About this Research Topic
In the context of increasing attention to forest resource management and ecological protection, remote sensing technology, as an efficient and widely used monitoring tool, has made significant advancements in the field of forest monitoring and analysis. Commonly used remote sensing images include hyperspectral images, multispectral images, infrared images, and synthetic aperture radar (SAR) images, etc. Using remote sensing images to classify forest types, such as coniferous forests, broadleaf forests, and mixed forests, is crucial for forest management and ecological monitoring. Remote sensing images provide a broad perspective for monitoring the occurrence and spread of forest fires. Infrared and thermal imaging, in particular, are highly effective in detecting fire hotspots and heat variations, enabling timely fire warning and emergency response. Regular acquisition of remote sensing images allows for tracking changes in forest cover, such as forest degradation, logging activities, and natural disasters, which aids in formulating forest protection and restoration measures. In addition, remote sensing image fusion techniques are also indispensable in forest monitoring. Our Research Topic provides an important platform for exploring the application and development of remote sensing technology in forest monitoring.
This Research Topic seeks to gather cutting-edge research and advancements in remote sensing techniques specifically tailored for forest monitoring and analysis. We invite contributions that explore innovative technologies, methodologies, and applications aimed at enhancing our understanding and management of forest environments. Topics of interest include, but are not limited to:
• Hyperspectral image classification
• Hyperspectral target Detection
• Hyperspectral anomaly detection
• Infrared target detection
• Change detection in remote sensing images (optical, hyperspectral , SAR) for tracking forest cover changes
• Fusion of hyperspectral, multispectral, and panchromatic images
• Infrared and visible image fusion for forest fire monitoring
This Research Topic seeks to gather cutting-edge research and advancements in remote sensing techniques specifically tailored for forest monitoring and analysis. We invite contributions that explore innovative technologies, methodologies, and applications aimed at enhancing our understanding and management of forest environments. Topics of interest include, but are not limited to:
• Hyperspectral image classification
• Hyperspectral target Detection
• Hyperspectral anomaly detection
• Infrared target detection
• Change detection in remote sensing images (optical, hyperspectral , SAR) for tracking forest cover changes
• Fusion of hyperspectral, multispectral, and panchromatic images
• Infrared and visible image fusion for forest fire monitoring
Keywords: change detection, image classification, image fusion, target detection, hyperspectral, SAR
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
