-term landslide displacement estimation by fusing C- and L-band SAR observations: A case study in Gongjue County, Tibet, China

Recently, a large number of synthetic aperture radar (SAR) images has been introduced into landslide investigations with the growing launch of new SAR satellites, such as ALOS/PALSAR-2 and Sentinel-1. Therefore, it is appropriate to develop new approaches to retrieve three-dimensional (3D) displacem...

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Veröffentlicht in:Remote sensing of environment 2021-12, Vol.267, p.112745, Article 112745
Hauptverfasser: Liu, Xiaojie, Zhao, Chaoying, Zhang, Qin, Yin, Yueping, Lu, Zhong, Samsonov, Sergey, Yang, Chengsheng, Wang, Meng, Tomás, Roberto
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container_title Remote sensing of environment
container_volume 267
creator Liu, Xiaojie
Zhao, Chaoying
Zhang, Qin
Yin, Yueping
Lu, Zhong
Samsonov, Sergey
Yang, Chengsheng
Wang, Meng
Tomás, Roberto
description Recently, a large number of synthetic aperture radar (SAR) images has been introduced into landslide investigations with the growing launch of new SAR satellites, such as ALOS/PALSAR-2 and Sentinel-1. Therefore, it is appropriate to develop new approaches to retrieve three-dimensional (3D) displacements and long-term (> 10 years) displacement time series to investigate the spatio-temporal evolution and creep behavior of landslides. In this study, a new approach for the estimation of 3D and long-term displacement time series of landslides, based on the fusion of C- and L-band SAR observations, is presented. This method is applied to map 3D and long-term displacements (nearly 12 years) of the landslides in Gongjue County, Tibet in China; four sets of SAR images from different platforms (i.e., L-band ascending ALOS/PALSAR-1, C-band descending ENVISAT, and C-band ascending and descending Sentinel-1 SAR datasets) covering the period of January 2007 to November 2018 were collected and exploited. First, the assumption that the landslide moves parallel to its ground surface is used to produce 3D displacement rates and time series by fusing ascending and descending Sentinel-1 SAR images, from which the optimal sliding direction for each pixel of the slope is well estimated. Then, the long-term displacement time-series of the landslide between January 2007 and October 2018 in the estimated sliding direction is recovered by fusing L-band ALOS/PALSAR-1 and C-band Sentinel-1 SAR images. In order to fill the time gap of nearly four years between ALOS/PALSAR-1 and Sentinel-1 SAR images, the Tikhonov regularization (TR) method is developed to establish the observational equation. Moreover, to solve the problem arising from ALOS/PALSAR-1 and Sentinel-1 images with different wavelengths, incidence angles and flight directions, the measurements from ALOS/PALSAR-1 and Sentinel-1 images are both projected to the estimated optimal sliding direction to achieve a unified displacement datum. Our results from ascending and descending Sentinel-1 images suggest that the maximum displacement rates of the study area in the vertical and east-west directions from December 2016 to October 2018 were greater than 70 and 80 mm/year, respectively, and 2D displacement results reveal that the displacement patterns and movement characteristics of all the detected landslides are not identical in the study area. Specifically, the 3D displacement results successfully revealed the spatiotemporal dis
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Therefore, it is appropriate to develop new approaches to retrieve three-dimensional (3D) displacements and long-term (&gt; 10 years) displacement time series to investigate the spatio-temporal evolution and creep behavior of landslides. In this study, a new approach for the estimation of 3D and long-term displacement time series of landslides, based on the fusion of C- and L-band SAR observations, is presented. This method is applied to map 3D and long-term displacements (nearly 12 years) of the landslides in Gongjue County, Tibet in China; four sets of SAR images from different platforms (i.e., L-band ascending ALOS/PALSAR-1, C-band descending ENVISAT, and C-band ascending and descending Sentinel-1 SAR datasets) covering the period of January 2007 to November 2018 were collected and exploited. First, the assumption that the landslide moves parallel to its ground surface is used to produce 3D displacement rates and time series by fusing ascending and descending Sentinel-1 SAR images, from which the optimal sliding direction for each pixel of the slope is well estimated. Then, the long-term displacement time-series of the landslide between January 2007 and October 2018 in the estimated sliding direction is recovered by fusing L-band ALOS/PALSAR-1 and C-band Sentinel-1 SAR images. In order to