Advanced Artificial Intelligence Algorithm for the Analysis of Remote Sensing Images (Third Edition)

Dear Colleagues,

In the field of Earth observation, the massive amount of remote sensing data obtained by a large number of satellites in orbit or manned/unmanned aerial vehicles (UAVs) poses opportunities and challenges for the analysis of remote sensing images. Artificial intelligence is an emerging technology that is very suitable for big data applications. Therefore, how to interpret remote sensing images automatically, efficiently, and accurately is a hot and difficult topic in the research into and application of remote sensing technology. In recent years, artificial intelligence, especially deep learning techniques, has had a significant impact on the field of remote sensing, providing promising tools to overcome many challenging issues in the analysis of remote sensing images in terms of accuracy and reliability.

This is the third volume of the Special Issue of Remote Sensing on “Advanced Artificial Intelligence Algorithm for the Analysis of Remote Sensing Images”. In this Special Issue, we intend to compile a series of papers that merge the analysis and use of remote sensing images with AI techniques. We expect that new research will address practical problems in remote sensing image applications with the help of advanced AI methods.

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

• Advanced AI architectures for image classification;
• Advanced AI-based target detection/recognition/tracking;
• Change detection/semantic segmentation for remote sensing;
• Multi-senor data fusion/multi-modal data analysis;
• Image super-resolution/restoration for remote sensing;
• Unsupervised/weakly supervised learning for image processing;
• Advanced AI techniques for remote sensing applications;
• Clustering (including classic and more advanced tools, such as subspace clustering, clustering ensemble, etc.);
• Spectral unmixing, adopting either linear or non-linear models, using Bayesian or non-Bayesian approaches for parameter estimation;
• Dimensionality reduction;
• Data transformations.

Prof. Dr. Gangyao Kuang
Dr. Siqian Zhang
Dr. Xin Su
Dr. Olga Sykioti
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.