Leveraging Deep Learning for Sustainable Forest Management: Monitoring Deforestation and Biodiversity Loss
Abstract
Forests are critical for biodiversity, climate stability, and human livelihoods, yet they face unprecedented threats from deforestation and habitat degradation. This paper proposes a deep learning approach to monitor forest health and detect deforestation in real time using satellite imagery and remote sensing data. Our model identifies patterns in vegetation loss and can differentiate between natural and human-induced changes, offering conservationists timely insights for intervention. Case studies in tropical forests illustrate how deep learning can support sustainable forest management by promoting proactive measures to preserve biodiversity and reduce carbon emissions from deforestation.
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