fill the time gap of nearly four years between ALOS/PALSAR-1 and Sentinel-1 SAR images, the Tikhonov regularization (TR) method is developed to establish the observational equation. Moreover, to solve the problem arising from ALOS/PALSAR-1 and Sentinel-1 images with different wavelengths, incidence angles and flight directions, the measurements from ALOS/PALSAR-1 and Sentinel-1 images are both projected to the estimated optimal sliding direction to achieve a unified displacement datum. Our results from ascending and descending Sentinel-1 images suggest that the maximum displacement rates of the study area in the vertical and east-west directions from December 2016 to October 2018 were greater than 70 and 80 mm/year, respectively, and 2D displacement results reveal that the displacement patterns and movement characteristics of all the detected landslides are not identical in the study area. Specifically, the 3D displacement results successfully revealed the spatiotemporal displacement patterns and movement direction of each block of the Shadong landslide, and long-term displacement time series showed for the first time that the maximum cumulative displacement exceeds 1.3 m from January 2007 to October 2018. Moreover, the kinematic evolution and possible driving factors of landslides were investigated using 2D and 3D and long-term displacement results, coupled with hydrological factors and unidimensional constitutive models of the rocks. •New approaches are presented to estimate 3D and long-term landslide displacements.•Optimal sliding direction of the landslide is retrieved using 3D displacements.•InSAR reveals 12-year's displacement time series and its creep behavior of a landslide.•InSAR measurements suggest that the landslide was in a stable deformation stage.•Non-linear landslide movement is likely caused by the Jinsha River water level changes.</description><identifier>ISSN: 0034-4257</identifier><identifier>EISSN: 1879-0704</identifier><identifier>DOI: 10.1016/j.rse.2021.112745</identifier><language>eng</language><publisher>New York: Elsevier Inc</publisher><subject>3D displacements ; C band ; Constitutive models ; Creep (materials) ; Displacement ; Evolution ; Hydrology ; Incidence angle ; InSAR ; Jinsha River ; Landslide ; Landslides ; Landslides &amp; mudslides ; Long-term displacement time series ; Radar imaging ; Regularization ; Sliding ; Synthetic aperture radar ; Tibet ; Time series ; Wavelengths</subject><ispartof>Remote sensing of environment, 2021-12, Vol.267, p.112745, Article 112745</ispartof><rights>2021 Elsevier Inc.</rights><rights>Copyright Elsevier BV Dec 15, 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c368t-2a5c79fca0d0a7bdcb47a30f2905bf079d625b3319da6b4bf2b49b705aa60b463</citedby><cites>FETCH-LOGICAL-c368t-2a5c79fca0d0a7bdcb47a30f2905bf079d625b3319da6b4bf2b49b705aa60b463</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S003442572100465X$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65534</link.rule.ids></links><search><creatorcontrib>Liu, Xiaojie</creatorcontrib><creatorcontrib>Zhao, Chaoying</creatorcontrib><creatorcontrib>Zhang, Qin</creatorcontrib><creatorcontrib>Yin, Yueping</creatorcontrib><creatorcontrib>Lu, Zhong</creatorcontrib><creatorcontrib>Samsonov, Sergey</creatorcontrib><creatorcontrib>Yang, Chengsheng</creatorcontrib><creatorcontrib>Wang, Meng</creatorcontrib><creatorcontrib>Tomás, Roberto</creatorcontrib><title>Three-dimensional and long-term landslide displacement estimation by fusing C- and L-band SAR observations: A case study in Gongjue County, Tibet, China</title><title>Remote sensing of environment</title><description>Recently, a large number of synthetic aperture radar (SAR) images has been introduced into landslide investigations with the growing launch of new SAR satellites, such as ALOS/PALSAR-2 and Sentinel-1. Therefore, it is appropriate to develop new approaches to retrieve three-dimensional (3D) displacements and long-term (&gt; 10 years) displacement time series to investigate the spatio-temporal evolution and creep behavior of landslides. In this study, a new approach for the estimation of 3D and long-term displacement time series of landslides, based on the fusion of C- and L-band SAR observations, is presented. This method is applied to map 3D and long-term displacements (nearly 12 years) of the landslides in Gongjue County, Tibet in China; four sets of SAR images from different platforms (i.e., L-band ascending ALOS/PALSAR-1, C-band descending ENVISAT, and C-band ascending and descending Sentinel-1 SAR datasets) covering the period of January 2007 to November 2018 were collected and exploited. First, the assumption that the landslide moves parallel to its ground surface is used to produce 3D displacement rates and time series by fusing ascending and descending Sentinel-1 SAR