Fabio Pacifici of Digital Globe Inc.

During the last two decades, significant progress has been made in developing and launching satellites with instruments, in both the optical/infrared and microwave regions of the spectra, well suited for Earth observation with an increasingly finer spatial, spectral, and temporal resolution. Sensors with sub-metric resolution allow the detection of small-scale objects, such as elements of residential housing, commercial buildings, transportation systems, and utilities. Spectral capabilities provide additional discriminative features for classes that are spatially similar, due to their higher spectral resolution. The temporal component, integrated with the spectral and spatial dimensions, provides essential information, for example, on vegetation dynamics. However, the current offering of imagery does not match the customer real need. Users in all domains require information or information-related services that are focused, concise, reliable, low cost, timely, and which are provided in forms and formats compatible with the user’s own activities. The information extraction process is generally too complex, too expensive, and too dependent on user conjecture to be applied systematically over an adequate number of scenes. This talk illustrates the current status of the geospatial industry and highlights the evolution of pixels into new capabilities to address the needs of geospatial big data, crowd source, and disaster response.

Biography:

Fabio Pacifici received his Ph.D. degree in GeoInformation from Tor Vergata University, Rome, Italy, in 2010. He also received the Laurea
Specialistica (M.Sc.; cum laude) and Laurea (B.Sc.; cum laude) degrees in telecommunication engineering from the same University, in 2006 and 2003, respectively. He is a Principal R&D Scientist at DigitalGlobe, Inc., where he has been working since 2009. Between 2005 and 2009, he collaborated as Visiting Scientist with the Department of Aerospace Engineering Sciences, University of Colorado, Boulder.

He has more than 10 years of experience in industrial and academic research, developing remote sensing solutions and leading R&D teams. His research includes processing of remote sensing images, data fusion, feature extraction, pattern recognition, and analysis of multi-angular and multi-temporal data. He has interests in classification and change detection techniques for urban remote sensing applications using very high spatial resolution optical and/or synthetic aperture radar imagery, with special emphasis on machine learning.

Dr. Pacifici serves as Associate Editor for the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS) and as Member of the IEEE Geoscience and Remote Sensing Administrative Committee (AdCom). He served as Editor-in-Chief of the IEEE Geoscience and Remote Sensing eNewsletter (2013-2017) and as Chair of the IEEE Geoscience and Remote Sensing Society Data Fusion Technical Committee (2011-2013). He received the Early Career Award from IEEE Geoscience and Remote Sensing Society in recognition of the outstanding service for the benefit and advancement of the geoscience and remote sensing community, and the Best Paper Award at the 6th IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) in Lausanne, Switzerland in 2014. He received the 2011 Best Reviewer Award from IEEE Geoscience and Remote Sensing Society for his service to IEEE JSTARS. He was the recipient of the Best Student Paper award at the 2009 IEEE GRSS Joint Urban Remote Sensing Event, in Shanghai, China. He also won the 2007, 2008 and 2009-2010 IEEE Geoscience and Remote Sensing Society Data Fusion Contest. He currently serves as a member of Technical Committee for the Joint Urban Remote Sensing Event, and for the International Geoscience and Remote Sensing Symposium.

Fabio Pacifici of Digital Globe Inc.

Biography: