Contribution to sandy site characterization: Spectro-directional signature, grain size distribution and mineralogy extracted from sand samples
KAUST DepartmentBiological and Environmental Sciences and Engineering (BESE) Division
Red Sea Research Center (RSRC)
Visual Computing Center (VCC)
Permanent link to this recordhttp://hdl.handle.net/10754/660213
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AbstractThe characterization of sands detailed in this paper has been performed in order to support the in-flight radiometric performance assessment of space-borne optical sensors over the so-called Pseudo-Invariant Calibration Sites (PICS). Although the physical properties of PICS surface are fairly stable in time, the signal measured from space varies with the illumination and the viewing geometries. Thus, there is a need to characterize the spectro-directional properties of PICS. This could be done on a broad scale, thanks to multi-spectral multi-directional space-borne sensors such as the POLDER instrument (with old data). However, interpolating or extrapolating the spectro-directional reflectance measured from space to spectral bands of another sensor is not straightforward. The hyperspectral characterization of sand samples collected within or nearby PICS could contribute to a solution. In this context, a set of 31 sand samples was compiled. The BiConical Reflectance Factor (BCRF), linked to Bidirectional Reflectance Distribution Function (BRDF), was measured between 0.4 and 2.5 μm, over a half hemisphere when the amount of sand in the sample was large enough and for only a single fixed angular configuration for small samples. These optical measurements were complemented by grain size distribution measurements and mineralogical analysis and compiled together with previously published measurements in the so-called PICSAND database, freely available online.
CitationViallefont-Robinet, Bacour, Bouvet, Kheireddine, Ouhssain, Idoughi, … Rivière. (2019). Contribution to Sandy Site Characterization: Spectro-Directional Signature, Grain Size Distribution and Mineralogy Extracted from Sand Samples. Remote Sensing, 11(20), 2446. doi:10.3390/rs11202446
SponsorsWe wish to acknowledge all the contributors to the database: Jerzy Cierniewski (University in Poznań, Poland) and Arnon Karnieli (Blaustein International Center for Desert Studies, Israel), Craig Coburn (University of Lethbridge, Canada), Jouni Peltoniemi (Finnish Geodetic Institute, Masala, Finland), Peter Roosjen (Laboratory of Geo-Information Science and Remote Sensing,Wageningen University&Research, The Netherlands), Zhongqiu Sun (School of Geographical Science, Northeast Normal University, Changchun, Jilin, China), Hong Zhang, and Zhengchao Chen (Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China), Kenneth Voss (University of Miami, Miami, USA) and Hao Zhang (China University of Geosciences, Wuhan, China), Claire Greenwell (National Physical Laboratory, UK), Andreas Hueni (University of Zurich, Switzerland), Kevin White (University of Reading, UK) and Joanna Bullard (Loughborough University, UK), and the sand samples providers: Charles Bristow from the Birkbeck University of London (United Kingdom), Ian Lau from CSIRO (Australia), Laurent Poutier from ONERA (France), Michael Schaepmann from University of Zurich (Switzerland), Kevin White from the University of Reading (United Kingdom), Burton Jones and Wolfgang Heidrich from King Abdullah University of Sciences and Technology (Kingdom of Saudi Arabia) and the French Defense Forces. The study was funded by ESA (European Space Agency), contract no. 4000116561/16/NL/AF, and performed in the framework of the PICSAND project.
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