Antonio Plaza (M’05-SM’07-F’15) is the Head of the Hyperspectral Computing Laboratory at the Department of Technology of Computers and Communications, University of Extremadura. His main research interests comprise hyperspectral data processing and parallel computing of remote sensing data. He has authored more than 500 publications, including more than 150 journal papers (more than 100 in IEEE journals), 20 book chapters, and over 250 peer-reviewed conference proceeding papers. He has guest edited 9 special issues on hyperspectral remote sensing for different journals. Dr. Plaza is a Fellow of IEEE “for contributions to hyperspectral data processing and parallel computing of Earth observation data.” He is a recipient of the recognition of Best Reviewers of the IEEE Geoscience and Remote Sensing Letters (in 2009) and a recipient of the recognition of Best Reviewers of the IEEE Transactions on Geoscience and Remote Sensing (in 2010), for which he served as Associate Editor in 2007-2012. He is also an Associate Editor for IEEE Access, and was a member of the Editorial Board of the IEEE Geoscience and Remote Sensing Newsletter (2011-2012) and the IEEE Geoscience and Remote Sensing Magazine (2013). He was also a member of the steering committee of the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS). He is a recipient of the Best Column Award of the IEEE Signal Processing Magazine in 2015, the 2013 Best Paper Award of the JSTARS journal, and the most highly cited paper (2005-2010) in the Journal of Parallel and Distributed Computing. He received best paper awards at the IEEE International Conference on Space Technology and the IEEE Symposium on Signal Processing and Information Technology. He served as the Director of Education Activities for the IEEE Geoscience and Remote Sensing Society (GRSS) in 2011-2012, and is currently serving as President of the Spanish Chapter of IEEE GRSS. He has reviewed more than 500 manuscripts for over 50 different journals. He is currently serving as the Editor-in-Chief of the IEEE Transactions on Geoscience and Remote Sensing journal.
Modern operational forest inventory often uses remotely sensed data that cover the whole inventory area to produce spatially explicit estimates of forest properties through statistical models. The data obtained by airborne light detection and ranging (…Read more