I would like to know about the future development of quantitative research on night light.
Múltiples procesamientos espectrales pueden ser desarrollados con imágenes para cualquier Geociencias y en Áreas de OBSCURIDAD Es cuestión de formularse preguntas de interés, según los objetivos específicos de la investigación. Hay autores que han publicado papers bajo esas Circunstancias.
You can record temperatures emitted from various objects. A practical application is the heat loss from the buildings due to inefficient insulation. You can also record the land temperature to use for various applications such as agriculture.
Night light remote sensing was originally developed to map clouds illuminated by moonlight, to support USAF missions. Urban planning is a collateral benefit.
Night light can be used as a poverty proxy in areas with data scarcity.
One can estimate population densities.
For sure in regions where demographic data are non existent or of deplorable quality.
One has to train and validate the demographic model as well.
A validated model exists for child labour in the Ganghes catchment.
#NoMercyCV
It's important also in astronomy site selection and to study the impact of light on animal behaviour.
Night light remote sensing holds practical significance in fields like monitoring economic activities, estimating energy consumption, and assessing social development.
It aids in tracking urbanization trends, identifying infrastructure disparities, and studying the impact of human activities on the environment, making it a valuable tool for diverse applications beyond urban planning.
See "Fifty years of nightly global low-light imaging satellite observations" at https://www.frontiersin.org/articles/10.3389/frsen.2022.919937/full
Monthly and annual nighttime lights
The Earth Observation Group traces its origins to 1994 when a DMSP fire detection project funded at NGDC by the U.S. Department of Defense Strategic Environmental Research and Development Program (SERDP). The original EOG team at NGDC consisted of Chris Elvidge, Kimberly Baugh, Ethan Davis and Edward Erwin. The first task in the SERDP project was to develop a map of stable lights that could be used as a mask to detect biomass burning in rural areas. Kim and Ethan wrote software to geolocated OLS data.
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