Special Issue "Data Fusion for Urban Applications"
Deadline for manuscript submissions: 31 October 2021.
Interests: Remote Sensing; Image Analysis; Interpretation; Data Fusion; Simulation
Interests: Remote Sensing; Data Fusion; Machine Learning; Geospatial Data Science
Special Issues and Collections in MDPI journals
Interests: remote sensing; image processing; data fusion; machine learning; disaster management; environmental monitoring
Special Issues and Collections in MDPI journals
Special Issue in Remote Sensing: Multisensor Data Fusion in Remote Sensing
Special Issue in Remote Sensing: Point Cloud Processing in Remote Sensing
Special Issue in Remote Sensing: Deep Learning and Feature Mining Using Hyperspectral Imagery
Special Issue in Remote Sensing: Advanced Machine Learning Techniques for High-Resolution Remote Sensing Data Analysis
Special Issue in Remote Sensing: Remote Sensing on Land Surface Albedo
Special Issue in Remote Sensing: Spectral Data Meets Machine Learning: From Datasets to Algorithms and Applications
Remote Sensing applications for urban areas are of major importance as the majority of human population is concentrated in these regions. Looking at reported literature, data from different sensors have been acquired, e.g., in order to characterize the nature of city areas, monitor urban development over time or detect changes after unexpected events. In this context, the unification of information from multimodal sensors in urban applications has always been very welcome, but so far hard to solve. On the one hand, finding appropriate strategies for combining the complementary information is difficult. On the other hand, the assignment of multi-modal information to entities of urban scenes is often not unambiguous. An increase of the spatial resolution of image data does not necessarily help but even tightens the conditions for useful solutions.
This Special Issue is devoted to strategies and methods for fusing multi-modal data in the context of urban remote sensing. As a general guideline, complementary sources should be combined in order to gain improved information about urban areas.
Submitting authors are encouraged to address one of the following topics in the context of remote sensing data (not exclusively):
- Enhancement of urban applications through exploitation of complementary information provided by data from multiple sensors, multiple sources and multi-temporal acquisitions;
- Integration of external prior knowledge into urban remote sensing;
- Fusion of information from remote sensing and non-typical Earth observation data sources (terrestrial data, data from social media, etc.) for improved understanding of urban problems;
- 2-D, 3-D and multi-dimensional data fusion for urban analysis;
- Multi-view fusion for exploiting different perspectives on urban elements;
- Data fusion for urban tasks conducted on data level, feature level, or decision level;
- Urban applications on different resolution levels (spatial, spectral, temporal).
Dr. Stefan Auer
PD Dr. Michael Schmitt
Dr. Naoto Yokoya
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.
- Data fusion
- Image fusion
- Multi-sensor fusion
- Multi-source fusion
- Urban applications
- City monitoring
- Change detection
- Multi-resolution data
- Multi-temporal data
- Multi-spectral data
- Accuracy assessment