AI-Driven Hyperspectral Image Classification and Processing in Remote Sensing

Dear Colleagues,

Hyperspectral imaging (HSI) provides dense, contiguous spectra for every pixel, enabling material-level discrimination beyond what multispectral sensors can deliver. Over the past five years, advances in AI—especially spectral–spatial representation learning, self-/weakly supervised pretraining, and emerging remote-sensing foundation models—have reshaped HSI classification and processing. These models promise stronger generalization across scenes and sensors, data-efficient learning under sparse or noisy labels, and end-to-end pipelines that couple physics with learning.

This Special Issue focuses on novel artificial intelligence methods and systems for hyperspectral image classification and processing, featuring the following topics: (1) learning transferable spectral–spatial representations; (2) integrating hyperspectral imagery with complementary sensing modalities; (3) achieving robust performance across scenes, sensors, and seasons through domain adaptation; (4) demonstrating scientific value in key application domains (marine/coastal, forestry/biodiversity, urban land use/cover). We particularly welcome submissions that provide open-source code, datasets, models, and inference pipelines to enable fully reproducible research.

Suggested themes include the following: (1) cross-modal fusion; (2) spectral–spatial feature learning; (3) domain adaptation and cross-scene generalization; (4) remote sensing foundation model; (5) AI-driven hyperspectral image classification; (6) hyperspectral image denoising; (7) self-/weakly supervised learning; (8) marine and coastal monitoring; (9) forestry and biodiversity assessment; (10) urban land use and land-cover monitoring

Prof. Dr. Le Sun
Prof. Dr. Jie Feng
Dr. Yang Xu
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.