Home Articles Classification of sar data for flood inundation studies

Classification of sar data for flood inundation studies

M Ramalingam
Professor In charge
Institute of Remote Sensing, College of Engineering
Anna University, Guindy, Chennai, India
Email: [email protected]

M Vadivukkarasi
Institute of Remote Sensing, College of Engineering, Anna University,
Guindy, Chennai, India

Understanding exactly which regions a flood has affected is of vital importance for the relief effort and in order to put into place measures to limit the effects of a flood in the future. Space borne sensors have great potential to provide this information and Synthetic Aperture Radar (SAR) in particular has been used in recent years to significant effect

Flood inundation is a major hazard worldwide. Its prediction and prevention require considerable investment, apart from socio-economic consequences of severe flooding episodes. Better flood extent prediction is relevant to a significant percentage of the global population. It is also important to raise fundamental scientific issues and challenges relating to Remote Sensing, distributed environmental modeling, risk analysis and uncertainty. In recent years, remote sensing of flood plain environment has increasingly become an operational tool that may begin to solve some fundamental problems in flood conveyance estimation.

Floods world wide, beyond loss of life, also cause many millions of dollars worth of damage each year to crops and property. Understanding exactly the regions, which get affected by flood is of vital importance for the relief effort and also to put into place measures to limit the effects of flood in future. Space borne sensors have great potential to provide this information and SAR in particular has been used in recent years to significant because of SAR’s ability to observe through the cloud that is inevitable if flooding is taking place.

The primary objective of remote sensing methods for mapping flood-prone areas in developing countries is to provide planners and disaster management institutions with a practical and cost-effective way to identify floodplains and other susceptible areas and to assess the extent of disaster impact. The satellite remote sensing method is one of the many flood hazard assessment techniques that are available.

Floods are usually described in terms of their statistical frequency. A “100-year flood” or “100-year floodplain” describes an event or an area subject to a 1% probability of a certain size flood occurring in any given year. Frequency of inundation depends on the climate, the material that makes up the banks of the stream, and the channel slope. Where substantial rainfall occurs in a particular season each year, or where the annual flood is derived principally from snowmelt, the flood plain may be inundated nearly every year, even along large streams with very small channel slopes. In regions without extended periods of below-freezing temperatures, floods usually occur in the season of highest precipitation. Since the most floods in Southern Indian context are the result of heavy rainfall, it is very significant to study the phenomena.

The late 1990s inundation data were seen as a potential solution to the problem of hydraulic model validation as, while these were 0D in time, their 2D spatial format could provide ‘whole reach’ data for both distributed calibration and validation of distributed predictions. Inundation extent was also seen as a sensitive test of a hydraulic model, as small errors in predicted water surface elevation would lead to large errors in shoreline position over flat floodplain topography. The sensors available for this task are reviewed by Pearson et al (2001) so only a brief synopsis is provided here. The available sensors are:

  • Optical imagers on Airborne and Satellite platforms
  • Synthetic Aperture Radar (SAR) imagers on Airborne and Satellite platforms
  • Digital video cameras mounted on surveillance aircraft