Analysis of Increase in Average Temperature on Earth, its Causes and Wildfire Using Machine Learning Techniques

Abstract

We are observing a visible change in climate patterns. Its significant effects are overall temperature increase, sea-level rise because of massive ice melting, and other extreme weather events.Wildfires are a significant issue in the whole world and cause devastation year after year. Due to this change in climate pattern, we are observing increase rates of Wildfire. Now, the question arises of the increase in the overall world's temperature, the reason for this cause, or any other reason for it.Initially, we are handling the Earth surface temperature data, which has data ranging back to 1750. From this data, we are trying to visualize the increase in average temperature around the world. Accordingly, these visualizations lead us to create machine learning models for estimation and prediction purposes for our future work.Secondly, we have a government-funded dataset of wildfire data that we are using to generate visualizations of the wildfire scope, frequency, and causation. And eventually, these visualizations guided us to create some machine learning models for estimation and prediction.Next, we combined the above datasets based on the unique features present in them for our final observation correlating the increase in temperature and wildfire causes.In brief, we want to know which cause of the Wildfire affects the increase in temperature and how much in terms of some values.There is a dynamic web page deployed with cloud service. The application supports user input to generate visualizations for parameters of interest dynamically; also, users can provide details like latitude, longitude, year, month, state, fires, and perform causation predictions with the trained models.