Remote Sensing in Ecological Environments: Innovations and Achievements, Volume II

This Research Topic is Volume II of a series. The previous volume, which has attracted over 15k views can be found here:
Remote Sensing in Ecological Environments: Innovations and Achievements
Remote sensing is a powerful tool for monitoring and understanding the Earth’s ecosystems and their changes in terms of land cover and use, vegetation, soil, water, atmosphere, climate, and so on. These observations play a crucial role in revealing the spatial patterns, temporal dynamics, and causal mechanisms behind environmental phenomena and processes. With the rapid development of satellite sensing systems and artificial intelligence, scientists have achieved significant breakthroughs in the field of environmental remote sensing in recent decades. These advancements have not only enriched our understanding and management of the Earth’s environment and its changes but also contributed to addressing global environmental challenges and promoting sustainable development.

This Research Topic aims to highlight the latest innovations and achievements of remote sensing in ecological environments advancing our understanding of Earth's diverse ecosystems and dynamic processes. We welcome original research and review articles that explore the applications and innovations of satellite remote sensing measurements in monitoring changes in the ecological environment. This includes analyzing and modeling the impacts of natural events and human activities on ecosystems, as well as identifying management solutions that foster ecosystem sustainability. Additionally, we encourage contributions that explore the integration and fusion of remote sensing with cutting-edge techniques, such as artificial intelligence, deep learning, and cloud computing for data processing and analysis, pattern recognition and prediction, spatial modeling, and decision-making.

We welcome papers focusing on, but not limited to, the following areas of applications and techniques:

Applications:
• Land cover/land change detection
• Climate change
• Ecological parameters and ecosystem functions
• Ecosystem service assessment
• Disaster monitoring
• Impacts of human activities on ecosystems

Techniques & Methods:
• Artificial intelligence, deep learning, and machine learning for data processing and analysis
• Robots and autonomous systems for environmental remote sensing
• Novel advances in collecting collocated spatiotemporal data
• Data fusion and assimilation in environmental remote sensing
• Data-driven applications in environmental remote sensing
• Emerging technologies for environmental remote sensing