📚 Volume 30, Issue 4
📋 ID: 87tKU3m
Authors
Li Wei, Saanvi Patel, Lucas Moreau
, Matthew Bernard, Victoria Olsson
Department of Environmental Sciences, Tsinghua University, Beijing, China; School of Ecology, Indian Institute of Science, Bangalore, India; Institute of Biodiversity, University of Montpellier, Montpellier, France
Keywords
Biodiversity
Remote Sensing
Machine Learning
Ecosystem Monitoring
Conservation
Abstract
Biodiversity assessment is crucial for understanding ecosystem health and ensuring environmental sustainability. Traditional methods of biodiversity monitoring are often labor-intensive and limited in spatial and temporal coverage. In this study, we develop an innovative framework that integrates remote sensing data with machine learning algorithms to enhance the accuracy and efficiency of biodiversity assessments. By utilizing satellite imagery and ground truth data, we implement a system that can identify and monitor diverse species across large landscapes. Our results demonstrate significant improvements in detecting species richness and distribution patterns, providing valuable insights for conservation efforts.
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📝 How to Cite
Li Wei, Saanvi Patel, Lucas Moreau , Matthew Bernard, Victoria Olsson (2023).
"A Novel Approach to Biodiversity Assessment Using Remote Sensing and Machine Learning".
Wulfenia, 30(4).
