Advances in Hyperspectral Remote Sensing Image Processing: 2nd Edition

Dear Colleagues,

Hyperspectral remote sensing images have become a well-established data source for precision agriculture, resource investigation, environmental monitoring, national defense, and other important fields for their fine spectral information. Meanwhile, the renewal of the space industry in various countries has also established a relatively complete remote sensing data acquisition system, which provides data support and new power for hyperspectral remote sensing earth observation. Under the rapid development of artificial intelligence, big data, 5G, and other advanced technologies, massive hyperspectral data processing and reasonable application have become a hot research topic in remote sensing.

This Special Issue aims to study hyperspectral remote sensing image processing methods and applications. Topics may range from comparative study, overview, and different types of hyperspectral remote sensing image processing methods to more comprehensive practical applications. Therefore, the method design, performance evaluation, application implementation, and other issues based on hyperspectral remote sensing image processing are welcome. Articles may address, but are not limited to, the following topics:

• Comparative study or review of hyperspectral image processing methods;
• Primary processing methods of hyperspectral remote sensing images (e.g., rectification, denoising, restoration, enhancement);
• Intermediate processing methods of hyperspectral remote sensing images (e.g., feature selection and extraction, super-resolution, clustering, image fusion, unmixing);
• Advanced processing methods of hyperspectral remote sensing images (e.g., classification, target detection, anomaly detection, segmentation, scene recognition, image interpretation);
• Application of hyperspectral remote sensing image processing results in real scenarios (e.g., disaster monitoring, precision agriculture, resource investigation);
• Lightweight networks and efficient targeted systems designed for hyperspectral remote sensing image processing;
• Opportunities and challenges in hyperspectral remote sensing image processing.

Prof. Dr. Xudong Kang
Dr. Mingmin Chi
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 250 words) can be sent to the Editorial Office for assessment.

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.