Study and Prediction of Surface Deformation Characteristics of Different Vegetation Types in the Permafrost Zone of Linzhi, Tibet

Permafrost and alpine vegetation are widely distributed in Tibet, which is a sensitive area for global climate change. In this study, we inverted the surface deformation from 22 May 2018 to 9 October 2021 in a rectangular area within the city of Linzhi, Tibet, using the Sentinel1-A data and two time...

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Published in:Remote Sensing
Main Authors: Xiaoci Wang, Qiang Yu, Jun Ma, Linzhe Yang, Wei Liu, Jianzheng Li
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2022
Subjects:
Online Access:https://doi.org/10.3390/rs14184684
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spelling ftmdpi:oai:mdpi.com:/2072-4292/14/18/4684/ 2023-08-20T04:09:10+02:00 Study and Prediction of Surface Deformation Characteristics of Different Vegetation Types in the Permafrost Zone of Linzhi, Tibet Xiaoci Wang Qiang Yu Jun Ma Linzhe Yang Wei Liu Jianzheng Li agris 2022-09-19 application/pdf https://doi.org/10.3390/rs14184684 EN eng Multidisciplinary Digital Publishing Institute Forest Remote Sensing https://dx.doi.org/10.3390/rs14184684 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 14; Issue 18; Pages: 4684 InSAR surface deformation permafrost vegetation machine learning Tibet Text 2022 ftmdpi https://doi.org/10.3390/rs14184684 2023-08-01T06:32:18Z Permafrost and alpine vegetation are widely distributed in Tibet, which is a sensitive area for global climate change. In this study, we inverted the surface deformation from 22 May 2018 to 9 October 2021 in a rectangular area within the city of Linzhi, Tibet, using the Sentinel1-A data and two time-series interferometric system aperture radar (InSAR) techniques. Then, the significant features of surface deformation were analyzed separately according to different vegetation types. Finally, multiple machine learning methods were used to predict future surface deformation, and the results were compared to obtain the model with the highest prediction accuracy. This study aims to provide a scientific reference and decision basis for global ecological security and sustainable development. The results showed that the surface deformation rate in the study area was basically between ±10 mm/a, and the cumulative surface deformation was basically between ±35 mm. The surface deformation of grassland, meadow, coniferous forest, and alpine vegetation were all significantly correlated with NDVI, and the effect of alpine vegetation, coniferous forest, and grassland on permafrost was stronger than that of the meadow. The prediction accuracy of the Holt–Winters model was higher than that of Holt′s model and the ARIMA model; it was expected that the ground surface would keep rising in the next two months, and the ground surface deformation of alpine vegetation and the coniferous forest was relatively small. The above studies indicated that the surface deformation in the Tibetan permafrost region was relatively stable under the conditions of alpine vegetation and coniferous forest. Future-related ecological construction needs to pay more attention to permafrost areas under grassland and meadow conditions, which are prone to surface deformation and affect the stability of ecosystems. Text permafrost MDPI Open Access Publishing Remote Sensing 14 18 4684
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic InSAR
surface deformation
permafrost
vegetation
machine learning
Tibet
spellingShingle InSAR
surface deformation
permafrost
vegetation
machine learning
Tibet
Xiaoci Wang
Qiang Yu
Jun Ma
Linzhe Yang
Wei Liu
Jianzheng Li
Study and Prediction of Surface Deformation Characteristics of Different Vegetation Types in the Permafrost Zone of Linzhi, Tibet
topic_facet InSAR
surface deformation
permafrost
vegetation
machine learning
Tibet
description Permafrost and alpine vegetation are widely distributed in Tibet, which is a sensitive area for global climate change. In this study, we inverted the surface deformation from 22 May 2018 to 9 October 2021 in a rectangular area within the city of Linzhi, Tibet, using the Sentinel1-A data and two time-series interferometric system aperture radar (InSAR) techniques. Then, the significant features of surface deformation were analyzed separately according to different vegetation types. Finally, multiple machine learning methods were used to predict future surface deformation, and the results were compared to obtain the model with the highest prediction accuracy. This study aims to provide a scientific reference and decision basis for global ecological security and sustainable development. The results showed that the surface deformation rate in the study area was basically between ±10 mm/a, and the cumulative surface deformation was basically between ±35 mm. The surface deformation of grassland, meadow, coniferous forest, and alpine vegetation were all significantly correlated with NDVI, and the effect of alpine vegetation, coniferous forest, and grassland on permafrost was stronger than that of the meadow. The prediction accuracy of the Holt–Winters model was higher than that of Holt′s model and the ARIMA model; it was expected that the ground surface would keep rising in the next two months, and the ground surface deformation of alpine vegetation and the coniferous forest was relatively small. The above studies indicated that the surface deformation in the Tibetan permafrost region was relatively stable under the conditions of alpine vegetation and coniferous forest. Future-related ecological construction needs to pay more attention to permafrost areas under grassland and meadow conditions, which are prone to surface deformation and affect the stability of ecosystems.
format Text
author Xiaoci Wang
Qiang Yu
Jun Ma
Linzhe Yang
Wei Liu
Jianzheng Li
author_facet Xiaoci Wang
Qiang Yu
Jun Ma
Linzhe Yang
Wei Liu
Jianzheng Li
author_sort Xiaoci Wang
title Study and Prediction of Surface Deformation Characteristics of Different Vegetation Types in the Permafrost Zone of Linzhi, Tibet
title_short Study and Prediction of Surface Deformation Characteristics of Different Vegetation Types in the Permafrost Zone of Linzhi, Tibet
title_full Study and Prediction of Surface Deformation Characteristics of Different Vegetation Types in the Permafrost Zone of Linzhi, Tibet
title_fullStr Study and Prediction of Surface Deformation Characteristics of Different Vegetation Types in the Permafrost Zone of Linzhi, Tibet
title_full_unstemmed Study and Prediction of Surface Deformation Characteristics of Different Vegetation Types in the Permafrost Zone of Linzhi, Tibet
title_sort study and prediction of surface deformation characteristics of different vegetation types in the permafrost zone of linzhi, tibet
publisher Multidisciplinary Digital Publishing Institute
publishDate 2022
url https://doi.org/10.3390/rs14184684
op_coverage agris
genre permafrost
genre_facet permafrost
op_source Remote Sensing; Volume 14; Issue 18; Pages: 4684
op_relation Forest Remote Sensing
https://dx.doi.org/10.3390/rs14184684
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs14184684
container_title Remote Sensing
container_volume 14
container_issue 18
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