Natural disasters and critical environmental issues pose significant threats to human safety, infrastructure, and ecological balance. In response to these challenges, there is an increasing need for advanced monitoring technologies that can provide accurate and timely information. With its ability to penetrate adverse weather conditions and provide high-resolution data, synthetic aperture radar (SAR) imaging is pivotal in disaster management and environmental studies on a global scale. Leveraging an unprecedented volume of data obtained from SAR satellite imaging systems, the distinctive capabilities of multidimensional SAR processing emerge as a key tool, providing valuable information crucial for the detection and monitoring of natural disasters and critical environmental issues.
This Research Topic aims at outlining innovative methods and recent advances in multidimensional SAR Imaging for the effective monitoring of natural disasters and critical environmental issues. It also seeks to gather cutting-edge research contributions that explore application of SAR processing techniques, address challenges in disaster response, and contribute to a deeper understanding of environmental changes. Within this framework, the goal includes highlighting the transformative effects of incorporating deep learning methods and the computational power of high performance computing (HPC) platforms in multidimensional SAR imaging. Therefore, the outcomes will contribute significantly to the development of scalable, efficient, and innovative solutions for handling and interpreting SAR data.
By fostering collaboration and synergies among researchers, this Research Topic aims to propel the field forward, ultimately enhancing our ability to mitigate the impact of natural disasters and address urgent environmental concerns through the utilization of SAR technology.
We welcome researchers and experts in the field to contribute this Research Topic with innovative research and advancements in the application of SAR imaging technology. The Research Topic will cover, but is not limited to, the following topics:
• Advanced techniques for processing multidimensional SAR images, including multi-temporal, multi-frequency, multi-modal, multi-polarization, multi-sensor, multi-resolution SAR observations.
• Advancing SAR imaging capabilities through the deployment of emerging constellations and fleet of satellites
• Integration of deep learning/machine learning methods with SAR data processing for improved feature extraction, classification, and interpretation.
• HPC-enabled SAR processing, enabling faster and more accurate analyses of multidimensional SAR data.
• Detecting and monitoring natural disasters using SAR data: such as earthquakes, wildfires, flooding, landslides, and environmental issues.
• Monitoring glaciers, forests, wetlands, and other natural resources.
• Environmental impact assessment: Studies assessing the environmental impact of natural disasters, including analyses of ecosystems and urban areas.
• Resource management: Research on utilizing SAR data for optimizing resource management during and after disasters, encompassing damage assessment and reconstruction planning.
Keywords:
synthetic aperture radar, statistical image processing, environmental monitoring, remote sensing, earth observation
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.
Natural disasters and critical environmental issues pose significant threats to human safety, infrastructure, and ecological balance. In response to these challenges, there is an increasing need for advanced monitoring technologies that can provide accurate and timely information. With its ability to penetrate adverse weather conditions and provide high-resolution data, synthetic aperture radar (SAR) imaging is pivotal in disaster management and environmental studies on a global scale. Leveraging an unprecedented volume of data obtained from SAR satellite imaging systems, the distinctive capabilities of multidimensional SAR processing emerge as a key tool, providing valuable information crucial for the detection and monitoring of natural disasters and critical environmental issues.
This Research Topic aims at outlining innovative methods and recent advances in multidimensional SAR Imaging for the effective monitoring of natural disasters and critical environmental issues. It also seeks to gather cutting-edge research contributions that explore application of SAR processing techniques, address challenges in disaster response, and contribute to a deeper understanding of environmental changes. Within this framework, the goal includes highlighting the transformative effects of incorporating deep learning methods and the computational power of high performance computing (HPC) platforms in multidimensional SAR imaging. Therefore, the outcomes will contribute significantly to the development of scalable, efficient, and innovative solutions for handling and interpreting SAR data.
By fostering collaboration and synergies among researchers, this Research Topic aims to propel the field forward, ultimately enhancing our ability to mitigate the impact of natural disasters and address urgent environmental concerns through the utilization of SAR technology.
We welcome researchers and experts in the field to contribute this Research Topic with innovative research and advancements in the application of SAR imaging technology. The Research Topic will cover, but is not limited to, the following topics:
• Advanced techniques for processing multidimensional SAR images, including multi-temporal, multi-frequency, multi-modal, multi-polarization, multi-sensor, multi-resolution SAR observations.
• Advancing SAR imaging capabilities through the deployment of emerging constellations and fleet of satellites
• Integration of deep learning/machine learning methods with SAR data processing for improved feature extraction, classification, and interpretation.
• HPC-enabled SAR processing, enabling faster and more accurate analyses of multidimensional SAR data.
• Detecting and monitoring natural disasters using SAR data: such as earthquakes, wildfires, flooding, landslides, and environmental issues.
• Monitoring glaciers, forests, wetlands, and other natural resources.
• Environmental impact assessment: Studies assessing the environmental impact of natural disasters, including analyses of ecosystems and urban areas.
• Resource management: Research on utilizing SAR data for optimizing resource management during and after disasters, encompassing damage assessment and reconstruction planning.
Keywords:
synthetic aperture radar, statistical image processing, environmental monitoring, remote sensing, earth observation
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.