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Time series SAR interferometry approach for landslide identification in mountainous areas of Western Ghats, India

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Abstract

Monitoring of Earth’s surface processes is efficiently performed by Differential SAR interferometry (DInSAR) techniques with the availability of open access Copernicus Sentinel-1A and 1B SAR data products having 6 days temporal resolution. With over 750 landslides triggered in Kodagu district, Karnataka, India, interferometric wide swath (IW) mode Sentinel-1 datasets are used to identify landslide locations. Interferograms from DInSAR obtained using Sentinel-1 VV polarization data are corrected using zenith total delay (ZTD) maps obtained from GACOS, which successfully assisted to identify major landslides in the study area. Sentinel-1 DInSAR analysis has limitations over dense vegetative regions and terrain conditions (particularly in mountainous regions) due to spatial and temporal decorrelation. With the aid of InSAR time series analysis, integration of deformation recognized and land use/land cover pattern helps experts in providing near real-time mitigation measures during a disaster event.

Research highlights

  1. 1.

    Due to heavy rainfall, Kodagu District recorded 104 landslides between 15th and 17th August 2018.

  2. 2.

    Advanced InSAR approach is adopted to identify the location of landslides in Kodagu district, Karnataka to explore the advantages of utilising SAR Datasets during an event.

  3. 3.

    GACOS corrected Sentinel-1 derived InSAR results assists in identification of larger landslides.

  4. 4.

    Limitations are experienced due to the dense vegetation and loss of coherence between the InSAR pairs.

  5. 5.

    Research suggested to use L and S band datasets along with corner reflectors installed in the mountainous regions to obtain results at higher accuracy.

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Acknowledgements

The authors would like to express their sincere thanks to Mr Sitansu Pattnaik and Mr Kumaran Narayanaswamy from kCube Consulting Services Pvt. Ltd. for their valuable contribution in the installation of GMTSAR software and providing access to the workstation. We would like to extend our hearty thanks to the European Space Agency (ESA) for providing access to Sentinel-1 data. The authors are also thankful to CDMM, VIT for their valuable support.

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Authors and Affiliations

  1. Department of Civil Engineering, Saveetha Engineering College, Chennai, India

    Suresh Devaraj

  2. Ghani Khan Chaudhury Institute of Engineering and Technology (GKCIET), Malda, India

    Kiran Yarrakula

  3. Geosciences Group, National Remote Sensing Centre (NRSC), ISRO, Hyderabad, India

    Tapas Ranjan Martha

  4. Centre for Incubation, Innovation, Research and Consultancy, Jyothy Institute of Technology, Bangalore, India

    Geetha Priya Murugesan

  5. Centre of Studies in Resources Engineering, Indian Institute of Technology Bombay, Mumbai, India

    Divya Sekhar Vaka

  6. Centre for Disaster Mitigation and Management, Vellore Institute of Technology, Vellore, India

    Samvedya Surampudi, Abhinav Wadhwa & Venkatesh Budamala

  7. Department of Civil Engineering, Sree Vidyanikethan Engineering College, Tirupati, India

    Parthiban Loganathan

Authors
  1. Suresh Devaraj
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  2. Kiran Yarrakula
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  3. Tapas Ranjan Martha
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  4. Geetha Priya Murugesan
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  5. Divya Sekhar Vaka
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  6. Samvedya Surampudi
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  7. Abhinav Wadhwa
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  8. Parthiban Loganathan
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  9. Venkatesh Budamala
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Contributions

Suresh Devaraj and Kiran Yarrakula framed the methodology and carried out the research work. Tapas Ranjan Martha, Geetha Priya Murugesan and Divya Sekhar Vaka provided technical assistance in various stages of the research work. Tapas Ranjan Martha and Kiran Yarrakula evaluated the process carried out in research work. Samvedya Surampudi, Abhinav Wadhwa, Parthiban Loganathan and Venkatesh Budamala assisted in processing the datasets and collection of GCP points.

Corresponding author

Correspondence to Kiran Yarrakula.

Additional information

Communicated by Arkoprovo Biswas

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Devaraj, S., Yarrakula, K., Martha, T.R. et al. Time series SAR interferometry approach for landslide identification in mountainous areas of Western Ghats, India. J Earth Syst Sci 131, 133 (2022). https://doi.org/10.1007/s12040-022-01876-3

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  • DOI: https://doi.org/10.1007/s12040-022-01876-3

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