Metrology for Earth Observation and Climate 3
Non-linear response to a class of hyper-spectral radiometers
Marco Talone and Giuseppe Zibordi
Published 21 September 2018 • © 2018 BIPM & IOP Publishing Ltd
doi.org/10.1088/1681-7575/aadd7f
Realistic Forest Stand Reconstruction from Terrestial LiDAR for Radiative Transfer Modelling
Kim Calders, Niall Origo, Andrew Burt, Mathias Disney, Joanne Nightingale, Pasi Raumonen, Markku Åkerblom, Yadvinder Malhi, Philip Lewis
Remote Sens. (2018), 10(6), 933;
doi.org/10.3390/rs10060933
RadCalNet: A Radiometric Calibration Network for Earth Observing Imagers Operating in the Visible to Shortwave Infrared Spectral Range
Bouvet, M., (2019).
www.mdpi.com/2072-4292/11/20/2401
Monte-Carlo based quantification of uncertainties in determining ocean remote sensing reflectance from underwater fixed-depth radiometry measurements
Bialek, A., (2020).
https://doi.org/10.1175/JTECH-D-19-0049.1
Calibration of a CubeSat spectroradiometer with a narrow-band widely tunable radiance source
Berg, S., (2021).
https://doi.org/10.1364/AO.417467
Traceability of the Sentinel-3 SLSTR Level-1 Infrared Radiometric Processing
Smith, D., (2021).
https://doi.org/10.3390/rs13030374
Comparison of the Sentinel-3A and B SLSTR Tandem Phase Data Using Metrological Principles
Hunt, S., (2020).
https://doi.org/10.3390/rs12182893
Uncertainty Analysis for RadCalNet Instrumented Test Sites Using the Baotou Sites BTCN and BSCN as Examples
Ma, L., (2020).
https://doi.org/10.3390/rs12111696
Ancillary Data Uncertainties within the SeaDAS Uncertainty Budget for Ocean Colour Retrievals
Pieter De Vis, Frederic Melin, Samuel E. Hunt, Rosalinda Morrone, Morven Sinclair, Bill Bell
Remote Sens. (2022), 14(3), 497;
https://doi.org/10.3390/rs14030497