Multi-Modality Data Classification: Algorithms and Applications
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 44988
Special Issue Editors
Interests: high-performance geo-computation; big earth data; data science
Special Issues, Collections and Topics in MDPI journals
Interests: signal and image processing; machine learning for remote sensing; multimodal data integration; hyperspectral data analysis; remote sensing for precision agriculture
Special Issues, Collections and Topics in MDPI journals
Interests: signal and image processing; pattern recognition; texture modeling; hyperspectral image classification; SAR image processing; high resolution remote sensing; images analysis
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; image analysis; pattern recognition; signal processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Due to the rapid development of sensor technology, multi-modality remotely sensed datasets (e.g., optical, SAR, and LiDAR) that may differ in imaging mechanism, spatial resolution, and coverage can be achieved. Classification is one of the most important techniques to utilize these multi-modality datasets for land cover/land use and dynamic changes in various applications, e.g., precision agriculture, urban planning, and disaster responses.
The utilization of multi-modality datasets has been an active topic in recent years because they can provide complementary information of the same scene, thus boosting the classification performance. The availability of big remote sensing multi-modality data platforms, e.g, ESA’s Copernicus program, Landsat series, and China GaoFen series, is likely to reinforce this trend.
However, there still remains unsolved problems with multi-modality datasets, such as spectral/spatial variations, gaps in imaging mechanisms, and sensor-specific features of applications, which should be addressed further. This Special Issue, “Multi-Modality Data Classification: Algorithms and Applications”, will collect original manuscripts that address the above-mentioned challenging of multi-modality data classification, not only in the algorithm domain but also in the application domain. We kindly invite you to contribute to the following (but not exhaustive) topics that fit this Special Issue: multi-modality feature extraction, multi-modality data fusion, deep learning and transfer learning using multi-modality datasets, and classification and change detection of multi-modality datasets for any thematic application (related to urban, agricultural, ecological, and disaster ones) from local to global scales.
Dr. Junshi Xia
Dr. Nicola Falco
Dr. Lionel Bombrun
Prof. Jon Atli Benediktsson
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.
Keywords
- classification
- multi-modality data
- applications
- data fusion
- machine learning
- applications
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue polices can be found here.