ARIA-SG Project

ARIA-SG Flood Proxy Map: Laos Floods, 6 Sep 2019, v0.1 This preliminary map shows areas that are likely flooded (shown by light blue pixels of 30 m in size) in southern Laos due to heavy rains brought by Tropical Storm Podul a week before, and Tropical Depression Kajiki. The map extents are indicated by the white polygon. This map should be used as a guidance to identify areas that are likely flooded, and is less reliable over urban and vegetated areas. Derived from synthetic aperture radar data acquired by the Copernicus Sentinel-1 satellites operated by the European Space Agency (ESA) before (3 Apr) and during (6 Sep) the event. Analysed by the ARIA-SG team at the Earth Observatory of Singapore (EOS), using the ARIA-SG system originally developed by NASA-JPL and Caltech. Data processing used an AWS Open Dataset of Copernicus Sentinel-1 data for the Asia region (https://registry.opendata.aws/sentinel1-slc-seasia-pds).

The aims of this project are to use remote-sensing data to:
• Support regional and local stakeholders and decision makers by monitoring and mapping regional hazards, environmental crises, and natural disasters
• Develop cutting-edge algorithms for hazards monitoring and disaster mapping (e.g., using machine learning techniques).
 

In particular, we are using Synthetic Aperture Radar (SAR) to make timely maps of disasters (e.g., flood extents, building damage from earthquakes and typhoons) for post-disaster situations, and to provide routine monitoring of ground deformation that is related to potential hazards.

This project is in collaboration with the NASA Jet Propulsion Laboratory and Caltech, and uses their Advanced Rapid Imaging and Analysis (ARIA) system to process the SAR data in a cloud-computing environment.

Disaster-response maps from this project can be downloaded at:
http://ariasg-products.earthobservatory.sg/

Updates on our work, including posting of disaster-response products can be found at:
https://twitter.com/eos_aria

Funding Sources: 

  • Earth Observatory of Singapore
  • National Research Foundation

Project Years: 

2018
2019