Enhancing Flood Area Mapping Accuracy Using Advanced SAR Data Processing
S. Pazhanivelan, K. P. Ragunath, N.S. Sudarmanian, S. Satheesh, K. Sneka
International Journal of Environment and Climate Change · pp. 783–799 · Published 30 Dec 2024
10.9734/ijecc/2024/v14i124662Abstract
Aim: To assess the spatial distribution of floods in 2024 using remote sensing data, specifically Synthetic Aperture Radar (SAR), a powerful tool in flood monitoring and mapping due to its ability to capture data under all weather conditions, including rain and cloud cover provides high-resolution imagery suitable for identifying and analyzing flood extents. Study Area and Duration: North-Eastern districts of Tamil Nadu viz., Tiruvannamalai, Ranipet, Chengalpat, Kancheepuram, Tiruvallur, Viluppuram, Cuddalore, Nagapattinam, Thanjavur, Tiruvarur, Kallakurichi and Mayiladuthurai. Methodology: Flood mapping uses imagery collected from the European Space Agency's (ESA) Sentinel-1A satellite to identify and map flooded regions. Flood mapping receives assistance from this satellite's C-band SAR sensor, which can capture images in any weather condition without affecting the data. Results: The flood vulnerability assessment using Sentinel-1A satellite data has provided critical insights into the extent and impact of flooding across Tamil Nadu in 2024. With a total of 90,369 hectares of agricultural land affected, the study highlights the urgency of implementing targeted flood management strategies. 350 ground truth points were collected, out of which 309 points coincided with the flood-affected areas. Among these 309 points, 214 were flood points and 95 were non-flood points. The overall accuracy of the results was 90.00 per cent. The producer and user accuracy for flood-affected areas was 92.10 per cent and 93.40 per cent, respectively. The producer and user accuracy for non-flood areas. was 85.30 per cent and 82.70 per cent with Kappa index of 0.80. Conclusion: These findings underscore the importance of integrating advanced remote sensing technologies with ground-level data to better understand flood dynamics and provides a foundation for sustainable disaster risk management and resource allocation, ensuring long-term agricultural and environmental security in Tamil Nadu.
Cited by 1
1 citation reported by external sources — individual citing-article records aren't available to list yet.
Related research
- Seasonally Separated Logistic Models to Assess the Impact of Climate Variables on Occurrence of Rainfall over the Bagmati River Basin of Nepal — shares topic coverage
- Assessing the relationship between outbreaks of the African Armyworm and Climatic Factors in the Forest Transition Zone of Ghana — shares topic coverage
- Present and Future Climate Change in Indian Cardamom Hills: Implications for Cardamom Production and Sustainability — shares topic coverage
- The Environmental Quadrupole: Forest Area, Rainfall, CO2 Emissions and Arable Production Interactions in Cameroon — shares topic coverage
- Climate Change and Shift in Cropping System: From Cocoa to Maize Based Cropping System in Wenchi Area of Ghana — shares topic coverage
Article metrics
Real usage data collected on this platform.
0
Page views
0
PDF downloads
0
Outbound clicks
1
Citations
Views by country
Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".
No views recorded yet.
Traffic sources
Referring site, by host.
No traffic recorded yet.
Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.