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Author Zheng, Q.; Weng, Q.; Huang, L.; Wang, K.; Deng, J.; Jiang, R.; Ye, Z.; Gan, M.
Title A new source of multi-spectral high spatial resolution night-time light imagery—JL1-3B Type Journal Article
Year 2018 Publication Remote Sensing of Environment Abbreviated Journal Remote Sensing of Environment
Volume (down) 215 Issue Pages 300-312
Keywords Remote Sensing
Abstract Artificial light at night (ALAN) provides a unique footprint of human activities and settlements. However, the adverse effects of ALAN on human health and ecosystems have not been well understood. Because of a lack of high resolution data, studies of ALAN in China have been confined to coarse resolution, and fine-scale details are missing. The fine details of ALAN are pertinent, because the highly dense population in Chinese cities has created a distinctive urban lighting pattern. In this paper, we introduced a new generation of high spatial resolution and multi-spectral night-time light imagery from the satellite JL1-3B. We examined its effectiveness for monitoring the spatial pattern and discriminating the types of artificial light based on a case study of Hangzhou, China. Specifically, local Moran's I analysis was applied to identify artificial light hotspots. Then, we analyzed the relationship between artificial light brightness and land uses at the parcel-level, which were generated from GF-2 imagery and open social datasets. Third, a machine learning based method was proposed to discriminate the type of lighting sources – between high pressure sodium lamps (HPS) and light-emitting diode lamps (LED) – by incorporating their spectral information and morphology feature. The result shows a complicated heterogeneity of illumination characteristics across different land uses, where main roads, commercial and institutional areas were brightly lit while residential area, industrial area and agricultural land were dark at night. It further shows that the proposed method was effective at separating light emitted by HPS and LED, with an overall accuracy and kappa coefficient of 83.86% and 0.67, respectively. This study demonstrates the effectiveness of JL1-3B and its superiority over previous night-time light data in detecting details of lighting objects and the nightscape pattern, and suggests that JL1-3B and alike could open up new opportunities for the advancement of night-time remote sensing.
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Corporate Author Thesis
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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 1945
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Author Duriscoe, D.M.; Anderson, S.J.; Luginbuhl, C.B.; Baugh, K.E.
Title A simplified model of all-sky artificial sky glow derived from VIIRS Day/Night band data Type Journal Article
Year 2018 Publication Journal of Quantitative Spectroscopy and Radiative Transfer Abbreviated Journal Journal of Quantitative Spectroscopy and Radiative Transfer
Volume (down) 214 Issue Pages 133-145
Keywords Skyglow; Remote Sensing
Abstract We present a simplified method using geographic analysis tools to predict the average artificial luminance over the hemisphere of the night sky, expressed as a ratio to the natural condition. The VIIRS Day/Night Band upward radiance data from the Suomi NPP orbiting satellite was used for input to the model. The method is based upon a relation between sky glow brightness and the distance from the observer to the source of upward radiance. This relationship was developed using a Garstang radiative transfer model with Day/Night Band data as input, then refined and calibrated with ground-based all-sky V-band photometric data taken under cloudless and low atmospheric aerosol conditions. An excellent correlation was found between observed sky quality and the predicted values from the remotely sensed data. Thematic maps of large regions of the earth showing predicted artificial V-band sky brightness may be quickly generated with modest computing resources. We have found a fast and accurate method based on previous work to model all-sky quality. We provide limitations to this method. The proposed model meets requirements needed by decision makers and land managers of an easy to interpret and understand metric of sky quality.
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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 1879
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Author Román, M.O.; Wang, Z.; Sun, Q.; Kalb, V.; Miller, S.D.; Molthan, A.; Schultz, L.; Bell, J.; Stokes, E.C.; Pandey, B.; Seto, K.C.; Hall, D.; Oda, T.; Wolfe, R.E.; Lin, G.; Golpayegani, N.; Devadiga, S.; Davidson, C.; Sarkar, S.; Praderas, C.; Schmaltz, J.; Boller, R.; Stevens, J.; Ramos González, O.M.; Padilla, E.; Alonso, J.; Detrés, Y.; Armstrong, R.; Miranda, I.; Conte, Y.; Marrero, N.; MacManus, K.; Esch, T.; Masuoka, E.J.
