| Idea Name: |
Flood Mapping |
| Slogan: |
Mapping floods to save lives |
| Supervisor Name: |
Safdar Abbas |
| Supervisor Designation: |
Assistant Professor |
| Supervisor School: |
SEECS |
| Supervisor Department: |
SEECS |
| Contact number: |
03335734215 |
| Email ID: |
[email protected] |
| Abstract: |
| Remote sensing data has repeatedly shown its interest and usefulness during the various phases of the flood management process by providing an overview of the situation on the ground efficiently and effectively. This project will aim to use computer vision and satellite imagery to visualize the impact of current floods and identify areas at risk of flooding. |
| What is the unmet need in society that your idea will fulfill ? |
| The unmet need for flood mapping is the lack of accurate and up-to-date information about potential flood areas, especially in the remote areas of Pakistan. This lack of information can hinder emergency response efforts, as well as long-term planning and risk assessment. |
| Who needs it ? How many would benefit ? |
| Flood mapping can benefit a wide range of individuals and organizations such as emergency responders, government agencies, insurance companies, property owners, community planners, environmental organizations, etc. Thus, it is a valuable tool for improving flood preparedness and response. |
| How will the solution works |
| This project will aim to train a convolutional neural network architecture for flood segmentation to distinguish water and land areas. Also, we will use the segmentation model on satellite images of areas before and during the flood image. We will generate a flood extent map of the flood-affected area by comparing the segmentation results on a pixel-to-pixel basis. This would be used to create a dashboard to visualize the impact of multiple floods and assess the impact of future floodings. |
| Who are your competitors ? How is your solution different |
| A few international competitors include Flood Insurance Rate Map (FIRM), AquaSIM, FloodRunnery, etc, and Hydrology.nl in Pakistan. the distinguishing factor of our system will be the better accuracy and precision of our flood maps, the speed, reliability, and user-friendliness of our mapping system. |
| Status: |
new |
| Entry Date & Time: |
2022-12-15 (1657) |
