Rapid flood inundation mapping and impact assessment using Sentinel-1 SAR data over Ghaggar River basin of Punjab, India

被引:0
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作者
Mohit Arora
Sashikanta Sahoo
Chandra Mohan Bhatt
Pradeep Kumar Litoria
Brijendra Pateriya
机构
[1] Punjab Remote Sensing Centre,Centre of Excellence in Disaster Mitigation and Management
[2] IIT Roorkee,undefined
[3] Indian Institute of Remote Sensing,undefined
[4] ISRO,undefined
关键词
Flood; SAR; GPM; backscattering coefficient; Ghaggar sub-basin;
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学科分类号
摘要
The present study focuses primarily on the rapid mapping of flood-inundated areas using high-resolution Synthetic Aperture Radar (SAR) data and its impact assessment in the Ghaggar basin during the 2019 floods. Further, a comprehensive analysis has been carried out by Global Precipitation Mission (GPM) data to investigate the intensity and frequency of precipitation over the basin. Multi-temporal, dual-polarised (VH & VV) Sentinel-1 (SAR) data have been used for mapping the flood inundated area. SAR data is very useful and most preferred for detecting flood-inundated areas in all weather and day/night time. In this study, binarisation technique was applied to separate satellite image pixel values into flooded and non-flooded groups. Thresholds for backscattering coefficient (σ0) between –22 to –30 and –10 to –20 dB have been applied for both the polarised band (VH & VV) to extract the maximum flood pixels. It was also observed that flood extent was at its peak during July 20–23, 2019, and on July 26–27, 2019, and impacted a large part of agricultural and urban patches during this time. The zonal statistics are calculated to find the inundated area over the study region. The results have been validated against Radarsat-1 images provided by NRSC-ISRO during the flood period and found an accuracy of 82% in both polarisations. VH polarisation has been found to have higher accuracy than VV polarisation. The finding reveals that ~9600 hectares and ~2700 hectares of land have been affected in Patiala and Sangrur districts. The results revealed that paddies were mostly inundated by flooding with low elevations and low slopes. From the proposed approach, it is evident that the SAR images, along with GIS data, can be used efficiently for mapping flood-inundated areas.
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