EventsThe 1st International Online Conference on Environments
Published
This submission belongs to the session S1. Environmental Assessment Methods and Management Technologies of the event The 1st International Online Conference on Environments
Published date
27 Feb, 2026
Academic Editor
author-avatarMilena Horvat
Citation
Aditya Bhalekar, Varun Gowda, Neeraj Parekh, Ashish Itolikar, Vaishali Wangikar, Assessment of Flash Flood in the Dharali Region of Uttarkashi using Sentinel-1A and Sentinel-1C SAR data, in Proceedings of The 1st International Online Conference on Environments, 2 March–4 March 2026, MDPI: Basel, Switzerland
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Assessment of Flash Flood in the Dharali Region of Uttarkashi using Sentinel-1A and Sentinel-1C SAR data

Varun Gowda 1
Neeraj Parekh 1
Vaishali Wangikar 3
1. Department of Electrical and Electronics Engineering, MIT Academy of Engineering, Alandi, Pune, Maharashtra 412105, India, India
2. Department of Humanities and Engineering Sciences, MIT Academy of Engineering, Alandi Road, Pune -412105 (MS), India, India
3. Department of Computer Engineering, MIT Academy of Engineering, Alandi Road, Pune -412105 (MS), India, India
Abstract

Floods are among the most devastating natural disasters, causing widespread damage to life, property, and infrastructure. Rapid and accurate flood detection and mapping are essential for effective emergency response and mitigation. Synthetic Aperture Radar (SAR) data, with its ability to penetrate cloud cover and operate in all weather conditions, plays a crucial role in real-time flood assessment and management. The present study uses Synthetic Aperture Radar (SAR) Sentinel-1A and Sentinel-1C (10 M resolution) datasets provided by the European Space Agency (ESA) to assess the extent of flooding in the Dharali Region of Uttarkashi, Uttarakhand, India. During the flood event, extensive cloud cover limits the applicability of optical imagery; therefore, microwave SAR data are used in the present investigation. The flood-affected zone in the Dharali region is relatively small, making change detection using 10-meter-resolution SAR data challenging. The challenges posed by comparatively low-resolution data can be addressed using threshold-based band-filtering techniques and RGB composites. The present study uses Sentinel-1A and Sentinel-1C data to detect changes in the flooded area before and after the event. The data are preprocessed using an orbit file application, geometric correction, radiometric calibration, speckle noise reduction, and terrain correction, all of which are essential for accurate geospatial analysis. A threshold-based band-filtering technique and RGB composite images are employed to detect change. This study provides useful data for rapid response in disaster management and flood mapping in the Dharali region of Uttarkashi, Uttarakhand, India, during the flash floods that occurred on 5th August 2025.

Keywords
Sentinel-1
SAR
Flood
Image Processing
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