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.

Woodpile: acessible way to save our home.

Summary

We chose the “Spot that fire V3.0” challenge, in order to develop a platform aimed mainly at the government and public agencies, where an individual could consult a particular location, and according to images coming from satellites and the temperature of the day , the climate present in the region of consultation, the date and season of the year, in addition to capturing data on the fire history of that particular location, would be able to present the areas of greatest risk of fire, and thus already issue warning messages to local authorities, in order to facilitate the focus of firefighters, and other authorities.

How We Addressed This Challenge

We developed a website called Woodpile (https://woodpile.biz/) aimed at help people and the government take care of our precious forest around the world as well as helping native people that live among the nature and wild animals that live in the forest. Our project is very important because lately all around the world we see news about forest being burned out, like in Australia, Amazonas and recently pantanal in Brazil, with our website people could easly access it and see places that are currently in fire as well as places that are likely to caught on fire duo to climate changes, temperature, season of ther year etc. The website receives live images from geo-stationary satellites from the world and pass those images through a Deep learning algorithm that can return if a forest fire has been detected. With our project we hope to soften world-wide wild fires in the forest as well as help native people to be aware of nearby fires, also we aim to inform people about what is happening in the world, because a lot of people dont even know what is happening and government normaly dont tell them what they to wrong

How We Developed This Project

We got inspired to do this project because in Brazil we see a lot of forest fires happening and teh government dont even tell if they will do something to turn off the fire or help minimize the damage caused. To make this project happen we used web-development languages like HTML, CSS and Wordpress to make our website, in addition to other tecnologies such as bootstrap and Jquery. As for a Deep learning alrorithm we tried to use IBM Visual Recognition to exemplify what we are aiming to do, unfortunately we were unable to easily make use of the api. As for achievements we as a team construct a well-design, visually atractive and aesthetically well-built interface to be our website, on the other hand our main problem was both, organization given the time span that we have to work on and the functionality of our api, since none of our members previously knew how to work with or build a working Deep learning/ IA / Machine learning, since this was our first hackathon we hope to get better and better each time and learn a lot of things in the path

How We Used Space Agency Data in This Project

In our project we used space satellites images to pass pass through a deep learning algorithm and return if a forest fire has been detected in that region, for clear and faster forest fires detection,  

Project Demo

https://1drv.ms/p/s!Atq-lRxliA6YcG88iIYtMvMjdTs?e=PCXeYe

Data & Resources

In our project we used data from geo-stationary satellites from NASA, one in specific was MODIS steallite, launched by nasa in 1999 and in 2002. We also got some images from GeoNEX (www.nasa.gov/geonex) and FIRMS(Fire Information for Resource Managment System) among others satellite images with forest being burned out in the world.

Tags
#fire #forestfire #forest #save #the #planet #native #animals #animal #deeplearning #ia #government #firefighters #website #tree #savethetrees #help #forestneedus
Judging
This project was submitted for consideration during the Space Apps Judging process.