Jadhav et al. (2026) Multi-Temporal Flood Assessment of Mahad, Maharashtra Hybrid Method of Using Sentinel-1 SAR and NDWI Technique on Google Earth Engine

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Identification

• Journal: Springer Link (Chiba Institute of Technology)
• Year: 2026
• Date: 2026-04-01
• Authors: Yash Jadhav, Yash Dhotre, Sufiyan Rawoot, Parmeshwar Gurushette, Shravan Kshirsagar, S. R. Bhagat, Mandar Malandkar
• DOI: 10.1051/e3sconf/202670205001/pdf

Research Groups

Not explicitly mentioned in the provided text.

Short Summary

This study presents a multi-temporal hybrid approach combining Sentinel-1 SAR and Sentinel-2 NDWI data on Google Earth Engine to assess flood inundation in Mahad, India, from 2020 to 2024, demonstrating its effectiveness in localizing true flood zones, especially during monsoon cloud cover.

Objective

• To develop and apply a multi-temporal hybrid flood detection approach using Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 Normalized Difference Water Index (NDWI) data to assess flood inundation status in low-lying urban centers, specifically Mahad, India, from 2020 to 2024.

Study Configuration

• Spatial Scale: Mahad, Raigad district, Maharashtra, India.
• Temporal Scale: 2020 to 2024.

Methodology and Data

• Models used: Hybrid flood detection approach combining SAR backscatter ratio thresholding and NDWI-based filtering, implemented on Google Earth Engine (GEE).
• Data sources: Sentinel-1 Satellite (Synthetic Aperture Radar (SAR)), Sentinel-2 Satellite, Normalized Difference Water Index (NDWI).

Main Results

• The hybrid model effectively localized 'true' flood zones and improved spatial consistency in identifying flood-prone areas.
• A significant flood event occurred in 2021, with an inundated area of 28,879,300 square meters based on both SAR and NDWI data.
• In 2023, only a small interactive flooding area was noted after dredging.
• The hybrid approach proved feasible for flood detection, particularly during cloud cover in the monsoon season.

Contributions

• Consistent integration and repeated multi-year application of established SAR and NDWI techniques for flood detection using Google Earth Engine.
• Development of a robust hybrid approach effective during monsoon cloud cover, reducing misclassification in urban and vegetated areas.
• Demonstration of a repeatable and scalable workflow for long-term flood assessment and regional flood monitoring.

Funding

Not explicitly mentioned in the provided text.

Citation

@article{Jadhav2026MultiTemporal,
  author = {Jadhav, Yash and Dhotre, Yash and Rawoot, Sufiyan and Gurushette, Parmeshwar and Kshirsagar, Shravan and Bhagat, S. R. and Malandkar, Mandar},
  title = {Multi-Temporal Flood Assessment of Mahad, Maharashtra Hybrid Method of Using Sentinel-1 SAR and NDWI Technique on Google Earth Engine},
  journal = {Springer Link (Chiba Institute of Technology)},
  year = {2026},
  doi = {10.1051/e3sconf/202670205001/pdf},
  url = {https://doi.org/10.1051/e3sconf/202670205001/pdf}
}