images, from which the optimal sliding direction for each pixel of the slope is well estimated. Then, the long-term displacement time-series of the landslide between January 2007 and October 2018 in the estimated sliding direction is recovered by fusing L-band ALOS/PALSAR-1 and C-band Sentinel-1 SAR images. In order to fill the time gap of nearly four years between ALOS/PALSAR-1 and Sentinel-1 SAR images, the Tikhonov regularization (TR) method is developed to establish the observational equation. Moreover, to solve the problem arising from ALOS/PALSAR-1 and Sentinel-1 images with different wavelengths, incidence angles and flight directions, the measurements from ALOS/PALSAR-1 and Sentinel-1 images are both projected to the estimated optimal sliding direction to achieve a unified displacement datum. Our results from ascending and descending Sentinel-1 images suggest that the maximum displacement rates of the study area in the vertical and east-west directions from December 2016 to October 2018 were greater than 70 and 80 mm/year, respectively, and 2D displacement results reveal that the displacement patterns and movement characteristics of all the detected landslides are not identical in the study area. Specifically, the 3D displacement results successfully revealed the spatiotemporal displacement patterns and movement direction of each block of the Shadong landslide, and long-term displacement time series showed for the first time that the maximum cumulative displacement exceeds 1.3 m from January 2007 to October 2018. Moreover, the kinematic evolution and possible driving factors of landslides were investigated using 2D and 3D and long-term displacement results, coupled with hydrological factors and unidimensional constitutive models of the rocks. •New approaches are presented to estimate 3D and long-term landslide displacements.•Optimal sliding direction of the landslide is retrieved using 3D displacements.•InSAR reveals 12-year's displacement time series and its creep behavior of a landslide.•InSAR measurements suggest that the landslide was in a stable deformation stage.•Non-linear landslide movement is likely caused by the Jinsha River water level changes.</description><subject>3D displacements</subject><subject>C band</subject><subject>Constitutive models</subject><subject>Creep (materials)</subject><subject>Displacement</subject><subject>Evolution</subject><subject>Hydrology</subject><subject>Incidence angle</subject><subject>InSAR</subject><subject>Jinsha River</subject><subject>Landslide</subject><subject>Landslides</subject><subject>Landslides &amp; mudslides</subject><subject>Long-term displacement time series</subject><subject>Radar imaging</subject><subject>Regularization</subject><subject>Sliding</subject><subject>Synthetic aperture radar</subject><subject>Tibet</subject><subject>Time series</subject><subject>Wavelengths</subject><issn>0034-4257</issn><issn>1879-0704</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kc9q3DAQxkVpodskD9CboNd4O5Jla92eFpOmhYVCuzkL_RknMl55K8mBfZM8brXZnnsaBr7fzHzzEfKRwZoBaz-P65hwzYGzNWNciuYNWbGN7CqQIN6SFUAtKsEb-Z58SGkEYM1GshV52T9FxMr5A4bk56AnqoOj0xweq4zxQKfSpsk7pM6n46QtFmWmmLI_6FwIak50WJIPj7SvXuFdZc7l9_YXnU3C-PyqS1_ollqdkKa8uBP1gd6XLeOCtJ-XkE-3dO8N5lvaP_mgr8m7QU8Jb_7VK_Lw7W7ff692P-9_9NtdZet2kyuuGyu7wWpwoKVx1gipaxh4B40ZQHau5Y2pa9Y53RphBm5EZyQ0WrdgRFtfkU-Xucc4_1mKLTXOSyx_SIq3rBE1g1YWFbuobJxTijioYyz-40kxUOcA1KhKAOocgLoEUJivFwbL-c8eo0rWY7DofESblZv9f-i_SlGPHQ</recordid><startdate>20211215</startdate><enddate>20211215</enddate><creator>Liu, Xiaojie</creator><creator>Zhao, Chaoying</creator><creator>Zhang, Qin</creator><creator>Yin, Yueping</creator><creator>Lu, Zhong</creator><creator>Samsonov, Sergey</creator><creator>Yang, Chengsheng</creator><creator>Wang, Meng</creator><creator>Tomás, Roberto</creator><general>Elsevier Inc</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SN</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7TG</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>KL.</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope></search><sort><creationdate>20211215</creationdate><title>Three-dimensional and long-term landslide displacement estimation by fusing C- and L-band SAR observations: A case study in Gongjue County, Tibet, China</title><author>Liu, Xiaojie ; Zhao, Chaoying ; Zhang, Qin ; Yin, Yueping ; Lu, Zhong ; Samsonov, Sergey ; Yang, Chengsheng ; Wang, Meng ; Tomás, Roberto</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c368t-2a5c79fca0d0a7bdcb47a30f2905bf079d625b3319da6b4bf2b49b705aa60b463</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>3D displacements</topic><topic>C band</topic><topic>Constitutive models</topic><topic>Creep (materials)</topic><topic>Displacement</topic><topic>Evolution</topic><topic>Hydrology</topic><topic>Incidence angle</topic><topic>InSAR</topic><topic>Jinsha