Monitoring Slope Creep Motion using Multi Temporal Interferometry Synthetic Aperture Radar in Semarang, Indonesia

Landslide is one type of slope movement, where the slope movement includes creep. Although creep movement does not have an impact on the risk of loss of life, this creep movement takes place constantly and invisible which has an impact on economic losses. In this study, a time-series monitoring was carried out from 2018 to 2020 to see the movement of the slopes in the study area using the Multi-Temporal Interferometry Synthetic Aperture Radar (MTInSAR). A time series method from Sentinel 1A/B data, which includes Trangkil Sejahtera Housing (PTS), Soegijapranata Catholic University (UNIKA), and 17 August 1945 University (UNTAG) in Semarang City, Indonesia. The results of data processing indicate that there are slope movement in the target location, namely Trangkil Sejahtera and Selorejo Housing (southwest of UNIKA). Based on BPBD 2021 data, landslides occurred in the Trangkil Baru Housing Center (to the north of PTS) and the Garang River landslide channel west of Selorejo. This shows that there is a link between crawling in 2018-2020 and landslides in 2021. Although the use of satellite data has some drawbacks, the results can be taken into consideration in building an early warning system and reducing losses due to landslides.

Download Full-text

Landslide Deformation Monitoring by Adaptive Distributed Scatterer Interferometric Synthetic Aperture Radar

Remote Sensing ◽

10.3390/rs11192273 ◽

2019 ◽

Vol 11 (19) ◽

pp. 2273 ◽

Cited By ~ 2

Author(s):

Hongguo Jia ◽

Hao Zhang ◽

Luyao Liu ◽

Guoxiang Liu

Keyword(s):

Time Series ◽

Synthetic Aperture Radar ◽

Deformation Monitoring ◽

Synthetic Aperture ◽

Economic Losses ◽

Interferometric Synthetic Aperture Radar ◽

Mountainous Areas ◽

Landslide Area ◽

Landslide Deformation ◽

Aperture Radar

Landslide is the second most frequent geological disaster after earthquake, which causes a large number of casualties and economic losses every year. China frequently experiences devastating landslides in mountainous areas. Interferometric Synthetic Aperture Radar (InSAR) technology has great potential for detecting potentially unstable landslides across wide areas and can monitor surface displacement of a single landslide. However traditional time series InSAR technology such as persistent scatterer interferometry (PSI) and small-baseline subset (SBAS) cannot identify enough points in mountainous areas because of dense vegetation and steep terrain. In order to improve the accuracy of landslide hazard detection and the reliability of landslide deformation monitoring in areas lacking high coherence stability point targets, this study proposes an adaptive distributed scatterer interferometric synthetic aperture radar (ADS-InSAR) method based on the spatiotemporal coherence of the distributed scatterer (DS), which automatically adjusts its detection threshold to improve the spatial distribution density and reliability of DS detection in the landslide area. After time series network modeling and deformation calculation of the ADS target, the displacement deformation of the landslide area can be accurately extracted. Shuibuya Town in Enshi Prefecture, Hubei Province, China, was used as a case study, along with 18 Sentinal-1A images acquired from March 2016 to April 2017. The ADS-InSAR method was used to obtain regional deformation data. The deformation time series was combined with hydrometeorological and related data to analyze landslide deformation. The results show that the ADS-InSAR method can effectively improve the density of DS distribution, successfully detect existing ancient landslide groups and determine multiple potential landslide areas, enabling early warning for landslide hazards. This study verifies the reliability and accuracy of ADS-InSAR for landslide disaster prevention and mitigation.

Download Full-text

A Novel Method of Generating Deformation Time-Series Using Interferometric Synthetic Aperture Radar and Its Application in Mexico City

Remote Sensing ◽

10.3390/rs10111741 ◽

2018 ◽

Vol 10 (11) ◽

pp. 1741 ◽

Cited By ~ 3

Author(s):

Xiaying Wang ◽

Qin Zhang ◽

Chaoying Zhao ◽

Feifei Qu ◽

Juqing Zhang

Keyword(s):

