Performance evaluation of multi-parametric synthetic aperture radar data for geological lineament extraction

ABSTRACT

The demarcation of linear geomorphological features due to fracture systems, underlying or exposed faults, drainage lines etc. from satellite images has been one of the most widely used applications in geological studies. Synthetic Aperture Radar (SAR) data has been recognized as an effective tool for lineament extraction due to its unique sensitivity to subtle topography, soil moisture and texture. However, the typical SAR sensor parameters such as frequency, polarization and look direction plays a vital role in enhancing the performance for a specific application. Therefore, the study aims to analyse the multi-frequency (C- and L-band), multi-polarization (like and cross) and multi-look direction SAR data for geological lineaments extraction. In this paper, Sentinel-1 and Advanced Land Observation Satellite (ALOS)-2 Phased Array type L-band Synthetic Aperture Radar (PALSAR)-2 datasets acquired over a part of the Indo-Burma ranges of Manipur region (northeastern part of India) are considered for analysis. The lineaments extracted from SAR datasets are compared with reference to lineaments provided by the Geological Survey of India (GSI) through their portal. The study observes that the like-polarization C-band SAR data provide optimal results for this application. It is also observed that the integration of lineaments extracted from multi-look SAR data can significantly improve the performance than that derived from single-look data. Overall, the study also focuses on the spatial distribution of lineaments with respect to the local structural regime for a better understanding of the regional tectonic setup.

Acknowledgements

The authors would like to thank European Space Agency for providing Sentinel-1 SAR data and The Japan Aerospace Exploration Agency for ALOS PALSAR-2 mosaic data. The Bhukosh Portal of GSI is acknowledged for providing lineaments in 1:50,000 scale. Thanks are also due to Google (LLC) for Google Earth and Google Earth Engine Cloud Platform. The authors would also like to thank the editor and anonymous reviewers for their insightful comments and recommendations.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.