Advances in Methods and Techniques for Satellite Image Processing and Analysis

Dear Colleagues,

As large-scale datasets are becoming more accessible and because high-performance computing devices and effective training methods are available, machine learning-based techniques have been introduced in a variety of applications, such as in the analysis of remote sensing images. Advanced machine learning algorithms have emerged as a powerful tool for analyzing satellite imagery in recent years. These models can be used for various tasks, such as classification, forecasting, regression, and clustering. Unseen challenges arise when applying computer vision-developed machine learning techniques to large-scale, multivariate, noisy, irregularly collected remote sensing data.

This Special Issue aims to publish studies covering different uses of machine learning models, as well as the utilization and fusion of various sensors and platforms in remote sensing.

Review and research papers on cutting-edge CNNs and vision transformer-based methods for machine learning, architectures, and structures for applications in remote sensing will be published in this Special Issue, with an emphasis on tasks that address the problems in this field.

Potential topics of interest include, but are not limited to, the following:

1. Shallow and deep learning remote sensing image interpretation and analysis (image classification, pan-sharpening, image enhancement, object detection, semantic segmentation, and change detection).
2. Graphic, adversarial, unsupervised, semi-supervised, self-supervised, active, and transfer learning for dealing with limited and/or low-quality data.
3. Knowledge acquisition of deep learning models for remote sensing imagery.
4. Novel benchmark datasets for remote sensing image analysis.
5. Applications of Vision Transformers (ViTs) in remote sensing.

Dr. Ali Jamali
Guest Editor

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.

• deep learning
• computer vision
• machine learning
• image processing
• remote sensing
• image analysis