Time Series ◽

Synthetic Aperture Radar ◽

Mexico City ◽

Land Subsidence ◽

Functional Model ◽

Synthetic Aperture ◽

Economic Losses ◽

Deformation Pattern ◽

Interferometric Synthetic Aperture Radar ◽

Aperture Radar

As a result of rapid societal development and urbanization, the pumping of groundwater has gradually increased. Land subsidence has thus become a common geological disaster, which can result in huge economic losses. Interferometric synthetic aperture radar (InSAR), with its large-scale and high-accuracy monitoring characteristics, can attain information on Earth surface deformation using the interferometric phase between couples of SAR images acquired at different times. Time-series results for the ground surface are the key information required to understand the deformation pattern and further study the reason for the subsidence. However, in recent research, most methods for resolving time-series deformation—like the Berardino method—that use residuals in functional model solving and distinguish high-pass displacement and the atmospheric component by filtering do not generally work well and functional models focusing on prior information in the time-series solution process are not always available. In this paper, to solve the above problems, 34 Sentinel-1A descending mode scenes of Mexico City captured between 2015/04/13 and 2016/09/10 are used as experimental data. Firstly, a new functional model is provided to obtain the deformation time-series. The nonlinear deformation and atmospheric phase are combined as an unknown parameter and the method of singular value decomposition (SVD) is used to solve this variable. The nonlinear displacement and atmospheric phase are then separated by the singular spectrum analysis (SSA) method. Finally, the total land subsidence time-series is obtained by adding together the linear displacement and nonlinear displacement. Two typical methods and the proposed method were compared using both unit weights and adaptive weights. The experimental results show that the proposed method can obtain a more accurate time-series deformation result. Moreover, the different weights do not result in significant differences and the solved atmospheric and nonlinear phases have good consistency with the interferogram phase.

Download Full-text

A Decade of Ground Deformation in Kunming (China) Revealed by Multi-Temporal Synthetic Aperture Radar Interferometry (InSAR) Technique

Sensors ◽

10.3390/s19204425 ◽

2019 ◽

Vol 19 (20) ◽

pp. 4425 ◽

Cited By ~ 2

Author(s):

Wu Zhu ◽

Wen-Liang Li ◽

Qin Zhang ◽

Yi Yang ◽

Yan Zhang ◽

...

Keyword(s):

Time Series ◽

Synthetic Aperture Radar ◽

Ground Deformation ◽

Soft Soil ◽

Synthetic Aperture ◽

X Band ◽

Deformation Velocity ◽

Multi Temporal ◽

L Band ◽

Aperture Radar

Large-scale urbanization has brought about severe ground subsidence in Kunming (China), threatening the stability of urban infrastructure. Mapping of the spatiotemporal variations of ground deformation is urgently needed, along with summarization of the causes of the subsidence over Kunming with the purpose of disaster prevention and mitigation. In this study, for the first time, a multi-temporal interferometric synthetic aperture radar (InSAR) technique with L-band Advanced Land Observation Satellite (ALOS-1) and X-band Constellation of Small Satellites for Mediterranean basin Observation (COSMO-SkyMed) data was applied to Kunming to derive the time series deformation from 2007 to 2016. The annual deformation velocity revealed two severe subsiding regions in Kunming, with a maximum subsidence of 35 mm/y. The comparison of the deformation between InSAR and leveling showed root-mean-square error (RMSE) values of about 4.5 mm for the L-band and 3.7 mm for the X-band, indicating that our results were reliable. We also found that the L-band illustrated a larger amount of subsidence than the X-band in the tested regions. This difference was mainly caused by the different synthetic aperture radar (SAR)-acquired times and imaging geometries between the L- and X-band SAR images. The vertical time series deformation over two severe subsiding regions presented an approximate linear variation with time, where the cumulative subsidence reached 209 mm during the period of 2007–2016. In view of relevant analyses, we found that the subsidence in Kunming was the result of soft soil consolidation, building load, and groundwater extraction. Our results may provide scientific evidence regarding the sound management of urban construction to mitigate potential damage to infrastructure and the environment.

Download Full-text

Earth Environmental Monitoring Using Multi-Temporal Synthetic Aperture Radar: A Critical Review of Selected Applications

Remote Sensing ◽

10.3390/rs13040604 ◽

2021 ◽

Vol 13 (4) ◽

pp. 604

Author(s):

Donato Amitrano ◽

Gerardo Di Martino ◽

Raffaella Guida ◽

Pasquale Iervolino ◽

Antonio Iodice ◽

...

Keyword(s):

Remote Sensing ◽

Synthetic Aperture Radar ◽

Microwave Remote Sensing ◽

Radar Data ◽

Synthetic Aperture ◽

Special Focus ◽

Arid Environments ◽

Synthetic Aperture Radar Data ◽

Multi Temporal ◽

Aperture Radar

Microwave remote sensing has widely demonstrated its potential in the continuous monitoring of our rapidly changing planet. This review provides an overview of state-of-the-art methodologies for multi-temporal synthetic aperture radar change detection and its applications to biosphere and hydrosphere monitoring, with special focus on topics like forestry, water resources management in semi-arid environments and floods. The analyzed literature is categorized on the base of the approach adopted and the data exploited and discussed in light of the downstream remote sensing market. The purpose is to highlight the main issues and limitations preventing the diffusion of synthetic aperture radar data in both industrial and multidisciplinary research contexts and the possible solutions for boosting their usage among end-users.

Download Full-text