Pathfinders| Automated Detection of Hazards
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.
Fire Fighter
Summary
We created a machine learning model to detect fires using MODIS data which contained brightness of pixels. Based on that, we visualized the data by putting points on a map on a web application.
How We Addressed This Challenge
We developed a web site that visualizes the fire locations on a map after detecting the locations using a machine learning model that we trained.
How We Developed This Project
We used machine learning to study the data (written in JavaScript), used JavaScript in developing a simple web page which contains a map (imported from mappa-mundi).
How We Used Space Agency Data in This Project
We used MODIS_C6 data, where we took the brightness of pixels to predict if there was a fire.
Project Demo
https://drive.google.com/file/d/1fyATXbcODYQ1RYlHKijiJBNpE4--wLD2/view?usp=sharing
Project Code
Data & Resources
https://firms.modaps.eosdis.nasa.gov/active_fire/#firms-txt
https://earthdata.nasa.gov/learn/articles/feature-articles/wildfire-articles/wildfires-cant-hide-from-earth-observing-satellites
Tags
#machine learning, #fire detection
Judging
This project was submitted for consideration during the Space Apps Judging process.