Deep Learning and Foundation Models: Advancing Remote Sensing Applications

Dear Colleagues,

Remote sensing has become an active area of research over the past few years. Today, unlike in the past, large amounts of data are accessible, and many applications are now derived from crossovers of imaging, sensing, machine vision and artificial intelligence.

In particular, the advent of deep learning has marked the onset of a new era of research in machine vision in general and remote sensing in particular, owing mainly to unprecedented performance in various applications. Nevertheless, there is always room for improvement.

To this end, this Special Issue builds upon the success of its first edition and will carry on for a second volume. In particular, it undertakes a wide range of applications that make use of deep learning methodologies applied to remote sensing data. For instance, potential submissions may cover (but are not limited to) the following deep learning-driven topics:

• Image classification, segmentation, fusion, super-resolution and inpainting;
• Adversarial techniques;
• Area reconstruction or removal;
• UAV image analysis;
• Changes in detection;
• Remote Sensing of aquatic environments;
• Remote sensing in forestry;
• Object detection/tracking/re-identification;
• Assessing natural hazards;
• Image captioning;
• Visual question answering;
• Image retrieval (including text to image retrieval and vice versa);
• Land use/cover;
• Urban development assessment;
• Soil analysis (e.g., mineral estimation);
• Precision farming;
• Remote sensing datasets;
• Domain adaptation;
• Internet of Things, big data;
• Remote sensing data protection/security;
• Forecasting (e.g., weather data);

Dr. Mohamed Lamine Mekhalfi
Prof. Dr. Yakoub Bazi
Dr. Edoardo Pasolli
Dr. Mawloud Guermoui
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.