658
Views
36
CrossRef citations to date
0
Altmetric
Original Articles

Using multi-temporal remote-sensing data to estimate 2011 flood area and volume over Chao Phraya River basin, Thailand

, , &
Pages 243-250 | Received 28 Apr 2012, Accepted 20 Aug 2012, Published online: 05 Sep 2012
 

Abstract

In 2011, when Thailand faced its most severe flood disaster in 50 years, the Geo-Informatics and Space Technology Development Agency provided flood affected data to support government agencies during the crisis, specifically synthetic aperture radar (SAR) imagery, optical satellite imagery and a digital elevation model (DEM). These data were combined with water level data from gauge stations to map the area flooded and to estimate water volume in near real time to support decision-making for flood relief operations.

However, difficulties were encountered when dealing with different kinds of spatial data and different application techniques. Problems included inconsistent acquisition schedules for different satellites, different image resolutions and different data acquisition modes, i.e. ScanSAR Wide and Wide modes. DEM accuracy also proved to be an issue. Current work is underway to improve the satellite image acquisition planning and DEM accuracy and increase the number of gauge stations in the flood affected area so as to improve the accuracy, reliability and usefulness of geoinformatics data for future disaster management.

Acknowledgement

The authors highly acknowledge the generous and dedicated work of GISTDA flood working team.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 83.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.