Spaceborne C‑band SAR remote sensing–based food mapping and runof estimation for 2019 food scenario in Rupnagar, Punjab, India

Abstract

Floods are one of the most disastrous and dangerous catastrophes faced by humanity for ages. Though mostly deemed a natural phenomenon, foods can be anthropogenic and can be equally devastating in modern times. Remote sensing with its non-evasive data availability and high temporal resolution stands unparalleled for food mapping and modelling. Since foods in India occur mainly in monsoon months, optical remote sensing has limited applications in proper food mapping owing to lesser number of cloud-free days. Remotely sensed microwave/synthetic aperture radar (SAR) data has penetration ability and has high temporal data availability, making it both weather independent and highly versatile for the study of foods. This study uses space-borne SAR data in C-band with VV (vertically emitted and vertically received) and VH (vertically emitted and horizontally received) polarization channels from Sentinel-1A satellite for SAR interferometry-based food mapping and runof modeling for Rupnagar (Punjab) foods of 2019. The food maps were prepared using coherence-based thresholding, and digital elevation map (DEM) was prepared by correlating the unwrapped phase to elevation. The DEM was further used for Soil Conservation Service-curve number (SCS-CN)-based runof modelling. The maximum runof on 18 August 2019 was 350 mm while the average daily rainfall was 120 mm. The estimated runof signifcantly correlated with the rainfall with an R2 statistics value of 0.93 for 18 August 2019. On 18 August 2019, Rupnagar saw the most devastating foods and waterlogging that submerged acres of land and displaced thousands of people.