AI-Based Flood Susceptibility Mapping and Prediction Using Remote Sensing

Local Chapter Sylhet, Bangladesh Chapter

Coordinated byBangladesh ,

Status: Ongoing

Project background.

Bangladesh experiences severe flood devastation every year. A sizable population of Sylhet is affected by the flooding. It is crucial to conduct the required actions with the aid of advance technologies. With the right preparation and a flood warning system, disaster aid may be delivered quickly. Additionally, the severity may be identified and the appropriate precautions can be taken in advance thanks to a predictive machine learning model. In this situation, building a system with AI technologies can aid in tackling this local issue.

The problem.

Flood is a common natural hazard in Bangladesh. Sylhet is surrounded on the north by Meghalaya because it is situated on the northeastern edge of Bangladesh. A vast population experiences flooding every year as a result of the severe rains, and in some situations, property and crop production are also harmed. With the aid of our AI technology, it will be simpler to identify flooded areas during a disaster and to establish appropriate damage assessments and relief plans.

Project goals.

- Identifying potential flood hazard zones. - Flood extent mapping during the disaster. - Predicting flood direction during the disaster. - Possible relief plan from damage assessment.

Project plan.

  • Week 1

    Literature review and data collection of target region.

  • Week 2

    Identifying methodology and data analysis with various test cases. Implement machine learning with historical data.

  • Week 4

    Establishing refined model to identify inundated zones and a system for mapping and predicting hazard zones.

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