Editorial Board Members’ Collection Series: Advances in Remote Sensing Image Analysis and Data Fusion
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 (15 July 2023) | Viewed by 728
Special Issue Editors
Interests: geographic information systems (GIS); remote sensing; spatial modeling; and data mining for urban and environmental analysis and planning; mapping urban land cover (green space, impervious surfaces, etc.); monitoring forest health using fine resolution satellite imagery
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; image processing; image analysis; computer vision; mathematical morphology; multi-scale analysis; algorithms; parallel and distributed computing; pattern recognition; machine learning
Special Issue Information
Dear Colleagues,
Remote sensing images have recorded vast quantities of information on the earth’s surface and its changes over time for decades. Maps and other data produced through remote sensing image analysis have also been used for a broad range of applications, e.g., for urban planning, national security, agricultural management, forestry, environmental conservation, climate monitoring, hydrological modeling, etc. New remote-sensing-image-processing methods are constantly being developed and applied to more efficiently extract information from the growing quantity (and variety) of data available from satellite, airborne, and terrestrial sensors. The increasing availability of geospatial data from other sources, e.g., government/non-government agencies, crowdsourcing, or other big data, is also leading to innovations in data integration/data fusion for remote sensing analysis. This issue is looking for papers that demonstrate breakthroughs in remote sensing image analysis, focusing on the advances in remote sensing using computer vision, deep learning, data fusion, and artificial intelligence techniques.
We welcome the most recent advancements in remote sensing related to, but not limited to:
- Deep learning architectures;
- Machine learning approaches;
- Computer vision;
- Classification/change detection/regression methods for information extraction;
- Unsupervised feature learning;
- Domain adaptation and transfer learning;
- Anomaly/novelty detection;
- New datasets and tasks for remote sensing;
- Integration of remote sensing and other geospatial data;
- New remote sensing applications;
- Synthetic remote sensing data generation;
- Real-time remote sensing;
- Deep-learning-based image registration.
Dr. Brian Alan Johnson
Dr. Michael H.F. Wilkinson
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.
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