Year: 2025
Type: article
Abstract: This project investigates climate variability across the districts of Maharashtra, India, focusing on key environmental indicators such as temperature, CO₂ emissions, rainfall, deforestation, urban growth, and an overall Climate Impact Index. The core objective is to examine whether these factors show significant differences between districts using statistical analysis through one-way ANOVA. To enhance predictive capabilities, a machine learning model based on regression is developed using Python. The model is built with libraries such as Pandas, NumPy, and Joblib, and the environmental data is stored and managed in MongoDB to ensure efficient handling of large datasets. The outcome of this project provides valuable insights into localized climate trends, supporting targeted environmental strategies and district-level policy-making. Key Words: one way ANOVA, Deforestation, Regression Model, CO₂ Emission, Urbanization.
DOI: 10.55041/ijsrem50788
Author: Ananda Mane
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4411412112