Theory and Application of Machine Learning in Remote Sensing

Dear Colleagues,

Rapid advances in machine learning have spurred the application of associated algorithms and techniques to problems in a variety of fields. Principled and theoretical insights into these new methods have followed but there remains a need for their application within remote sensing. For example, high-dimensional methods, signal processing on graphs and tensors, and theoretical understanding of deep learning algorithms are all recent advances in mathematics and statistics that could improve our understanding of long-standing remote sensing problems.

This Special Issue will cover the latest advances in the application of novel methods and mathematics to applications such as classification, segmentation and clustering, anomaly detection, and data fusion. As recognized experts in the field, we invite you to contribute articles to this Special Issue covering the theory and application of machine learning algorithms in remote sensing.

Topics of interest include but are not limited to the following:

Deep learning

Manifold learning

Spectral graph theory

High-dimensional methods

Kernel methods

Classification

Segmentation

Clustering

Anomaly detection

Data fusion

Sensitivity analysis

Harmonic analysis

Numerical methods

Signal processing on graphs and tensors

Hyperspectral imaging

Unsupervised learning

Semi-supervised learning

Asst. Prof. James Murphy
Dr. Colin Olson
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.