Abstract
This research paper aims to analyze the NASA Satellite image dataset in order to monitor and understand forest cover changes over the course of the past year. Forest cover change is a crucial environmental indicator, with implications for biodiversity, climate regulation, and ecosystem services. By employing advanced remote sensing techniques and machine learning algorithms, this study seeks to provide insights into the spatial and temporal patterns of forest cover change and its potential drivers. The research methodology involves data preprocessing, feature extraction, classification, change detection, and trend analysis. The results will contribute to a better understanding of the dynamics of forest ecosystems and support informed decision-making for sustainable land management. Keywords: Satellite imagery, forest cover change, remote sensing, data analysis, machine learning, classification, change detection.
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