River</topic><topic>Landslide</topic><topic>Landslides</topic><topic>Landslides &amp; mudslides</topic><topic>Long-term displacement time series</topic><topic>Radar imaging</topic><topic>Regularization</topic><topic>Sliding</topic><topic>Synthetic aperture radar</topic><topic>Tibet</topic><topic>Time series</topic><topic>Wavelengths</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Xiaojie</creatorcontrib><creatorcontrib>Zhao, Chaoying</creatorcontrib><creatorcontrib>Zhang, Qin</creatorcontrib><creatorcontrib>Yin, Yueping</creatorcontrib><creatorcontrib>Lu, Zhong</creatorcontrib><creatorcontrib>Samsonov, Sergey</creatorcontrib><creatorcontrib>Yang, Chengsheng</creatorcontrib><creatorcontrib>Wang, Meng</creatorcontrib><creatorcontrib>Tomás, Roberto</creatorcontrib><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Ecology Abstracts</collection><collection>Electronics &amp; 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Therefore, it is appropriate to develop new approaches to retrieve three-dimensional (3D) displacements and long-term (&gt; 10 years) displacement time series to investigate the spatio-temporal evolution and creep behavior of landslides. In this study, a new approach for the estimation of 3D and long-term displacement time series of landslides, based on the fusion of C- and L-band SAR observations, is presented. This method is applied to map 3D and long-term displacements (nearly 12 years) of the landslides in Gongjue County, Tibet in China; four sets of SAR images from different platforms (i.e., L-band ascending ALOS/PALSAR-1, C-band descending ENVISAT, and C-band ascending and descending Sentinel-1 SAR datasets) covering the period of January 2007 to November 2018 were collected and exploited. First, the assumption that the landslide moves parallel to its ground surface is used to produce 3D displacement rates and time series by fusing ascending and descending Sentinel-1 SAR images, from which the optimal sliding direction for each pixel of the slope is well estimated. Then, the long-term displacement time-series of the landslide between January 2007 and October 2018 in the estimated sliding direction is recovered by fusing L-band ALOS/PALSAR-1 and C-band Sentinel-1 SAR images. In order to fill the time gap of nearly four years between ALOS/PALSAR-1 and Sentinel-1 SAR images, the Tikhonov regularization (TR) method is developed to establish the observational equation. Moreover, to solve the problem arising from ALOS/PALSAR-1 and Sentinel-1 images with different wavelengths, incidence angles and flight directions, the measurements from ALOS/PALSAR-1 and Sentinel-1 images are both projected to the estimated optimal sliding direction to achieve a unified displacement datum. Our results from ascending and descending Sentinel-1 images suggest that the maximum displacement rates of the study area in the vertical and east-west directions from December 2016 to October 2018 were greater than 70 and 80 mm/year, respectively, and 2D displacement results reveal that the displacement patterns and movement characteristics of all the detected landslides are not identical in the study area. Specifically, the 3D displacement results successfully revealed the spatiotemporal displacement patterns and movement direction of each block of the Shadong landslide, and long-term displacement time series showed for the first time that the maximum cumulative displacement exceeds 1.3 m from January 2007 to October 2018. Moreover, the kinematic evolution and possible driving factors of landslides were investigated using 2D and 3D and long-term displacement results, coupled with hydrological factors and unidimensional constitutive models of the rocks. •New approaches are presented to estimate 3D and long-term landslide displacements.•Optimal sliding direction of the landslide is retrieved using 3D displacements.•InSAR reveals 12-year's displacement time series and its creep behavior of a landslide.•InSAR measurements suggest that the landslide was in a stable deformation stage.•Non-linear landslide movement is likely caused by the Jinsha River water level changes.</abstract><cop>New York</cop><pub>Elsevier Inc</pub><doi>10.1016/j.rse.2021.112745</doi><oa>free_for_read</oa></addata></record>
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subjects 3D displacements
C band
Constitutive models
Creep (materials)
Displacement
Evolution
Hydrology
Incidence angle
InSAR
Jinsha River
Landslide
Landslides
Landslides & mudslides
Long-term displacement time series
Radar imaging
Regularization
Sliding
Synthetic aperture radar
Tibet
Time series
Wavelengths
title Three-dimensional and long-term landslide displacement estimation by fusing C- and L-band SAR observations: A case study in Gongjue County, Tibet, China
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