Volume IV-5
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-5, 265-272, 2018
https://doi.org/10.5194/isprs-annals-IV-5-265-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-5, 265-272, 2018
https://doi.org/10.5194/isprs-annals-IV-5-265-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  15 Nov 2018

15 Nov 2018

INSAR COHERENCE AND POLARIMETRIC PARAMETERS BASED CHARACTERIZATION OF FLOODED AREA – CASE STUDY OF A NATURAL WORLD HERITAGE SITE KAZIRANGA NATIONAL PARK

A. S. Dini Das, S. Kumar, A. Babu, and P. K. Thakur A. S. Dini Das et al.
  • Indian Institute of Remote Sensing, Dehradun, Uttrakhand, India

Keywords: Flood, Polarimetric decomposition, Polarimetric classification, Interferometric coherence

Abstract. Flood is a major threat to one of the UNESCO world heritage site of India-The Kaziranga National Park. Every year during the monsoon several hundreds of animals which include globally threatened species like single-horned Indian Rhinoceros of Kaziranga lose their lives due to the flood. The Synthetic Aperture Radar (SAR) can be used to monitoring the flood than the optical remote sensors because of their capability of all-weather and time-independent operability. The microwave L band is most suitable for the flood studies because of its higher penetration capability even through the vegetation. In this study, the advantages of SAR polarimetry and Interferometry of multi-temporal L band dual-pol data of ALOS PALSAR 2 were used to characterize the flooded area and also to monitor the flood extent. The H/ A/ Alpha decomposition gives a better characterization of the flooded area. The separability analysis is done with a different combination of decomposition parameters and the parameters having high-class separability between water and non-water areas are selected. Polarimetric classification using Random forest classifier is done on these selected decomposition parameters to classify the study into water and non-water areas. The classified images of different months before, during and after the flood time is used to quantitatively estimate the flood extent and for time series analysis. The Interferometric SAR coherence images along with the backscatter images are used to generate the RGB composites which also gives times series information on the flood impact.