Natural Calamities are events which are spontaneous and very difficult to predict. The fatalities are significant and all we can do is to save once we are hit by one. But now with advancing technology we must devise methods to predict natural disasters. We can no longer wait for the event to come and then save ourselves.
In this hackathon our focus is on Forest Fires. Forest fires are very frequent in areas including middle Africa and also California.
Fire Detection GIS Data is available at: https://fsapps.nwcg.gov/gisdata.php We will be using this data for our model and prediction.
We are aiming to develop a Machine Learning based model to predict Wildfire along with its intensity. The dataset contains reading for various sources including satellite images and GIS Data. Our model will take care of the Time Stamps along with the implementation.
CNN Networks will be trained to detect forest fires from Satellite imagery and this would help in early detection of wildfire. The GIS attributes will also be utilized during the prepraration to explore the possiblity of predicting Wildfire even before analysis from the Imagery data.
The impact of this project is quite significant and would help in faster relocation and quick response to the upcoming Wildfire. Wildfire causes emormous loss to the natural treaure of the country/state and bring discomfort to the life of parties involved.
Hence, we are quite motivated in providing state of art CNN Implementation of the Global GIS Data to obtain interesting resuls
Looking forward to a competitive participation in Codefundoo 2018.