| Records |
| Author |
Sun, B.; Zhang, Y.; Zhou, Q.; Gao, D. |
| Title |
Street-Scale Analysis of Population Exposure to Light Pollution Based on Remote Sensing and Mobile Big Data-Shenzhen City as a Case |
Type |
Journal Article |
Year  |
2020 |
Publication |
Sensors (Basel, Switzerland) |
Abbreviated Journal |
Sensors (Basel) |
| Volume |
20 |
Issue |
9 |
Pages |
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| Keywords |
Remote Sensing; Luojia 1-01; NTL remote sensing; light pollution; population exposure to light pollution; residential area |
| Abstract |
Most studies on light pollution are based on light intensity retrieved from nighttime light (NTL) remote sensing with less consideration of the population factors. Furthermore, the coarse spatial resolution of traditional NTL remote sensing data limits the refined applications in current smart city studies. In order to analyze the influence of light pollution on populated areas, this study proposes an index named population exposure to light pollution (PELP) and conducts a street-scale analysis to illustrate spatial variation of PELP among residential areas in cites. By taking Shenzhen city as a case, multi-source data were combined including high resolution NTL remote sensing data from the Luojia 1-01 satellite sensor, high-precision mobile big data for visualizing human activities and population distribution as well as point of interest (POI) data. Results show that the main influenced areas of light pollution are concentrated in the downtown and core areas of newly expanded areas with obvious deviation corrected like traditional serious light polluted regions (e.g., ports). In comparison, commercial-residential mixed areas and village-in-city show a high level of PELP. The proposed method better presents the extent of population exposure to light pollution at a fine-grid scale and the regional difference between different types of residential areas in a city. |
| Address |
TalkingData Co., Ltd., Beijing 100027, China |
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| Language |
English |
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Series Issue |
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Edition |
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| ISSN |
1424-8220 |
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| Notes |
PMID:32403250 |
Approved |
no |
| Call Number |
GFZ @ kyba @ |
Serial |
2921 |
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| Author |
Yue, Y.; Tian, L.; Yue, Q.; Wang, Z. |
| Title |
Spatiotemporal Variations in Energy Consumption and Their Influencing Factors in China Based on the Integration of the DMSP-OLS and NPP-VIIRS Nighttime Light Datasets |
Type |
Journal Article |
| Year |
2020 |
Publication |
Remote Sensing |
Abbreviated Journal |
Remote Sensing |
| Volume |
12 |
Issue |
7 |
Pages |
1151 |
| Keywords |
Remote Sensing |
| Abstract |
With the speedy growth of economic development, the imbalance of energy supply and demand pose a critical challenge for the energy security of our country. Meanwhile, the increasing and excessive energy consumption lead to the greenhouse effect and atmospheric pollution, greatly threatening the survival and development of human beings. This study integrated two nighttime light remote sensing datasets, namely Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) data and Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) data, to extend the temporal coverage of the study. Then, the distributions of China’s energy consumption from 1995 to 2016 at a 1-km resolution were estimated using different models and the spatiotemporal variations of energy consumption were explored on the basis of the best estimated results. Next, the factors influencing China’s energy intensity on the provincial level were investigated based on the spatial econometric model. The results show that: (1) The integrated nighttime light datasets can be successfully applied to estimate the dynamic changes of energy consumption. Moreover, the panel data model established in our research performed better than the quadratic polynomial model. (2) During the observation period, the energy consumption in China significantly increased, especially in the Yangtze River Delta, the Pearl River Delta, the Beijing–Tianjin–Hebei region, eastern coastal cities, and provincial capitals. (3) Different from the random spatial distribution pattern of energy consumption on the provincial level, the spatial distribution of energy consumption on the prefectural level has significant clusters, and its spatial agglomeration was strengthened year by year during the research period. (4) The spatial Durbin model (SDM) with a spatial fixed effect has been proved to be more suitable to explore the impact mechanism of China’s energy consumption. Among the four socio-economic factors, industrial structure has the greatest impact on the provincial energy intensity in China. Moreover, the changes in industrial structure and foreign direct investment (FDI) can not only influence the local energy intensity but also affect the energy intensity of the neighboring provinces. |
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| ISSN |
2072-4292 |
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no |
| Call Number |
GFZ @ kyba @ |
Serial |
2922 |
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| Author |
Linares, H.; Masana, E.; Ribas, S.J.; Aubé, M.; Simoneau, A.; Bará, S. |
| Title |
Night sky brightness simulation over Montsec protected area |
Type |
Journal Article |
| Year |
2020 |
Publication |
Journal of Quantitative Spectroscopy and Radiative Transfer |
