Remote Sensing of Night Lights—Beyond DMSP

Kollath

2022

Ecology and Evolution

The global increase in light pollution is being viewed with growing concern, as it has been reported to have negative effects ranging from the individual to the ecosystem level. Unlike movement on the ground, flying and swimming allows vertical motion. Here, we demonstrate that flight altitude change is crucial to the perception and susceptibility of artificial light at night of air‐borne organisms. Because air‐borne species can propagate through the airspace and easily across ecotones, effects might not be small‐scale. Therefore, we propose including airspace as a vital habitat in the concept of ecological light pollution. The interplay between flight altitude and the effects of light pollution may not only be crucial for understanding flying species but may also provide valuable insights into the mechanisms of responses to artificial light at night in general.

Section: From Surface To Volumementioning

confidence: 99%

X,Y, and Z: A bird's eye view on light pollution

Kollath

2022

Ecology and Evolution

“…Therefore, they have been widely used in the field of social science such as gross national product, greenhouse gas emissions, poverty index, urbanization monitoring and evaluation, urban agglomeration evolution analysis and light pollution analysis. In addition to reflecting the lights from urban areas, nighttime light remote sensing can also capture the lights of fishing boats, natural gas combustion, forest fires, etc., so it can also provide important support for many other research fields such as fishery monitoring, major event estimation and natural disaster risk assessment [ 1 , 2 , 3 , 4 , 5 ].…”

Section: Introductionmentioning

confidence: 99%

Optical Design of Imaging Spectrometer Based on Linear Variable Filter for Nighttime Light Remote Sensing

Xie

Liu

et al. 2021

Sensors

Nighttime light remote sensing has unique advantages on reflecting human activities, and thus has been used in many fields including estimating population and GDP, analyzing light pollution and monitoring disasters and conflict. However, the existing nighttime light remote sensors have many limitations because they are subject to one or more shortcomings such as coarse spatial resolution, restricted swath width and lack of multi-spectral data. Therefore, we propose an optical system of imaging spectrometer based on linear variable filter. The imaging principle, optical specifications, optical design, imaging performance analysis and tolerance analysis are illustrated. The optical system with a focal length of 100 mm, F-number 4 and 43° field of view in the spectrum range of 400–1000 nm is presented, and excellent image quality is achieved. The system can obtain the multi-spectral images of eight bands with a spatial resolution of 21.5 m and a swath width of 320 km at the altitude of 500 km. Compared with the existing nighttime light remote sensors, our system possesses the advantages of high spatial and high spectral resolution, wide spectrum band and wide swath width simultaneously, greatly making up for the shortage of the present systems. The result of tolerance analysis shows our system satisfy the requirements of fabrication and alignment.

“…For another thing, the Day-Night Band (DNB) in the NPP satellite system under low brightness conditions is widely used to estimate social and economic parameters, and in-orbit radiation correction can improve the data quality [17]. Considering the above factors and the existing research [18][19][20][21], accurate results can be obtained by using NPP-VIIRS images to estimate socioeconomic parameters.…”

Section: Introductionmentioning

confidence: 99%

Estimating Rural Electric Power Consumption Using NPP-VIIRS Night-Time Light, Toponym and POI Data in Ethnic Minority Areas of China

et al. 2020

Aiming at the problem that the estimation of electric power consumption (EPC) by using night-time light (NTL) data is mostly concentrated in large areas, a method for estimating EPC in rural areas is proposed. Rural electric power consumption (REPC) is a key indicator of the national socio-economic development. Despite an improved quality of life in rural areas, there is still a big gap between electricity consumption between rural residents and urban residents in China. The experiment takes REPC as the research target, selects Dehong (DH) Dai Jingpo Autonomous Prefecture of Yunnan Province as an example, and uses the NTL data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day–Night Band (DNB) carried by the Suomi National Polar-orbiting Partnership (NPP) Satellite from 2012 to 2017, toponym and points-of-interest (POI) data as the main data source. By performing kernel density estimation to extract the urban center and rural area boundaries in the prefecture, and combining the county-level boundary data and electric power data, a linear regression model of the total rural NTL intensity and REPC is estimated. Finally, according to the model, the EPC in ethnic minority rural areas is estimated at a 1-km spatial resolution. The results show that the NPP-REPC model can simulate REPC within a small average error (17.8%). Additionally, there are distinct spatial differences of REPC in ethnic minority areas.