Published Paper Details:

The AI-Powered Afforestation Planner project aims to address the growing issue of air pollution through strategic afforestation. By leveraging advanced remote sensing and machine learning techniques, the project identifies barren land areas suitable for tree planting to improve air quality. The study focuses on the Kanakapura Taluk in Ramanagara District, where land classification is performed using Google Earth Engine (GEE) with manually provided training samples. These samples were used to classify the region into urban areas, water bodies, vegetation, and barren lands using the Random Forest algorithm. The project fetches real-time Air Quality Index (AQI) data to assess pollution levels and recommends the optimal number and species of trees for planting. The final output is a web application that provides users with land classification results, barren land area calculations, and tree species recommendations tailored to improving air quality based on AQI levels. The web-based approach ensures accessibility for end users, offering an interactive tool for better environmental decision-making.