Automated Detection of Hazards

Countless phenomena such as floods, fires, and algae blooms routinely impact ecosystems, economies, and human safety. Your challenge is to use satellite data to create a machine learning model that detects a specific phenomenon and build an interface that not only displays the detected phenomenon, but also layers it alongside ancillary data to help researchers and decision-makers better understand its impacts and scope.

Explosive Concentration Detection

Summary

This project aims to devise a way to detect stored explosive concentrations, ammonium nitrate specifically, using space-based satellite data

How We Addressed This Challenge

The project uses ground based measurements in conjunction with satellite data to shed light on the issue of improperly stored explosives

How We Developed This Project

Recent events in Lebanon and India which caused huge losses in human life and property damage

How We Used Space Agency Data in This Project

Using population demographics, ammonium mapping

Project Demo

https://docs.google.com/presentation/d/12mWmqpnZo5N1L9Bm1SpFdoW57Jrcp1z3WkuDV2UJpd4/edit?usp=sharing

Data & Resources

NASA demographic data from Landsat

Tags
#explosive #hazards
Judging
This project was submitted for consideration during the Space Apps Judging process.