Large-Scale Flood Hazard Monitoring and Impact Assessment on Landscape: Representative Case Study in India

Bijay Halder, Subhadip Barman, Papiya Banik, Puja Das, Jatisankar Bandyopadhyay, Fredolin Tangang, Shamsuddin Shahid, Chaitanya B. Pande, Baqer Al-Ramadan and Zaher Mundher Yaseen ()
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Bijay Halder: Department of Remote Sensing and GIS, Vidyasagar University, Midnapore 721102, India
Subhadip Barman: Centre for Environmental Studies, Vidyasagar University, Midnapore 721102, India
Papiya Banik: Department of Geography, University of Calcutta, Kolkata 700019, India
Puja Das: Department of Geography, Cotton University, Guwahati 781001, India
Jatisankar Bandyopadhyay: Department of Remote Sensing and GIS, Vidyasagar University, Midnapore 721102, India
Fredolin Tangang: Department of Earth Sciences and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia
Shamsuddin Shahid: Department of Water and Environmental Engineering, Faculty of Civil Engineering, Universiti Teknologi Malaysia (UTM), Skudia 81310, Johor, Malaysia
Chaitanya B. Pande: Indian Institute of Tropical Meteorology, Pune 411008, India
Baqer Al-Ramadan: Architecture and City Design, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia
Zaher Mundher Yaseen: Civil and Environmental Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia

Sustainability, 2023, vol. 15, issue 14, 1-17

Abstract: Currently, natural hazards are a significant concern as they contribute to increased vulnerability, environmental degradation, and loss of life, among other consequences. Climate change and human activities are key factors that contribute to various natural hazards such as floods, landslides, droughts, and deforestation. Assam state in India experiences annual floods that significantly impact the local environment. In 2022, the flooding affected approximately 1.9 million people and 2930 villages, resulting in the loss of 54 lives. This study utilized the Google Earth Engine (GEE) cloud-computing platform to investigate the extent of flood inundation and deforestation, analyzing pre-flood and post-flood C band Sentinel-1 GRD datasets. Identifying pre- and post-flood areas was conducted using Landsat 8–9 OLI/TIRS datasets and the modified and normalized difference water index (MNDWI). The districts of Cachar, Kokrajhar, Jorhat, Kamrup, and Dhubri were the most affected by floods and deforestation. The 2022 Assam flood encompassed approximately 24,507.27 km 2 of vegetation loss and 33,902.49 km 2 of flood inundation out of a total area of 78,438 km 2 . The most affected areas were the riverine regions, the capital city Dispur, Guwahati, southern parts of Assam, and certain eastern regions. Flood hazards exacerbate environmental degradation and deforestation, making satellite-based information crucial for hazard and disaster management solutions. The findings of this research can contribute to raising awareness, planning, and implementing future disaster management strategies to protect both the environment and human life.

Keywords: Assam flood inundation; vegetation degradation; risk assessment; Google Earth Engine; Sentinel-1 SAR data (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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