IEEE Geoscience and Remote Sensing Magazine - March 2020 - 157

teaching professor with the Department of Aerospace and
Geodesy of TUM. In 2016, he was a guest scientist at the
University of Massachusetts, Amherst. His research focuses
on image analysis and machine learning applied to the extraction of information from remote sensing observations.
In particular, he is interested in remote sensing data fusion
with a focus on synthetic aperture radar and optical data.
He is a cochair of the International Society for Photogrammetry and Remote Sensing Working Group I/3 (SAR and
Microwave Sensing). He frequently serves as a reviewer for
a number of renowned international journals and conferences and has received several best reviewer awards. He is a
Senior Member of the IEEE and an associate editor of IEEE
Geoscience and Remote Sensing Letters.
REFERENCES
[1] N. Yokoya et al., "Open data for global multimodal land use classification: Outcome of the 2017 IEEE GRSS Data Fusion Contest,"
IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 11, no.
5, pp. 1363-1377, May 2018. doi: 10.1109/JSTARS.2018.2799698.
[2] Y. Xu et al., "Advanced multi-sensor optical remote sensing for
urban land use and land cover classification: Outcome of the

2018 IEEE GRSS Data Fusion Contest," IEEE J. Sel. Topics Appl.
Earth Observ. Remote Sens., vol. 12, no. 6, pp. 1709-1724, June
2019. doi: 10.1109/JSTARS.2019.2911113.
[3] B. L. Saux, N. Yokoya, R. Hansch, M. Brown, and G. Hager, "2019
Data Fusion Contest [Technical Committees]," IEEE Geosci.
Remote Sens. Mag., vol. 7, no. 1, pp. 103-105, Mar. 2019. doi:
10.1109/MGRS.2019.2893783.
[4] M. Schmitt, L. H. Hughes, C. Qiu, and X. X. Zhu, "SEN12MS:
A curated dataset of georeferenced multi-spectral sentinel-1/2
imagery for deep learning and data fusion," ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., vol. IV-2/W7, pp. 153-
160, Sept. 2019. doi: 10.5194/isprs-annals-IV-2-W7-153-2019.
[5] D. Sulla-Menashe and M. Fr iedl, "MCD12Q1 MODIS/
Terra+Aqua Land Cover Type Yearly L3 Global 500m SIN Grid
V006," 2015. [Online]. Available: https://lpdaac.usgs.gov/
products/mcd12q1v006/
[6] T. R. Loveland and A. Belward, "The international geosphere
biosphere programme data and information system global land
cover data set (discover)," Acta Astronaut., vol. 41, nos. 4-10, pp.
681-689, 1997. doi: 10.1016/S0094-5765(98)00050-2.
GRS

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MARCH 2020

IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE

157

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IEEE Geoscience and Remote Sensing Magazine - March 2020

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