| In Remote Sensing and Machine Learning in Conservation: Applications and Techniques, readers will discover how cutting-edge technology is transforming our understanding of the natural world. This book explores how remote sensing and machine learning are being used to monitor wildlife populations, map critical habitats, predict the effects of climate change, and identify poaching hotspots. From the analysis of satellite imagery to the use of drones and artificial intelligence, this book provides a comprehensive overview of the latest tools and techniques available to conservationists. Written by a renowned expert in spatial information research, this book introduces readers to the exciting new possibilities opened by the combination of remote sensing and machine learning. Early chapters provide an overview of both emerging technologies and their integration into habitat mapping, species distribution, environmental monitoring, and climate change adaptation. Central chapters explore real-world applications and case studies for combating poaching, managing urban expansion, controlling invasive species, and more. Final chapters explore the funding and policy landscape and conclude with a reflection on the role of these technologies in transforming conservation practices. By equipping readers with an overview of these technologies, case studies of their real-world applications, and sample code, datasets, and open-source tools, Remote Sensing and Machine Learning in Conservation: Applications and Techniques promotes the innovative use of these technologies to address global environmental challenges. This is an essential resource for conservationists, resource managers, environmental scientists, and academics studying novel technological applications to conservation issues. |
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