Colour remote sensing of the impact of artificial light at night (I): The potential of the International Space Station and other DSLR-based platforms

REMOTE SENSING OF ENVIRONMENT

卷:224

Article

Sanchez de Miguel, Alejandro^1,2,3,4  Kyba, Christopher C. M.^5,6  Aube, Martin³  Zamorano, Jaime²  Cardiel, Nicolas²  Tapia, Carlos²  Bennie, Jon¹  Gaston, Kevin J.^1,7 

[1] Univ Exeter, Environm & Sustainabil Inst, Penryn TR10 9FE, Cornwall, England

[2] Univ Complutense, Inst Fis Particulas & COSMOS IPARCOS, Dept Fis Tierra & Astrofis, Madrid, Spain

[3] CEGEP Sherbrooke, Phys Dept, Sherbrooke, PQ J1E 4K1, Canada

[4] Inst Astrofis Andalucia, Glorieta Astron S-N, Granada 18008, Spain

[5] German Ctr Geosci GFZ, Remote Sensing, D-14473 Potsdam, Germany

[6] Leibniz Inst Freshwater Ecol & Inland Fisheries, Ecohydrol, Muggelseedamm 310, D-12587 Berlin, Germany

[7] Inst Adv Study, Wissenschaftskolleg Berlin, Wallotstr 19, D-14193 Berlin, Germany

关键词: Artificial lighting;    Light pollution;    Night;    Remote sensing;    Urban;   

DOI  :  10.1016/j.rse.2019.01.035

来源: Elsevier

【 摘 要 】

Sensors on remote sensing satellites have provided useful tools for evaluation of the environmental impacts of nighttime artificial light pollution. However, due to their panchromatic nature, the data available from these sensors (VIIRS/DNB and DMSP/OLS) has a limited capacity accurately to assess this impact. Moreover, in some cases, recorded variations can be misleading. Until new satellite platforms and sensors are available, only nighttime images taken with DSLR cameras from the International Space Station (ISS), airplanes, balloons or other such platforms can provide the required information. Here we describe a theoretical approach using colour-colour diagrams to analyse images taken by astronauts on the ISS to estimate spatial and temporal variation in the spectrum of artificial lighting emissions. We then evaluate how this information can be used to determine effects on some key environmental indices: photopic vision, the Melatonin Suppression Index, the Star Light Index, the Induced Photosynthesis Index, production of NO2-NO radicals, energy efficiency and CO2 emissions, and Correlated Colour Temperature. Finally, we use the city of Milan as a worked example of the approach.

【 授权许可】

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