Abbreviated Journal |
Journal of Quantitative Spectroscopy and Radiative Transfer |
| Volume |
249 |
Issue |
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Pages |
106990 |
| Keywords |
Skyglow |
| Abstract |
Night sky brightness over Montsec Observatory (north-east of Spain) has been computed and checked against measurements using Illumina numerical model [2]. In a previous publication [20] the methodology was validated and light pollution received in the observatory coming from a unique city was computed. Here we present a simulation that includes all the sources that has a significant impact over the quality of the night sky in this area. The decision of which sources should be included in the simulations was taken following the methodology explained by [6]: using a point spread function (PSF) as a simple approach to estimate which sources are brightening the sky dome over the observer. An ad hoc PSF derived with Illumina was used with the purpose of avoiding to have to rely on already existing empirical PSF. The resulting PSF can be used in any location with similar atmospheric conditions. Differences in the spectrum of the lamps can be accounted easily by adjusting a spectrum scale factor. Illumina simulates the artificial sky brightness received (W/sr/m2) by an observer from any direction. Adding the natural sky brightness allows to compare the simulations to measurements taken with different instrumentation. In our case simulations were checked against ASTMON, SQC and SQM measurements. They show a good agreement both in absolute values and in geographical patterns for the three filters studied, B, V and R. The methodology presented opens many possibilities, such as increasing the reliability of the maps that point out the light pollution main contributors for any location, and reducing the amount of time needed to perform an accurate simulation of the night sky brightness. |
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| ISSN |
0022-4073 |
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no |
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GFZ @ kyba @ |
Serial |
2923 |
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| Author |
Kolláth, Z.; Száz, D.; Kolláth, K.; Tong, K.P. |
| Title |
Light Pollution Monitoring and Sky Colours |
Type |
Journal Article |
| Year |
2020 |
Publication |
Journal of Imaging |
Abbreviated Journal |
J. Imaging |
| Volume |
6 |
Issue |
10 |
Pages |
104 |
| Keywords |
Skyglow; Instrumentation; light pollution; imaging radiometry; colorimetry |
| Abstract |
The measurement of night sky quality has become an important task in nature conservation. The primary device used for this task can be a calibrated digital camera. In addition, colour information can be derived from sky photography. In this paper, we provide a test on a concept to gather information about the possible sources of night sky brightness based on digital camera images. This method helps to understand changes in night sky quality due to natural and artificial changes in the environment. We demonstrate that a well-defined colour–colour diagram can differentiate between the different natural and artificial sources of night sky radiance. The colour information can be essential when interpreting long-term evolution of light pollution measurements. |
| Address |
Department of Physics, Eötvös Loránd University (ELTE) BDPK, 9700 Szombathely, Hungary; zkollath( at ) gmail.com |
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| Publisher |
MDPI |
Place of Publication |
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| Language |
English |
Summary Language |
English |
Original Title |
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2313-433X |
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no |
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IDA @ john @ |
Serial |
3170 |
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| Author |
Chang, S.; Wang, J.; Zhang, F.; Niu, L.; Wang, Y. |
| Title |
A study of the impacts of urban expansion on vegetation primary productivity levels in the Jing-Jin-Ji region, based on nighttime light data |
Type |
Journal Article |
| Year |
2020 |
Publication |
Journal of Cleaner Production |
Abbreviated Journal |
Journal of Cleaner Production |
| Volume |
263 |
Issue |
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Pages |
121490 |
| Keywords |
Remote Sensing |
| Abstract |
Rapid urbanization has generated enormous pressure on natural resources. This study illustrates urban expansion in the Jing-Jin-Ji region and its influence on vegetation primary productivity. Tempo-spatial correlations between a vegetation index and nighttime light intensity are discussed to assess the urbanization effect quantitatively. The results show that: (1) From 1998 to 2018, urban areas gradually expanded outward from their original conglomerations. (2) In the past 20 years, Beijing and Tianjin have developed in different ways. The surrounding satellite cities have mostly developed concentrically, although some cities in Hebei province have developed more linearly. (3) The average primary productivity of the study area in 1998, 2003, 2008, 2013, and 2018 was generally lower than that of non-urban regions of the same year. (4) During the period from 1998 to 2018, the primary productivity of vegetation in the urban built-up areas increased, and the condition of the plant improved. |
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0959-6526 |
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GFZ @ kyba @ |
Serial |
2925 |
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