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Author Jiang, Z.; Zhai, W.; Meng, X.; Long, Y.
Title Identifying Shrinking Cities with NPP-VIIRS Nightlight Data in China Type Journal Article
Year (down) 2020 Publication Journal of Urban Planning and Development Abbreviated Journal J. Urban Plann. Dev.
Volume 146 Issue 4 Pages 04020034
Keywords Remote Sensing
Abstract Although there has been a rapid urbanization in China since the 1980s, the simultaneous urban shrinkage phenomenon has existed for a long time. The study of shrinking cities is particularly important for China as the current urban development has changed from physical expansion to built-up area improvement. After redefining what constitutes a city (what we term a natural city), we compared the adjusted nightlight intensity of National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) data between 2013 and 2016 to accurately identify shrinking cities throughout China. The results indicate that there are 2,862 redefined natural cities in China and that the total area reaches 53,275 km2, about 0.5% of the national territory. Based on this, we identified 798 shrinking cities with a total area of 13,839 km2. After analyzing the relative position of shrinking cities and internal shrinking pixels in the geometric space, the morphological characteristics of shrinking cities were systematically classified into six patterns. The majority of shrinking cities belong to scatter shrinkage, central shrinkage, and local shrinkage; only 5% are complete shrinkage; the rest are unilateral shrinkage and peripheral shrinkage. In addition, six shrinkage causes were quantitatively classified and summarized by referring to multiple-source urban data and municipal yearbooks. To enrich the methodological system for urban shrinkage, the research provides a reminder of the need to consider the other side of urbanization (i.e., dissolution of social networks) and proposes appropriate strategies and policies to address shrinkage issues.
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0733-9488 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 3065
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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 (down) 2020 Publication Energy Abbreviated Journal Energy
Volume 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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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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Author Ye, Y.; Xue, X.; Huang, L.; Gan, M.; Tong, C.; Wang, K.; Deng, J.
Title A new perspective to map the supply and demand of artificial night light based on Loujia1-01 and urban big data Type Journal Article
Year (down) 2020 Publication Journal of Cleaner Production Abbreviated Journal Journal of Cleaner Production
Volume 276 Issue Pages 123244
Keywords Remote Sensing
Abstract The notable increase in artificial night light (ANL) induced by the rapid urbanization process has been widely studied, but a deep understanding of the supply and demand status of ANL is still lacking. This paper attempts to map the supply and demand of ANL from the human perspective by using advanced Loujia1-01 nighttime imagery and social media derived population density (PD) data, which provides a new tool for light regulation in urban management. The bivariate clustering based k-means algorithm and template matching technique are integrated to delineate mismatch regions at the block scale to further analyze the underlying reason for unbalanced status. The results showed that the high supply but low demand (HSLD) ANL status was the leading component in the mismatch regions, occupying more than 650,000 ha and mainly occurring in the city center. The HSLD proportion was considerable in terms of public services (44%), commercial (40%), industrial (39%), transportation (56%), and green space areas (53%). Moreover, the HSLD area notably increased 946 ha over time from 18:00 to 22:00. The measurements for validation obtained by field investigation showed highly linear relationship with ANL (R2 = 0.75) and PD (R2 = 0.62), and the mapping results were consistent with the actual conditions. This study reveals the highly unbalanced ANL status, and appeals to planners for the establishment of optimal lighting regulations to alleviate disruptive effects.
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0959-6526 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 3070
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Author Davies, T.W.; McKee, D.; Fishwick, J.; Tidau, S.; Smyth, T.
Title Biologically important artificial light at night on the seafloor Type Journal Article
Year (down) 2020 Publication Scientific Reports Abbreviated Journal Sci Rep
Volume 10 Issue 1 Pages 12545
Keywords Ecology; Skyglow; Remote Sensing
Abstract Accelerating coastal development is increasing the exposure of marine ecosystems to nighttime light pollution, but is anthropogenic light reaching the seafloor in sufficient quantities to have ecological impacts? Using a combination of mapping, and radiative transfer modelling utilising in situ measurements of optical seawater properties, we quantified artificial light exposure at the sea surface, beneath the sea surface, and at the sea floor of an urbanised temperate estuary bordered by an LED lit city. Up to 76% of the three-dimensional seafloor area was exposed to biologically important light pollution. Exposure to green wavelengths was highest, while exposure to red wavelengths was nominal. We conclude that light pollution from coastal cities is likely having deleterious impacts on seafloor ecosystems which provide vital ecosystem services. A comprehensive understanding of these impacts is urgently needed.
Address Plymouth Marine Laboratory, Prospect Place, Devon, Plymouth, PL1 3DH, UK
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN 2045-2322 ISBN Medium
Area Expedition Conference
Notes PMID:32719492; PMCID:PMC7385152 Approved no
Call Number GFZ @ kyba @ Serial 3071
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Author Zhang, W.; Cui, Y.; Wang, J.; Wang, C.; Streets, D.G.
Title How does urbanization affect CO2 emissions of central heating systems in China? An assessment of natural gas transition policy based on nighttime light data Type Journal Article
Year (down) 2020 Publication Journal of Cleaner Production Abbreviated Journal Journal of Cleaner Production
Volume 276 Issue Pages 123188
Keywords Remote Sensing
Abstract Understanding the different impacts of urbanization on sectorial carbon dioxide (CO2) emissions at different spatial scales is of great importance for the evaluation of energy transition policies and reduction of environmental inequality. However, how urbanization affects the CO2 emissions of central heating systems at high spatial resolution in China has not been fully studied before. Based on satellite-observed NPP-VIIRS nighttime light (NTL) data, we develop a 5 km × 5 km annual CO2 emission inventory for coal boilers, thermal power plants (TPPs), and natural gas boilers in China’s central heating systems for the period 2012–2017 by using the geographical and temporally weighted regression (GTWR) model. It is observed that nonurban areas generated 2–4 times the CO2 emissions of coal boilers in urban areas. The largest increments of CO2 emissions of gas boilers are observed in urban areas of the eastern (6.80 times) and central regions (2.86 times) in 2013–2014, due to the clean heating policy in the “2 + 26” cities in China. The effects of urbanization on CO2 emissions from natural gas boilers are approximately 2–3 times those of coal boilers, and the differences are largest in western cities with only minor differences in northeastern cities. Our results will aid in designing low-carbon development goals and provide micro-level information on central heating facilities in urbanized and less developed regions.
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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 0959-6526 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 3072
Permanent link to this record