A Flood of Ideas

Your challenge is to develop a new methodology or algorithm that leverages Earth observation and critical infrastructure datasets to estimate damages to infrastructure caused by flooding. Make a measurable impact on the resilience of nations by helping the Earth observations community contribute to the United Nations’ primary effort to reduce disaster risk!

Argus of the floods (Argus is a Greek mythological creature that constantly monitors )

Summary

Our Problem statement is to discover ways that Earth observations can contribute to the monitoring and reporting of critical infrastructure impacts from flood events across the worldFloods are the most commonly occurring Natural disaster in the world and the most fatal. Our project uses Machine learning techniques to identify the before and after effects of floods and map it. Using the differences obtained we are able to detect the changes or damages that floods have impacted. We also use CSV files to generate an output where we intensity plot the outcome of the flood by comparing it to the previously acquired data. We can efficiently evaluate the damages caused to the infrastructure

How We Addressed This Challenge

Our code can detect the structural changes that happen to a particular place due to floods or water damage. We are able to remove interferences such as living conditions and clouds in the satellite images that we have acquired to produce the final outputs. By having an areal estimation it is easier to calculate the total infrastructural damage to check on the ground since when a flood happens it leads to series outbreaks such as cholera etc. Which makes on-site surveys dangerous and also the damaged buildings poses a threat to anyone who visits there . Our project eliminates the need to being physically present in the spot of disaster. We hope to help all countries world to get an estimate of the flood damage so that precautions ae taken .

How We Developed This Project

All the members of this team have faced various problems due to floods in our home towns, this gave us the motive too take this topic . We have developed the code using python language. We had various approaches where we thought about various factors such as clouds and other obstructions in the atmosphere after flooding after various rounds of tails errors and thing we were able to successfully develop a project . We faced problems due to lack of raw data of the post and pre floods ,but we did over come by thinking about the image data that satellites collects

How We Used Space Agency Data in This Project

We uses the images provided by NASA in its earth observatory website to generate the outputs of the before and after floods, where we could asses the damage and differences .We did go through all the space agency data to get a clear idea on how to proceed.

Tags
#flooding, #water , #machinelearning , #infrastructure , #satelliteimages
Judging
This project was submitted for consideration during the Space Apps Judging process.