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Remote Sensing Methods for Flood Prediction: A Review.

Hafiz Suliman Munawar1, Ahmed W A Hammad1, S Travis Waller2

  • 1School of Built Environment, University of New South Wales, Kensington, Sydney, NSW 2052, Australia.

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Summary
This summary is machine-generated.

Remote sensing technologies like multispectral, radar, and LIDAR are crucial for predicting floods. This study reviews their use in disaster management, identifying gaps and proposing a new model for improved flood forecasting and risk assessment.

Keywords:
disaster managementflood forecastingflood hazard assessmentflood predictionflood risk analysisremote sensing

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Area of Science:

  • Earth and Environmental Sciences
  • Geospatial Technology
  • Disaster Management

Background:

  • Floods cause significant loss of life, infrastructure damage, and economic disruption.
  • Effective disaster management requires accurate, timely flood prediction.
  • Current flood prediction methods face challenges due to climatic and environmental uncertainties.

Purpose of the Study:

  • To review the adoption of remote sensing technologies for flood prediction over the past 20 years.
  • To classify remote sensing methods (multispectral, radar, LIDAR) used in flood prediction.
  • To identify limitations in current technologies and propose a model to overcome them.

Main Methods:

  • Systematic review of remote sensing technologies applied to flood prediction.
  • Classification of technologies based on sensor type (multispectral, radar, LIDAR) and data analysis methods.
  • Evaluation of technologies for flood prediction, risk assessment, and hazard analysis.

Main Results:

  • Remote sensing offers advanced capabilities for early flood detection and forecasting.
  • Multispectral, radar, and LIDAR technologies have varying strengths and limitations in flood prediction.
  • Gaps exist in the current application of these technologies, particularly in automated prediction and integrated modeling.

Conclusions:

  • Remote sensing is vital for enhancing the pre-disaster phase of flood management.
  • Further development is needed to improve automated flood prediction and forecasting systems.
  • The proposed model aims to address identified gaps, leading to more accurate flood prediction and extent mapping.