Neural Networks and Deep Learning for Satellite Image Processing

Dear Colleagues,

Over the past decade, the rapid evolution of sophisticated AI technologies has significantly enhanced the precision and speed of analysing satellite remote sensing data, from basic classification tasks to more complex regression challenges. However, despite these advancements, contemporary remote sensing confronts persistent issues akin to those from a decade ago. Challenges persist in areas like the uncertainty surrounding multi-scale land cover mapping, integrating radiative transfer model simulations with deep learning algorithms, and establishing effective learning frameworks tailored to remote sensing tasks.

This Special Issue seeks original articles on creating innovative deep learning models for detecting various visual patterns aiding Earth monitoring. We also welcome research submissions on remote sensing change detection, forest canopy attribute retrieval, and ecosystem mapping with deep learning models. Additionally, we encourage in-depth review articles evaluating the effectiveness of cutting-edge deep learning models in remote sensing imagery.

Submitted works may explore various subjects, including the following:

1. Robust retrieval of forest canopy structure or parameters based on deep learning;
2. Deep learning-based land cover and land use change detection;
3. Transformer-based classification and object detection;
4. Reinforcement learning with remote sensing observation;
5. Matric learning in feature space;
6. Model generalisation;
7. Transfer learning for large scale mapping;
8. Transferability assessment.

Prof. Dr. Jinsong Chen
Dr. Shanxin Guo
Prof. Dr. Yanfei Zhong
Guest Editors

Dr. Yue Xu
Guest Editor Assistant

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.