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Author Danesh Yazdi, M.; Kuang, Z.; Dimakopoulou, K.; Barratt, B.; Suel, E.; Amini, H.; Lyapustin, A.; Katsouyanni, K.; Schwartz, J.
Title Predicting Fine Particulate Matter (PM2.5) in the Greater London Area: An Ensemble Approach using Machine Learning Methods Type Journal Article
Year 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 12 Issue 6 Pages 914
Keywords Remote Sensing
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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 (down) 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2856
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Author Ma, J.; Guo, J.; Ahmad, S.; Li, Z.; Hong, J.
Title Constructing a New Inter-Calibration Method for DMSP-OLS and NPP-VIIRS Nighttime Light Type Journal Article
Year 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 12 Issue 6 Pages 937
Keywords Remote Sensing
Abstract The anthropogenic nighttime light (NTL) data that are acquired by satellites can characterize the intensity of human activities on the ground. It has been widely used in urban development assessment, socioeconomic estimate, and other applications. However, currently, the two main sensors, Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) and Suomi National Polar-orbiting Partnership Satellite’s Visible Infrared Imaging Radiometer Suite (NPP-VIIRS), provide inconsistent data. Hence, the application of NTL for long-term analysis is hampered. This study constructed a new inter-calibration method for DMSP-OLS and NPP-VIIRS nighttime light to solve this problem. First, NTL data were processed to obtain vicarious site across China. By comparing different candidate models, it is discovered the Biphasic Dose Response (BiDoseResp) model, which is a weighted combination of sigmoid functions, can best perform the regression between DMSP-OLS and logarithmically transformed NPP-VIIRS. The coefficient of determination of BiDoseResp model reaches 0.967. It’s residual sum of squares is 6.136×105 , which is less than 6.199×105 of Logistic function. After obtaining the BiDoseResp-calibrated VIIRS (BDRVIIRS), we smoothed it by a filter with optimal parameters to maximize the consistency. The result shows that the consistency of NTL data is greatly enhanced after calibration. In 2013, the correlation coefficient between DMSP-OLS and original NPP-VIIRS data in the China region is only 0.621, while that reaches to 0.949 after calibration. Finally, a consistent NTL dataset of China from 1992 to 2018 was produced. When compared with the existing methods, our method is applicable to the full dynamic range of DMSP-OLS. Besides, it is more suitable for country or larger scale areas. It is expected that this method can greatly facilitate the development of research that is based on the historical NTL archive.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN (down) 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2860
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Author Duan, X.; Hu, Q.; Zhao, P.; Wang, S.; Ai, M.
Title An Approach of Identifying and Extracting Urban Commercial Areas Using the Nighttime Lights Satellite Imagery Type Journal Article
Year 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 12 Issue 6 Pages 1029
Keywords Remote Sensing
Abstract Urban commercial areas can reflect the spatial distribution of business activities. However, the scope of urban commercial areas cannot be easily detected by traditional methods because of difficulties in data collection. Considering the positive correlation between business scale and nighttime lighting, this paper proposes a method of urban commercial areas detection based on nighttime lights satellite imagery. First, an imagery preprocess model is proposed to correct imageries and improve efficiency of cluster analysis. Then, an exploratory spatial data analysis and hotspots clustering method is employed to detect commercial areas by geographic distribution metric with urban commercial hotspots. Furthermore, four imageries of Wuhan City and Shenyang City are selected as an example for urban commercial areas detection experiments. Finally, a comparison is made to find out the time and space factors that affect the detection results of the commercial areas. By comparing the results with the existing map data, we are convinced that the nighttime lights satellite imagery can effectively detect the urban commercial areas. The time of image acquisition and the vegetation coverage in the area are two important factors affecting the detection effect. Harsh weather conditions and high vegetation coverage are conducive to the effective implementation of this method. This approach can be integrated with traditional methods to form a fast commercial areas detection model, which can then play a role in large-scale socio-economic surveys and dynamic detection of commercial areas evolution. Hence, a conclusion can be reached that this study provides a new method for the perception of urban socio-economic activities.
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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 (down) 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2870
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Author Ernst, S.; Łabuz, M.; Środa, K.; Kotulski, L.
Title Graph-Based Spatial Data Processing and Analysis for More Efficient Road Lighting Design Type Journal Article
Year 2018 Publication Sustainability Abbreviated Journal Sustainability
Volume 10 Issue 11 Pages 3850
Keywords Lighting
Abstract The efficiency and affordability of modern street lighting equipment are improving quickly, but systems used to manage and design lighting installations seem to lag behind. One of their problems is the lack of consistent methods to integrate all relevant data. Tools used to manage lighting infrastructure are not aware of the geographic characteristics of the lit areas, and photometric calculation software requires a lot of manual editing by the designer, who needs to assess the characteristics of roads, define the segments, and assign the lighting classes according to standards. In this paper, we propose a graph-based method to integrate geospatial data from various sources to support the process of data preparation for photometric calculations. The method uses graph transformations to define segments and assign lighting classes. A prototype system was developed to conduct experiments using real-world data. The proposed approach is compared to results obtained by professional designers in a case study; the method was also applied to several European cities to assess its efficiency. The obtained results are much more fine-grained than those yielded by the traditional approach; as a result, the lighting is more adequate, especially when used in conjunction with automated optimisation tools.
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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 (down) 2071-1050 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2051
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Author Jechow, A.
Title Observing the Impact of WWF Earth Hour on Urban Light Pollution: A Case Study in Berlin 2018 Using Differential Photometry Type Journal Article
Year 2019 Publication Sustainability Abbreviated Journal Sustainability
Volume 11 Issue 3 Pages 750
Keywords Skyglow; Remote Sensing
Abstract Earth Hour is one of the most successful coordinated mass efforts worldwide to raise awareness of environmental issues, with excessive energy consumption being one driver of climate change. The campaign, first organized by the World Wildlife Fund in Australia in 2007, has grown across borders and cultures and was celebrated in 188 countries in 2018. It calls for voluntarily reduction of electricity consumption for a single hour of one day each year. Switching off non-essential electric lights is a central theme and resulted in 17,900 landmarks going dark in 2018. This switch-off of lights during Earth Hour also leads to reduction of light pollution for this specific period. In principle, Earth Hour allows the study of light pollution and the linkage to electricity consumption of lighting. However, quantitative analysis of the impact of Earth Hour on light pollution (and electricity consumption) are sparse, with only a few studies published showing no clear impact or the reverse, suffering from residual twilight and unstable weather conditions. In this work, light pollution measurements during Earth Hour 2018 in an urban park (Tiergarten) in Berlin, Germany, are reported. A novel light measurement method using differential photometry with calibrated digital cameras enables tracking of the switching off and switching back on of the lights of Berlin’s iconic Brandenburg Gate and the buildings of Potsdamer Platz adjacent to the park. Light pollution reduction during the event was measurable, despite the presence of moonlight. Strategies for future work on light pollution using such events are discussed.
Address
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 (down) 2071-1050 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2198
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