Open Access #4 2021
Abstract This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. ; Nighttime images taken with DSLR cameras from the International Space Station (ISS) can provide valuable information on the spatial and temporal variation of artificial nighttime lighting on Earth. In particular, this is the only source of historical and current visible multispectral data across the world (DMSP/OLS and SNPP/VIIRS-DNB data are panchromatic and multispectral in the infrared but not at visible wavelengths). The ISS images require substantial processing and proper calibration to exploit intensities and ratios from the RGB channels. Here we describe the different calibration steps, addressing in turn Decodification, Linearity correction (ISO dependent), Flat field/Vignetting, Spectral characterization of the channels, Astrometric calibration/georeferencing, Photometric calibration (stars)/Radiometric correction (settings correction - by exposure time, ISO, lens transmittance, etc) and Transmittance correction (window transmittance, atmospheric correction). We provide an example of the application of this processing method to an image of Spain. © 2021 The Author(s). ; This work was supported by the EMISSI@N project (NERC grant NE/P01156X/1), Fonds de Recherche du Québec: Nature et Technologies (FRQNT), COST (European Cooperation in Science and Technology) Action ES1204 LoNNe (Loss of the Night Network), the ORISON project (H2020-INFRASUPP-2015-2), the Cities at Night project, FPU grant from the Ministerio de Ciencia y Tecnologia and F. Sánchez de Miguel. Cameras were tested at Laboratorio de Investigaciónn Científica Avanzada (LICA), a facility of UCM-UPM funded by the Spanish program of International Campus of Excellence Moncloa (CEI). We acknowledge the support of the Spanish Network for Light Pollution Studies (MINECO AYA2011-15808-E) and also from STARS4ALL, a project funded by the European Union H2020-ICT-2015-688135. This work has been partially funded by the Spanish MICINN, (AyA2018-RTI-096188-B-I00), and by the Madrid Regional Government through the TEC2SPACE-CM Project (P2018/NMT-4291), Miniesterio de Ciencia y Tecnología (H2020). ; With funding from the Spanish government through the Severo Ochoa Centre of Excellence accreditation SEV-2017-0709. ; Peer reviewed