Using Satellites to Aid Flood Relief Efforts

   TwitCount

Floods are a common and often major disaster event in the Hindu Kush Himalaya during the monsoon season. The advent of the monsoon in June and over the next three months brings with it floods and landslides in the region. The Daily Star in Bangladesh reports that 20 districts in Bangladesh have been flooded, with an additional nine in danger of inundation. Al Jazeera reports that at least one million people have been affected in the Terai region of Nepal and several districts have been submerged in the Indian state of Bihar. The Department of Hydrology and Meteorology, Government of Nepal has issued warnings through its flood forecast bulletins as discharge levels in some rivers in the southern belt have exceeded alert levels. 

Timely and accurate mapping of floods is important for efficient and effective management of rescue and relief activities. It can help reduce loss and damage due to floods. 

This map shows flood inundated areas on 12 August 2017 in northern Bangladesh. It has been prepared using Sentinel-1 Synthetic-aperture radar (SAR) images acquired from the European Space Agency

The International Centre for Integrated Mountain Development (ICIMOD) has prepared flood inundation maps in view of the floods and landslides that this year’s monsoon has triggered in Bangladesh, India, and Nepal. The inundation maps have been prepared using Advanced Land Observing Satellite 2/ Phased Array L-band Synthetic Aperture Radar (ALOS-2/PALSAR), and Sentinel-1 satellite images made available by the Japan Aerospace Exploration Agency (JAXA) and the European Space Agency (ESA).  At ICIMOD, experts are using remote sensing data from active sensors to map floods, especially during the monsoon season as they can observe data even during the regular presence of cloud cover. 

The flood inundation application is being developed to provide a synoptic view of the floods in northern Bangladesh and India, and southern Nepal. 

A web-based application using ArcGIS Online, a cloud-based mapping platform, provides a synoptic overview of inundated areas in northern Bangladesh and India and southern Nepal as incessant rainfall and resulting floods and landslides have adversely affected the region. The application can be viewed here . 

The application is being updated with more inundation maps as new satellite data is processed in-house.  Satellite imagery from June onwards has been processed and interpreted as inundation maps for different dates and made available through this application. Processing and interpreting satellite data relies heavily on the availability of the satellite data, as the two revolving satellites revisit the same place at least 12 days apart. A mosaic of multiples scenes—a single Sentinel-1 satellite image scene covers an area of 250*170 square kilometres—provides a bird’s eye view of the extent of the inundation across multiple districts. 

ICIMOD is already liaising with relevant stakeholders so that the generated information can be put to further use as inputs towards relief and rescue efforts, estimation of loss and damage, and scenario assessments, including the viability of critical infrastructure like hospitals and schools in flood-affected areas. Besides providing a bird’s eye view of the floods in general, these datasets can also aid studies on how the floods have progressed this monsoon. 

The processed datasets are being made available to relevant agencies on request.

These mapping activities are part of the rapid response mapping activities at ICIMOD and are being made available under the framework of SERVIR-Hindu Kush Himalaya (SERVIR-HKH). ICIMOD hosts the SERVIR-HKH hub and is part of a larger SERVIR network—a joint development initiative of the United States Agency for International Development (USAID) and the National Aeronautics and Space Administration (NASA).

NB: The web application is regularly updated to include inundation maps as more satellite imagery becomes available. Data used in the application can be downloaded from ICIMOD’s Regional Database System