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Author Petržala, J.; Kocifaj, M.
Title Research on spectral factors towards determining nocturnal ground irradiance under overcast sky conditions in densely populated regions Type Journal Article
Year 2017 Publication Journal of Quantitative Spectroscopy and Radiative Transfer Abbreviated Journal Journal of Quantitative Spectroscopy and Radiative Transfer
Volume 189 Issue Pages 126-132
Keywords Skyglow
Abstract Light pollution is closely correlated with the meteorological factors, specifically cloudiness that is one of the major amplifiers of night sky radiances in urban regions. Although the decisive effects of cloud deck on artificial nighttime skyglow have been recognized experimentally, the radiative transfer modelling in a heterogeneous nocturnal environment illuminated from many light sources is a non-trivial problem that is difficult to solve both theoretically and numerically. A satisfactorily accurate evaluation of ground-reaching diffuse light is, however, an important issue as some optical properties (e.g. horizontal irradiance) are usually difficult to obtain with common instruments. Overcast sky represents a special class of situations in which clouds can act as amplifiers of the light pollution of the city.

In this paper we proceeded with a simple two-stream approach to solve the scalar radiative transfer equation (RTE) under overcast conditions. The technique we are using allows for a rapid prediction of ground irradiances in densely populated regions assuming various emission functions. We have shown that the classical RTE concept can be adopted in determining the diffuse irradiance, while the model abilities are illustrated in a set of numerical experiments for low and high turbidity states.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0022-4073 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2034
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Author Li, K.; Chen, Y.; Li, Y.
Title The Random Forest-Based Method of Fine-Resolution Population Spatialization by Using the International Space Station Nighttime Photography and Social Sensing Data Type Journal Article
Year 2018 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 10 Issue 10 Pages 1650
Keywords Remote Sensing
Abstract Despite the importance of high-resolution population distribution in urban planning, disaster prevention and response, region economic development, and improvement of urban habitant environment, traditional urban investigations mainly focused on large-scale population spatialization by using coarse-resolution nighttime light (NTL) while few efforts were made to fine-resolution population mapping. To address problems of generating small-scale population distribution, this paper proposed a method based on the Random Forest Regression model to spatialize a 25 m population from the International Space Station (ISS) photography and urban function zones generated from social sensing data—point-of-interest (POI). There were three main steps, namely HSL (hue saturation lightness) transformation and saturation calibration of ISS, generating functional-zone maps based on point-of-interest, and spatializing population based on the Random Forest model. After accuracy assessments by comparing with WorldPop, the proposed method was validated as a qualified method to generate fine-resolution population spatial maps. In the discussion, this paper suggested that without help of auxiliary data, NTL cannot be directly employed as a population indicator at small scale. The Variable Importance Measure of the RF model confirmed the correlation between features and population and further demonstrated that urban functions performed better than LULC (Land Use and Land Cover) in small-scale population mapping. Urban height was also shown to improve the performance of population disaggregation due to its compensation of building volume. To sum up, this proposed method showed great potential to disaggregate fine-resolution population and other urban socio-economic attributes.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2038
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Author Cao, C.; Shao, X.; Uprety, S.
Title Detecting Light Outages After Severe Storms Using the S-NPP/VIIRS Day/Night Band Radiances Type Journal Article
Year 2013 Publication IEEE Geoscience and Remote Sensing Letters Abbreviated Journal IEEE Geosci. Remote Sensing Lett.
Volume 10 Issue 6 Pages 1582-1586
Keywords Remote Sensing
Abstract Power outages after a major storm affect the lives of millions of people and cause massive light outages. The launch of the Suomi National Polar-orbiting Partnership satellite with the Visible Infrared Imaging Radiometer Suite (VIIRS) significantly enhances our capability to monitor and detect light outages with the well-calibrated day/night band (DNB) and to use light loss signatures as indication of regional power outages. This study explores the use of the DNB in quantifying light outages due to the derecho storm in the Washington DC metropolitan area in June 2012 and Hurricane Sandy at the end of October 2012 on the East Coast of U.S. The results show that the DNB data are very useful in detecting power outages by quantifying light loss, but it also has some challenges due to clouds, lunar illumination, and straylight effect. Comparison of light outage and recovery trend determined from DNB data with power company survey shows reasonable agreement, demonstrating the usefulness of DNB in independently verifying and complementing the statistics from power companies.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1545-598X ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2040
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Author Cao, X.; Chen, J.; Imura, H.; Higashi, O.
Title A SVM-based method to extract urban areas from DMSP-OLS and SPOT VGT data Type Journal Article
Year 2009 Publication Remote Sensing of Environment Abbreviated Journal Remote Sensing of Environment
Volume 113 Issue 10 Pages 2205-2209
Keywords Remote Sensing
Abstract Mapping urban areas at regional and global scales has become an urgent task because of the increasing pressures from rapid urbanization and associated environmental problems. Satellite imaging of stable anthropogenic lights from DMSP-OLS provides an accurate, economical, and straightforward way to map the global distribution of urban areas. To address problems in the thresholding methods that use empirical strategies or manual trial-and-error procedures, we proposed a support vector machine (SVM)-based region-growing algorithm to semi-automatically extract urban areas from DMSP-OLS and SPOT NDVI data. Several simple criteria were used to select SVM training sets of urban and non-urban pixels, and an iterative classification and training procedure was adopted to identify the urban pixels through region growing. The new method was validated using the extents of 25 Chinese cities, as classified by Landsat ETM+ images, and then compared with two common thresholding methods. The results showed that the SVM-based algorithm could not only achieve comparable results to the local-optimized threshold method, but also avoid its tedious trial-and-error procedure, suggesting that the new method is an easy and simple alternative for extracting urban extent from DMSP-OLS and SPOT NDVI data.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0034-4257 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2041
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Author Shi, K.; Yu, B.; Huang, Y.; Hu, Y.; Yin, B.; Chen, Z.; Chen, L.; Wu, J.
Title Evaluating the Ability of NPP-VIIRS Nighttime Light Data to Estimate the Gross Domestic Product and the Electric Power Consumption of China at Multiple Scales: A Comparison with DMSP-OLS Data Type Journal Article
Year 2014 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 6 Issue 2 Pages 1705-1724
Keywords Remote Sensing
Abstract The nighttime light data records artificial light on the Earth’s surface and can be used to estimate the spatial distribution of the gross domestic product (GDP) and the electric power consumption (EPC). In early 2013, the first global NPP-VIIRS nighttime light data were released by the Earth Observation Group of National Oceanic and Atmospheric Administration’s National Geophysical Data Center (NOAA/NGDC). As new-generation data, NPP-VIIRS data have a higher spatial resolution and a wider radiometric detection range than the traditional DMSP-OLS nighttime light data. This study aims to investigate the potential of NPP-VIIRS data in modeling GDP and EPC at multiple scales through a case study of China. A series of preprocessing procedures are proposed to reduce the background noise of original data and to generate corrected NPP-VIIRS nighttime light images. Subsequently, linear regression is used to fit the correlation between the total nighttime light (TNL) (which is extracted from corrected NPP-VIIRS data and DMSP-OLS data) and the GDP and EPC (which is from the country’s statistical data) at provincial- and prefectural-level divisions of mainland China. The result of the linear regression shows that R2 values of TNL from NPP-VIIRS with GDP and EPC at multiple scales are all higher than those from DMSP-OLS data. This study reveals that the NPP-VIIRS data can be a powerful tool for modeling socioeconomic indicators; such as GDP and EPC.
Address (up)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2042
Permanent link to this record