Metrology for Earth Observation and Climate 3 - Metrology for Earth Observation and Climate

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