Dear Colleagues,

Remote sensing is an integral part of many scientific applications, and demands new thoughts and techniques to be fully exploited. Deploying knowledge models in remote sensing data analysis has been at the center of attention for more than a decade. Various types of knowledge-driven methods have been applied in remote sensing image understanding, including object detection, segmentation, and classification. However, there is limited discussion on machine-readable knowledge and its incorporation in the remote sensing data analysis workflow. In the era of big data and machine learning, it is important to include explicit knowledge in data-intensive studies, which has huge potential to bring new thoughts and approaches in the field of remote sensing. Applying semantic techniques such as vocabularies, taxonomies, and ontologies leads to achieving knowledge that allows the experts of a scientific domain to capture and formalize the concepts and relationships of that domain. As such, in recent years the topics of formal knowledge representation and knowledge-infused machine learning have been increasingly discussed among the remote sensing research community. This Special Issue calls for research articles presenting innovative methods or applications that infuse knowledge in remote sensing data processing. Review and perspective articles that offer insights on this field of research are also welcome.

Dr. Xiaogang Ma
Dr. Ziheng Sun
Dr. Sanaz Salati
Dr. Chao Fan
Dr. Meifang Li
Dr. Zhe Wang
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 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.

• knowledge model
• remote sensing
• hybrid modeling
• machine learning
• ontology
• knowledge graph