Classification and Feature Extraction from Remote Sensing Imagery and Point Cloud Data

Dear Colleagues,

Classification is an essential part of information deconstruction in remote sensing, a core process of feature extraction. Technical feature designs need to be robust and have fidelity; classifiers are devoted to fitting a sample as close as possible through its features.  ​In recent years, further classification optimization is driven by the data needed for artificial intelligence, such as deep learning. The most recent emergence of platform type, spectrum quantity and resolution, advanced sensors, etc., have been applied to yield a vast amount of remote sensing images and point cloud data. New data usher in new challenges of classification and feature extraction. Mining new physical features and integrating multi-source data features are needed to improve classification accuracy. Moreover, the development and fusion of classifiers can further promote more refined remote sensing applications, such as the 3D reconstruction of large scenes, long-time series change detection, etc.

This Special Issue aims to provide more advanced feature extraction methods and classification techniques for multi-source and multi-modal remote sensing data.  Furthermore, with these new data and technologies, the application of remote sensing data can also be improved and expanded. Authors are invited to contribute to the most research results in cutting-edge technology, novel applications, and evaluation methods on remote sensing classification and feature extraction, including but not limited to the following topics:

• Breakthrough idea for image classification and feature extraction;
• Cutting-edge technologies for image classification and feature extraction;
• Artificial intelligence theory, method and algorithm for image classification and feature extraction;
• Classified image and point cloud data for various applications;
• Classification quality evaluation.

Prof. Dr. Guoqing Zhou
Dr. Yuefeng Wang
Prof. Dr. Oktay Baysal
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.