Mapping Surface Deformation in Rwanda and Neighboring Areas Using SBAS-InSAR

Surface deformation poses significant risks to urban infrastructure, agriculture, and the environment in many regions worldwide, including Rwanda and the neighboring areas. This study focuses on surface deformation mapping and time series analysis in Rwanda and the neighboring areas from 2 July 2016...

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Main Authors: Adrien Mugabushaka, Zhenhong Li, Xuesong Zhang, Chuang Song, Bingquan Han, Bo Chen, Zhenjiang Liu, Yi Chen
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Remote Sensing
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Online Access:https://www.mdpi.com/2072-4292/16/23/4456
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author Adrien Mugabushaka
Zhenhong Li
Xuesong Zhang
Chuang Song
Bingquan Han
Bo Chen
Zhenjiang Liu
Yi Chen
author_facet Adrien Mugabushaka
Zhenhong Li
Xuesong Zhang
Chuang Song
Bingquan Han
Bo Chen
Zhenjiang Liu
Yi Chen
author_sort Adrien Mugabushaka
collection DOAJ
description Surface deformation poses significant risks to urban infrastructure, agriculture, and the environment in many regions worldwide, including Rwanda and the neighboring areas. This study focuses on surface deformation mapping and time series analysis in Rwanda and the neighboring areas from 2 July 2016 to 8 June 2023 using the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR). The influence of atmospheric delay error is effectively reduced by integrating the Generic Atmospheric Correction Online Service (GACOS), which provides precise atmospheric delay maps. Then the SBAS-InSAR method is utilized to generate surface deformation maps and displacement time series across the region. The results of this study indicated that the maximum deformation rate was −0.11 m/yr (subsidence) and +0.13 m/yr (uplift). Through time series analysis, we quantified subsidence and uplift areas and identified key drivers of surface deformation. Since subsidence or uplift varies across the region, we have summarized the different deformation patterns and briefly analyzed the factors that may lead to deformation. Finally, this study underscores the importance of SBAS-InSAR for tracking surface deformation in Rwanda and the neighboring areas, which offers valuable perspectives for sustainable land utilization strategizing and risk mitigation.
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spelling doaj-art-849bbd8b0b7948cea017c84562c02bef2025-08-20T01:55:41ZengMDPI AGRemote Sensing2072-42922024-11-011623445610.3390/rs16234456Mapping Surface Deformation in Rwanda and Neighboring Areas Using SBAS-InSARAdrien Mugabushaka0Zhenhong Li1Xuesong Zhang2Chuang Song3Bingquan Han4Bo Chen5Zhenjiang Liu6Yi Chen7College of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, ChinaCollege of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, ChinaCollege of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, ChinaCollege of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, ChinaCollege of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, ChinaCollege of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, ChinaCollege of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, ChinaCollege of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, ChinaSurface deformation poses significant risks to urban infrastructure, agriculture, and the environment in many regions worldwide, including Rwanda and the neighboring areas. This study focuses on surface deformation mapping and time series analysis in Rwanda and the neighboring areas from 2 July 2016 to 8 June 2023 using the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR). The influence of atmospheric delay error is effectively reduced by integrating the Generic Atmospheric Correction Online Service (GACOS), which provides precise atmospheric delay maps. Then the SBAS-InSAR method is utilized to generate surface deformation maps and displacement time series across the region. The results of this study indicated that the maximum deformation rate was −0.11 m/yr (subsidence) and +0.13 m/yr (uplift). Through time series analysis, we quantified subsidence and uplift areas and identified key drivers of surface deformation. Since subsidence or uplift varies across the region, we have summarized the different deformation patterns and briefly analyzed the factors that may lead to deformation. Finally, this study underscores the importance of SBAS-InSAR for tracking surface deformation in Rwanda and the neighboring areas, which offers valuable perspectives for sustainable land utilization strategizing and risk mitigation.https://www.mdpi.com/2072-4292/16/23/4456surface deformationGACOSSBAS-InSARtime seriesRwanda
spellingShingle Adrien Mugabushaka
Zhenhong Li
Xuesong Zhang
Chuang Song
Bingquan Han
Bo Chen
Zhenjiang Liu
Yi Chen
Mapping Surface Deformation in Rwanda and Neighboring Areas Using SBAS-InSAR
Remote Sensing
surface deformation
GACOS
SBAS-InSAR
time series
Rwanda
title Mapping Surface Deformation in Rwanda and Neighboring Areas Using SBAS-InSAR
title_full Mapping Surface Deformation in Rwanda and Neighboring Areas Using SBAS-InSAR
title_fullStr Mapping Surface Deformation in Rwanda and Neighboring Areas Using SBAS-InSAR
title_full_unstemmed Mapping Surface Deformation in Rwanda and Neighboring Areas Using SBAS-InSAR
title_short Mapping Surface Deformation in Rwanda and Neighboring Areas Using SBAS-InSAR
title_sort mapping surface deformation in rwanda and neighboring areas using sbas insar
topic surface deformation
GACOS
SBAS-InSAR
time series
Rwanda
url https://www.mdpi.com/2072-4292/16/23/4456
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