Remote Sensing of Night-Time Light

doi:10.3390/books978-3-0365-7179-9

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https://mdpi.com/books/pdfview/book/7093

Contributor(s)

Goldblatt, Ran (editor)

Rubinyi, Steven Louis (editor)

Park, Hogeun (editor)

Language

English

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Abstract

Satellite measurements of night-time lights are widely recognized as a valuable indicator of human activity on Earth. These measurements capture the amount of light emitted from Earth at night and provide significant insights into a range of fields, including urbanization processes, socio-economic dynamics, local and regional GDP, economic impacts of conflicts, effects of epidemics on economic activity, and the various impacts of natural and man-made disasters. This reprint includes 16 articles that were published in the Remote Sensing Special Issue “Remote Sensing of Night-Time Light” and that highlight novel research on the remote sensing of night-time lights. The reprint aims to stimulate progress in the remote sensing research domain related to the utilization of night-time lights in a wide range of multidisciplinary and interdisciplinary domains, including urban studies, ecology, economics, oceanography, sociology, epidemiology, and more.

URI

https://directory.doabooks.org/handle/20.500.12854/100000

Keywords

VIIRS; Day-night band (DNB); Nighttime lights; COVID-19; Pandemic; earth observation data; nitrogen dioxide (NO2); night light imagery (VIIRS); mobility; environmental impacts; night-time lights; pandemic; protected areas; wildlife tourism; night-time light remote sensing; ethnic minorities; core ethnic minority areas; development index; toponym data; VIIRS/DNB; nighttime lights; shipping; spatial analysis; anchorage area; GDP; nonlinearity; panel data; MAUP; aggregation; DNB; flicker; artificial lighting; county urbanization; population urbanization; land urbanization; economic urbanization; comprehensive urbanization; China; Suomi NPP VIIRS; recalibrated/reprocessed historical radiance data; CNN/SI; urban night light long-term time series; urban growth; aerosols; night-time light data; extraction of urban areas; rank–size rule; law of primate city; DMSP-OLS; data fusion; urbanization processes; insect decline; artificial light at night; nighttime light remote sensing; road lighting quality measurements; JL1-3B; Nanjing; CO2 emission; integration of two nighttime light datasets; spatial-temporal dynamics; STIRPAT; policy; Tibetan plateau; light pollution; urbanization; highway; railway; biodiversity; landscape sustainability; carbon emission; energy conservation; genetic algorithm; nighttime light data; urban agglomerations; remote sensing; snow extent; nighttime; moonlight; thresholding; land cover