SAR Aware Methods towards Sustainable Development Goals

Dear Colleagues,

Synthetic aperture radar (SAR) is a versatile tool in the domain of remote sensing for earth observation and monitoring. It can operate day and night and can penetrate cloud cover, making it indispensable for change monitoring. With different spatio-temporal and polarimetric configurations, advanced techniques like PolSAR, InSAR, PolinSAR, TomoSAR, and PolTimeSAR can be utilized effectively for a wide range of applications from agriculture and urban area monitoring to forestry, cryosphere, ocean and land studies, and natural hazard monitoring.

The processing and analysis of SAR data before it can be applied for downstream remote sensing applications is often challenging. The viability of SAR data for an application can depend upon several factors: acquisition mode, resolution, frequency band, speckle and thermal noise patterns, look direction, incidence angle, target orientation with respect to radar line of sight, spatio-temporal baselines, additional understanding of the advanced techniques with SAR, assumptions on backscatter models for downstream applications and environmental conditions like dry or wet conditions, wind speed and direction, etc., depending on the domain of interest of the study.

The intent of this Special Issue is to encourage research that utilizes the SAR theory and techniques in providing robust solutions to global challenges towards the UN 2030 sustainable development goals (SDGs). To achieve efficient utilization of information, it is important to enhance SAR-aware methods. The complementary nature of the microwave region of the electromagnetic spectrum should clearly come to the fore in multi-modal approaches. This requires emphasis on SAR image processing and analysis.

We strongly encourage the submission of methods that are tailored specifically for SAR images. These methods should also underscore the significance of SAR's unique attributes for various applications. There is no limitation on the application area. Submissions that demonstrate the prowess of SAR in relatively new areas of application, innovative experiments using SAR and new SAR technologies are also welcome.

Below is a non-exhaustive list of themes for submission:

• SAR despeckling/denoising.
• SAR-aware/physics-aware machine learning/deep learning for SAR applications.
• Statistical methods for SAR applications.
• SAR/PolSAR/InSAR/PolinSAR/TomoSAR/PoltimeSAR techniques and applications.
• Polarimetric SAR: full, dual, twin, compact.
• Multimodal approaches to environmental applications using SAR.
• SAR image classification.
• Uncertainty quantification for SAR Applications.
• Change detection using SAR.
• Electromagnetic modeling of SAR response from environments.
• GB-SAR applications.

We look forward to your excellent work for submission in this Special Issue.

Dr. Debanshu Ratha
Dr. Unmesh Khati
Dr. Lanqing Huang
Guest Editors

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• advanced SAR techniques
• SAR aware methods
• multimodal approach (including SAR)
• information efficient retrieval (from SAR)
• active microwave remote sensing
• sustainable development goals