Special Issue "Classification and Feature Extraction Based on Remote Sensing Imagery"
Deadline for manuscript submissions: closed (31 March 2021).
Interests: digital image processing; computer vision; feature extraction; pattern recognition; object classification; machine learning; cognitive robotics; multi-modal sensing
Classification and feature extraction for remote sensing image analysis is applicable to a wide range of different environments and ecological systems, at a range of spatial and temporal scales. Emerging methodological approaches include big data analytics, deep learning, machine learning, and object-based image analysis (OBIA), many of which are now commonplace in a range of different contexts, from geomorphological time-lapse analysis to the broad-scale characterization of terrestrial and aquatic ecosystems. These approaches are allowing environmental, earth, and marine scientists to unlock the potential capacity for research into vitally important areas, such as climate change, susceptibility to geohazards, biodiversity loss, and habitat fragmentation.
For remote sensing image analysis, the process of feature extraction and classification is applicable at the scale of the landscape (e.g., geomorphometry) and also in terms of ground validation where this is achieved by optical means (e.g., photoquadrats). Boundaries between these spatial scales of observation and analysis are increasingly becoming blurred with developments in sensors and computing power, allowing for mapping of larger contexts at higher resolutions. Independent of spatial scale, feature extraction from landscape-level features and ground validation imagery are united by their potential capacity for automation in the analytical process.
In spite of recent technological advances, a great challenge remains in the development of new computational procedures for gaining a more accurate representation of complex environments. Recent breakthroughs in computer vision methods and deep learning models for image fusion, image classification, and object detection assist with obtaining a much more accurate model of environmental features than could be achieved previously; however, further investigation is required on the development of new algorithms for automatic feature extraction, monitoring, and integration of high-quality multi-modal data.
This Special Issue focuses on feature extraction and classification using remote sensing data and novel machine learning techniques. It aims to explore the potential of new ideas and technologies from the field of machine learning and pattern recognition in remote sensing applications in a variety of different environments and spatial scales (from landscape geomorphometry to ground validation) and to further investigate the overlap between remote sensing and computer vision/image analysis.
This Special Issue will include, but not be limited to, the following topics:
- Feature extraction approaches related to the characterization of terrestrial and marine ecosystems;
- Novel technologies or procedures for dynamic acquisition and processing of 3D point clouds, from a variety of sensors (e.g., LiDAR, laser line scanner, multibeam echosounder, photogrammetry);
- Pattern recognition/machine learning/deep learning for remote sensing;
- Innovative approaches to the classification of remote sensing data, from the scale of landscapes to ground validation data;
- Novel approaches for the quantification of biodiversity from remote sensing data;
- Automated approaches to analysis of ecological information from photographs.
Contributions with an emphasis on open-source code and data sharing are particularly welcome.
Dr. Bryan Gardiner
Dr. Chris McGonigle
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 papers will be 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 2400 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.
- feature extraction
- object detection
- 3D point clouds
- machine learning
- remote sensing
- deep learning
- laser line scanner (LLS)
- benthic mapping