IEEE/GRSS Magazine Special Issue on Data Fusion
in Remote Sensing
Data fusion is one of the fast moving areas of remote sensing image analysis. Fusing data coming from different sensors, at different resolutions, and of different quality is compulsory to meet the needs of society, which requires end-user products reflecting environmental problems that are naturally spatial, multiscale, evolving in time and observed at a discontinuous frequency.
This special issue will present a series of overview and tutorial-like papers about the latest advances in remote sensing data fusion. The focus of the contributions to the special issue will be on reviewing the current progress, on highlighting the latest trends that have been proposed in the literature to answer the needs of multisensory processing, and on pointing out the strategies to be thought to answer the information deluge which will come with the latest missions launched (or to be launched). Particular attention will be paid to the questions of multiresolution, multisensor, and multitemporal processing, while still covering the problems of missing data reconstruction and data assimilation with physical models. Consistently with the approach and style of the Magazine, the contributors to the special issue will pay strong attention to tuning the discussion level to a correct trade-off between ensuring scientific depth and disseminating to a wide public that would encompass remote sensing scientists, practitioners, and students, and include non-data-fusion specialists.
The topics of interest include (but are not limited to):
- Multisensor, multimodal, and multiresolution fusion
- Missing data reconstruction
- Multimodal interaction
- Data assimilation
- Application to urban studies, 3D reconstruction, vegetation modelling, climate change, etc.
- Valorisation of future missions providing complementary sensors
Dr. Gabriele Moser, University of Genoa, Italy, email@example.com
Dr. Devis Tuia, Ecole Polytechnique Fédérale de Lausanne, Switzerland, firstname.lastname@example.org
The Call for Papers can be found here: