This Research Topic entitled “Big Data and Artificial Intelligence Technologies for Smart Forestry” welcomes papers dealing with forest monitoring and analysis and presents the scientific research achievements of emerging technologies such as big data, remote sensing and IoT applied in the field of forestry.
Forest monitoring based on SAR, Lidar, optical remote sensing, and IoT can provide support for large spatial scale forest management and decision-making. With the development of big data technologies, the speed of smart forestry construction and the level of forestry information management has significantly improved. On the one hand, high-performance architectures for big data can significantly improve the efficiency of large-scale forestry research; on the other hand, artificial intelligence models can effectively extract the vegetation features and ecological parameters of the forest from the remote sensing data. Therefore, the development, integration, and application of big data technology have become the focus of forestry research. Meanwhile, research on forest plants driven by data and process-based models has also received much attention.
Special attention will be paid to the application of smart forestry based on big data and remote sensing, and this topic aims to do just that. The papers will be peer-reviewed and selected for publication in Frontiers in Plant Science. We kindly invite experts and scholars in related fields to contribute novel and original research to enrich our research community.
Potential topics may include, but are not limited to, the following:
• Ecosystem services monitoring
• Smart forestry construction
• Spatial-temporal analysis for forest
• Remote sensing image processing for forest
• Multi-source data fusion for forest
• Data assimilation for forest
• Intelligent decision-making tools for forest
• Tree height / DBH inversion
• Payment for ecosystem services
• Disturbance recognition in forest
• Forest biomass inversion
• Application of artificial intelligence and big data in forestry
Topic coordinator Donglin Di is employed by Baidu Co. and declares no competing interests with regards to the Research Topic Subject. All other Topic Editors declare no competing interests with regards to the Research Topic subject.
This Research Topic entitled “Big Data and Artificial Intelligence Technologies for Smart Forestry” welcomes papers dealing with forest monitoring and analysis and presents the scientific research achievements of emerging technologies such as big data, remote sensing and IoT applied in the field of forestry.
Forest monitoring based on SAR, Lidar, optical remote sensing, and IoT can provide support for large spatial scale forest management and decision-making. With the development of big data technologies, the speed of smart forestry construction and the level of forestry information management has significantly improved. On the one hand, high-performance architectures for big data can significantly improve the efficiency of large-scale forestry research; on the other hand, artificial intelligence models can effectively extract the vegetation features and ecological parameters of the forest from the remote sensing data. Therefore, the development, integration, and application of big data technology have become the focus of forestry research. Meanwhile, research on forest plants driven by data and process-based models has also received much attention.
Special attention will be paid to the application of smart forestry based on big data and remote sensing, and this topic aims to do just that. The papers will be peer-reviewed and selected for publication in Frontiers in Plant Science. We kindly invite experts and scholars in related fields to contribute novel and original research to enrich our research community.
Potential topics may include, but are not limited to, the following:
• Ecosystem services monitoring
• Smart forestry construction
• Spatial-temporal analysis for forest
• Remote sensing image processing for forest
• Multi-source data fusion for forest
• Data assimilation for forest
• Intelligent decision-making tools for forest
• Tree height / DBH inversion
• Payment for ecosystem services
• Disturbance recognition in forest
• Forest biomass inversion
• Application of artificial intelligence and big data in forestry
Topic coordinator Donglin Di is employed by Baidu Co. and declares no competing interests with regards to the Research Topic Subject. All other Topic Editors declare no competing interests with regards to the Research Topic subject.