Title NASA's Black Marble nighttime lights product suite Type Journal Article
Year 2018 Publication Remote Sensing of Environment Abbreviated Journal Remote Sensing of Environment
Volume (down) 210 Issue Pages 113-143
Keywords Remote Sensing
Abstract NASA's Black Marble nighttime lights product suite (VNP46) is available at 500 m resolution since January 2012 with data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP). The retrieval algorithm, developed and implemented for routine global processing at NASA's Land Science Investigator-led Processing System (SIPS), utilizes all high-quality, cloud-free, atmospheric-, terrain-, vegetation-, snow-, lunar-, and stray light-corrected radiances to estimate daily nighttime lights (NTL) and other intrinsic surface optical properties. Key algorithm enhancements include: (1) lunar irradiance modeling to resolve non-linear changes in phase and libration; (2) vector radiative transfer and lunar bidirectional surface anisotropic reflectance modeling to correct for atmospheric and BRDF effects; (3) geometric-optical and canopy radiative transfer modeling to account for seasonal variations in NTL; and (4) temporal gap-filling to reduce persistent data gaps. Extensive benchmark tests at representative spatial and temporal scales were conducted on the VNP46 time series record to characterize the uncertainties stemming from upstream data sources. Initial validation results are presented together with example case studies illustrating the scientific utility of the products. This includes an evaluation of temporal patterns of NTL dynamics associated with urbanization, socioeconomic variability, cultural characteristics, and displaced populations affected by conflict. Current and planned activities under the Group on Earth Observations (GEO) Human Planet Initiative are aimed at evaluating the products at different geographic locations and time periods representing the full range of retrieval conditions.
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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 1846
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Author Wang, L.; Wang, S.; Zhou, Y.; Liu, W.; Hou, Y.; Zhu, J.; Wang, F.
Title Mapping population density in China between 1990 and 2010 using remote sensing Type Journal Article
Year 2018 Publication Remote Sensing of Environment Abbreviated Journal Remote Sensing of Environment
Volume (down) 210 Issue Pages 269-281
Keywords Remote Sensing
Abstract Knowledge of the spatial distribution of populations at finer spatial scales is of significant value and fundamental to many applications such as environmental change, urbanization, regional planning, public health, and disaster management. However, detailed assessment of the population distribution data of countries that have large populations (such as China) and significant variation in distribution requires improved data processing methods and spatialization models. This paper described the construction of a novel population spatialization method by combining land use/cover data and night-light data. Based on the analysis of data characteristics, the method used partial correlation analysis and geographically weighted regression to improve the distribution accuracy and reduce regional errors. China's census data for the years 1990, 2000, and 2010 were assessed. The results showed that the method was better at population spatialization than methods that use only night-light data or land use/cover data and global linear regression. Evaluation of overall accuracies revealed that the coefficient of correlation R-square was >0.90 and increased by >0.13 in the years 1990, 2000, and 2010. Moreover, the local R-square of over 90% of the samples (counties) was higher than the adjusted R-square of the general linear regression model. Furthermore, the gridded population density datasets obtained by this method can be used to analyse spatial-temporal patterns of population density and provide population distribution information with increased accuracy and precision compared to conventional models.
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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 2480
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Author Li, P.; Zhang, H.; Wang, X.; Song, X.; Shibasaki, R.
Title A spatial finer electric load estimation method based on night-light satellite image Type Journal Article
Year 2020 Publication Energy Abbreviated Journal Energy
Volume (down) 209 Issue Pages 118475
Keywords Remote Sensing
Abstract As a fundamental parameter of the electric grid, obtaining spatial electric load distribution is the premise and basis for numerous studies. As a public, world-wide, and spatialized dataset, NPP/VIIRS night-light satellite image has been long used for socio-economic information estimation, including electric consumption, while little attention has been given to the electric load estimation. Additionally, most of the previous studies were performed at a large spatial scale, which could not reflect the electric information inner a city. Therefore, this paper proposes a method to estimate electric load density at a township-level spatial scale based on NPP/VIIRS night-light satellite data. Firstly, we reveal the different fitting relationships between EC (Electric Consumption)-NLS (Night-Light Sum) and EL (Electric Load)-NLI (Night-Light Intensity). Then, we validated the spatial-scale’s influence on the estimation accuracy by experiment via generating a series of simulated datasets. After working out the super-resolution night-light image with the SRCNN (Super-Resolution Convolutional Neural Network) algorithm, we established a finer spatial estimation model. By taking a monthly data of Shanghai as a case study, we validate the model we established. The result shows that estimating electric load at township-level based on night-light satellite data is feasible, and the SRCNN algorithm can improve the performance.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0360-5442 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 3068
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