Applications of Remote Sensing for Environmental Ecology

The transformation of environmental ecology from a model-oriented to a data-driven field requires robust methods to reveal the interactions among the organisms and their complex environment. The ongoing transformation of environmental ecology, driven by advancements in remote sensing and artificial intelligence (AI), offers unprecedented opportunities for understanding and managing ecosystems. To achieve this aim, this Special Issue focuses on the applications of remote sensing for environmental ecology, with a particular emphasis on the integration of AI algorithms. We welcome original research, reviews, and innovative case studies that demonstrate novel uses of remote sensing data—acquired from satellites, drones, and other platforms and sensors—in conjunction with AI techniques, such as machine learning and deep learning, in shaping the future of environmental ecology. Theoretical and practical cross-disciplinary studies that highlight the synergy between cutting-edge AI technologies and remote sensing in addressing ecological challenges and enhancing our understanding of complex environmental systems are encouraged. Topics of interest include, but are not limited to, habitat monitoring and mapping, climate change impact assessment, biodiversity monitoring, water resource management, forest and vegetation analysis, soil and land degradation, urban livability assessment, and ecological disturbance detection and restoration monitoring at regional and global scales.

We look forward to receiving your contributions.

 

Dr. Mohammad Sharif
Dr. Xuan Zhu
Guest Editors

Manuscript Submission Information

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