The Remote Sensing Best Paper Award for papers published in 2023 has been presented to the authors of the following articles, selected by a committee chaired by the journal’s Editor-in-Chief, Dr. Prasad S. Thenkabail. Following a thorough review process performed by the Award Evaluation Committee, five winners were chosen.
First prize:
“Seasonal Vegetation Trends for Europe over 30 Years from a Novel Normalised Difference Vegetation Index (NDVI) Time-Series—The TIMELINE NDVI Product”
by Christina Eisfelder, Sarah Asam, Andreas Hirner, Philipp Reiners, Stefanie Holzwarth, Martin Bachmann, Ursula Gessner, Andreas Dietz, Juliane Huth, Felix Bachofer et al.
Remote Sens. 2023, 15(14), 3616; https://doi.org/10.3390/rs15143616
Available online: https://www.mdpi.com/2072-4292/15/14/3616
Second prize:
“Global Water Quality of Inland Waters with Harmonized Landsat-8 and Sentinel-2 Using Cloud-Computed Machine Learning”
by Leonardo F. Arias-Rodriguez, Ulaş Firat Tüzün, Zheng Duan, Jingshui Huang, Ye Tuo and Markus Disse
Remote Sens. 2023, 15(5), 1390; https://doi.org/10.3390/rs15051390
Available online: https://www.mdpi.com/2072-4292/15/5/1390
“Continuously Updated Digital Elevation Models (CUDEMs) to Support Coastal Inundation Modeling”
by Christopher J. Amante, Matthew Love, Kelly Carignan, Michael G. Sutherland, Michael MacFerrin and Elliot Lim
Remote Sens. 2023, 15(6), 1702; https://doi.org/10.3390/rs15061702
Available online: https://www.mdpi.com/2072-4292/15/6/1702
Third prize:
“G-Rep: Gaussian Representation for Arbitrary-Oriented Object Detection”
by Liping Hou, Ke Lu, Xue Yang, Yuqiu Li and Jian Xue
Remote Sens. 2023, 15(3), 757; https://doi.org/10.3390/rs15030757
Available online: https://www.mdpi.com/2072-4292/15/3/757
“Surface ALbedo VALidation (SALVAL) Platform: Towards CEOS LPV Validation Stage 4—Application to Three Global Albedo Climate Data Records”
by Jorge Sánchez-Zapero, Enrique Martínez-Sánchez, Fernando Camacho, Zhuosen Wang, Dominique Carrer, Crystal Schaaf, Francisco Javier García-Haro, Jaime Nickeson and Michael Cosh
Remote Sens. 2023, 15(4), 1081; https://doi.org/10.3390/rs15041081
Available online: https://www.mdpi.com/2072-4292/15/4/1081
Please join us in congratulating the winners of the Remote Sensing 2023 Best Paper Award. We would also like to take this opportunity to thank our authors for their continued support of Remote Sensing (ISSN: 2072-4292).
