A remote sensing technique for identifying geometry and geomorphological features of the Indo-Burman frontal fold belt

Abstract

Satellite images are capable of displaying prominently the geometry and morphology of folds, especially when these have large spatial extent. The frontal part of the Indo-Burman fold belt, falling in parts of Bangladesh and north-east India, has developed into exemplary linear N–S oriented doubly plunging folds in late Tertiary sedimentary rock sequences and are arranged in a set of alternating ridge-forming anticlines and valley-forming synclines. Formation of these folds is attributed to E–W oriented compressional tectonics resulting out of eastward subduction of the Indian plate below the Burmese plate. Fold types present in the area appear to be simple but the present fold geometrical arrangement reveal some interesting features. The 90-m SRTM-DEM (Shuttle Radar Topographic Mission–Digital Elevation Model), remote sensing techniques, principal component analysis and resolution merging were used to understand the geometry and morphology of the folds covering a large area, through comparative assessment and enhancement of the structural features. This study includes identification of: multi-folds within a visibly single entity; the overlapping nature of folds and the interrelation between anticlines; the geometry of fold noses; fault-affected fold limbs causing bulging; and anticline bifurcation and formation of elliptical and cuspate synclines; as well as recognition of exposed eroded-out folded layers of the anticline and the effect of deformation and faulting. The doubly plunging nature of the folds and higher topography at the middle latitudes of the study area could have formed due to up-arching tectonic activity.

Acknowledgement

The authors are thankful to Department of Science and Technology (DST), Government of India for overall support for this work. Landsat ETM+ and PAN data are taken from Global Land Cover Facility (GLCF), University of Maryland, USA. 90-m SRTM-DEM are taken from Consortium for Spatial Information (CGIAR-CSI). Google Earth was very useful to cross-check the morphology and topography of geological features on images of high resolution.