FIEC Innovation | Spot That Fire V3.0

Spot That Fire V3.0

Recent wildfires worldwide have demonstrated the importance of rapid wildfire detection, mitigation, and community impact assessment analysis. Your challenge is to develop and/or augment an existing application to detect, predict, and assess the economic impacts from actual or potential wildfires by leveraging high-frequency data from a new generation of geostationary satellites, data from polar-orbiting environmental satellites, and other open-source datasets.

Forest fire prediction worldwide

Summary

This project's main objective is to predict as closely as possible to be able to detect forest fires before they occur around the world. That is why we raised clear and precise ideas of what we wanted to raise to find the best solution to this Spot That Fire project. The project consists of pre-processing the data obtained using "Python" as a programming language to train our data and predict forest fires worldwide so that they can be detected immediately, either using a mobile application or another machine learning tool.

How We Addressed This Challenge

We developed a machine learning solution that can predict forest fires and thus quickly detect a forest fire anywhere in the world.

It is important because it allows you to be aware and know when a forest fire may occur either by using an application with AI that serves as prevention.

We try to predict and decree the fire alerts but we only get to capture the ideas and we do not get to the implementation as such.

It works in a collaborative notebook that allows us to have an interactive environment and to determine the prediction and detection of a fire.

We hope that this project will be of great help and not only that but that it can be seen by other people who want to know when a forest fire can occur.

How We Developed This Project

What inspired us to carry out this challenge was because of what happened in Australia with the fires that caused a great impact worldwide, in this way to prevent other forest fires that can occur in the world.

The approach to carrying out this project is that we saw that the world itself has been greatly affected by these natural disasters that put the environment and animals at risk, and we decided to develop this project with great skill.

Used tools

  • We use the programming language " Python".
  • We use resources provided by NASA
  • We use Colab that allows us to write and execute codes in Python.

We had trouble getting the data from NASA, but we were able to find it in the end. Also at the time of being able to predict the data efficiently we could not arrive at a solution due to the lack of other data that we could not find.

We managed to take the challenge forward with all possible resources and thus complete the project satisfactorily.

How We Used Space Agency Data in This Project

The data provided by NASA (csv files) were used, in a way that greatly influenced our project, since with these data we try to predict forest fires at a global level or by geographical area. But if we could implement valuable information to solve the problem

Project Demo

https://drive.google.com/file/d/1_dRJ9d_u70ivjpNcndWUrFwBf3xCl90t/view?usp=drivesdk

Project Code
Data & Resources

We use the data provided by NASA.

Another resource was the Colab notebooks that allow us to combine executable code and rich text in a single document.

Tags
#PreventForestFires #Innovate
Judging
This project was submitted for consideration during the Space Apps Judging process.