SAR and Multisource Remote Sensing: Challenges and Innovations

Dear Colleagues,

In the rapid development of remote sensing technology, synthetic aperture radar (SAR) images have occupied an important position in the field of earth observation due to their all-weather and all-day imaging capabilities. Hyperspectral imaging (HSI) is a technique that reveals the properties of objects by capturing their reflectance or radiance across multiple spectral bands, typically ranging from dozens to hundreds. It finds extensive applications in fields such as land cover classification, environmental monitoring, and mineral resource exploration. The Special Issue will focus on new methods for SAR and HSI image processing, including but not limited to, noise reduction, feature extraction, target recognition, and change detection. Additionally, the fusion and interpretation of multisource remote sensing data (SAR, HSI, or others) have become important significance to enhance the accuracy and reliability of remote sensing information extraction. This Special Issue aims to gather the latest research findings, showcasing cutting-edge advancements and innovative applications in the interpretation of SAR, HSI and multisource remote sensing images.

Articles may address, but are not limited to, the following topics:

1. SAR denoising and feature extraction;
2. SAR image classification and detection based on deep learning;
3. Hyperspectral image and video processing;
4. Cooperative interpretation of SAR, HSI, LiDAR, and other data;
5. Remote sensing object tracking;
6. Change detection of multisource remote sensing data.

SAR remote sensing data processing is primarily used to extract surface features from radar signals and can penetrate clouds and the atmosphere to obtain structural information about the earth's surface. HSI image processing utilizes hyperspectral sensors to capture the spectral characteristics of objects, providing continuous spectral data from visible light to near-infrared. Multisource remote sensing image processing combines data from different sensors (such as SAR, HSI, and optical remote sensing) to obtain more comprehensive and accurate information. This fusion approach compensates for the limitations of individual sensors and enhances the precision and reliability of information extraction. The aforementioned research areas all fall within the field of remote sensing data processing and have been widely applied in environmental monitoring, agriculture, urban planning, disaster management, and other fields. The widespread application and technological innovation of SAR, HSI, and multisource remote sensing image processing technologies in the remote sensing field have made them key topics of interest for the journal remote sensing. These technologies not only drive the advancement of remote sensing technology, but also play a significant role in various practical applications.

Suggested themes:

(1) SAR denoising and feature extraction;

(2) SAR image classification and detection based on deep learning;

(3) Hyperspectral image and video processing;

(4) Cooperative interpretation of SAR, HSI, LiDAR, and other data;

(5) Remote sensing object tracking;

(6) Change detection of multisource remote sensing data.

Article types for submissions:

(1) Research articles;

(2) Review articles;

(3) Technical reports;

(4) Case studies.

Dr. Peng Wang
Dr. Kang Ni
Dr. Zhizhong Zheng
Prof. Dr. Henry Leung
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• SAR image processing
• hyperspectral image processing
• hyperspectral video processing
• multisource remote sensing deep learning
• deep learning
• feature learning