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Author Sun, Y.; Wang, S.; Wang, Y.
Title Estimating local-scale urban heat island intensity using nighttime light satellite imageries Type Journal Article
Year 2020 Publication Sustainable Cities and Society Abbreviated Journal Sustainable Cities and Society
Volume 57 Issue Pages in press
Keywords Remote Sensing
Abstract (down) Urban heat island (UHI) effect tends to harm health, increase anthropogenic energy consumption, and water consumption. Some policies targeting UHI mitigation have been implemented for a few years and thus needs to be evaluated for changes or modifications in the future. A low-cost approach to rapidly monitoring UHI intensity variations can assist in evaluating policy implementations. In this study, we proposed a new approach to local-scale UHI intensity estimates by using nighttime light satellite imageries. We explored to what extent UHI intensity could be estimated according to nighttime light intensity at two local scales. We attempted to estimate district-level and neighbourhood-level UHI intensity across London and Paris. As the geography level rises from district to neighbourhood, the capacity of the models explaining the variations of the UHI intensity decreases. Although the possible presence of residual spatial autocorrelation in the conventional regression models applied to geospatial data, most of the studies are likely to neglect this issue when fitting data to models. To remove negative effects of the residual spatial autocorrelation, this study used spatial regression models instead of non-spatial regression models (e.g., OLS models) to estimate UHI intensity. As a result, district-level UHI intensity was successfully estimated according to nighttime light intensity (approximately R2 = 0.7, MAE =1.16 °C, and RMSE =1.74 °C).
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 2210-6707 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2849
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Author Yao, Y.; Chen, D.; Chen, L.; Wang, H.; Guan, Q.
Title A time series of urban extent in China using DSMP/OLS nighttime light data Type Journal Article
Year 2018 Publication PloS one Abbreviated Journal PLoS One
Volume 13 Issue 5 Pages e0198189
Keywords Remote Sensing
Abstract (down) Urban extent data play an important role in urban management and urban studies, such as monitoring the process of urbanization and changes in the spatial configuration of urban areas. Traditional methods of extracting urban-extent information are primarily based on manual investigations and classifications using remote sensing images, and these methods have such problems as large costs in labor and time and low precision. This study proposes an improved, simplified and flexible method for extracting urban extents over multiple scales and the construction of spatiotemporal models using DMSP/OLS nighttime light (NTL) for practical situations. This method eliminates the regional temporal and spatial inconsistency of thresholding NTL in large-scale and multi-temporal scenes. Using this method, we have extracted the urban extents and calculated the corresponding areas on the county, municipal and provincial scales in China from 2000 to 2012. In addition, validation with the data of reference data shows that the overall accuracy (OA), Kappa and F1 Scores were 0.996, 0.793, and 0.782, respectively. We increased the spatial resolution of the urban extent to 500 m (approximately four times finer than the results of previous studies). Based on the urban extent dataset proposed above, we analyzed changes in urban extents over time and observed that urban sprawl has grown in all of the counties of China. We also identified three patterns of urban sprawl: Early Urban Growth, Constant Urban Growth and Recent Urban Growth. In addition, these trends of urban sprawl are consistent with the western, eastern and central cities of China, respectively, in terms of their spatial distribution, socioeconomic characteristics and historical background. Additionally, the urban extents display the spatial configurations of urban areas intuitively. The proposed urban extent dataset is available for download and can provide reference data and support for future studies of urbanization and urban planning.
Address School of Information Engineering, China University of Geosciences, Wuhan, Hubei province, China
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1932-6203 ISBN Medium
Area Expedition Conference
Notes PMID:29795685 Approved no
Call Number GFZ @ kyba @ Serial 1924
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Author Ratnasari, N.; Candra, E.D.; Saputra, D.H.; Perdana, A.P.
Title Urban Spatial Pattern and Interaction based on Analysis of Nighttime Remote Sensing Data and Geo-social Media Information Type Journal Article
Year 2016 Publication IOP Conference Series: Earth and Environmental Science Abbreviated Journal IOP Conf. Ser.: Earth Environ. Sci.
Volume 47 Issue Pages 012038
Keywords remote sensing; geo-social media; spatial pattern; spatial interaction; urban; Indonesia
Abstract (down) Urban development in Indonesia significantly increasing in line with rapid development of infrastructure, utility, and transportation network. Recently, people live depend on lights at night and social media and these two aspects can depicted urban spatial pattern and interaction. This research used nighttime remote sensing data with the VIIRS (Visible Infrared Imaging Radiometer Suite) day-night band detects lights, gas flares, auroras, and wildfires. Geo-social media information derived from twitter data gave big picture on spatial interaction from the geospatial footprint. Combined both data produced comprehensive urban spatial pattern and interaction in general for Indonesian territory. The result is shown as a preliminary study of integrating nighttime remote sensing data and geospatial footprint from twitter data.
Address Undergraduate Program of Cartography and Remote Sensing, Department of Geographic Information Science, Faculty of Geography, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia; nila.ratnasari(at)mail.ugm.ac.id
Corporate Author Thesis
Publisher IOP Place of Publication Editor
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1755-1307 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number IDA @ john @ Serial 1653
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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 (down) 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.
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 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2870
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Author Liu, Y.; Zhang, X.; Pan, X.; Ma, X.; Tang, M.
Title The spatial integration and coordinated industrial development of urban agglomerations in the Yangtze River Economic Belt, China Type Journal Article
Year 2020 Publication Cities Abbreviated Journal Cities
Volume 104 Issue Pages 102801
Keywords Remote Sensing
Abstract (down) Urban agglomeration is the engine of national development and regional prosperity. Although extensive work has investigated issues related to this new form of spatial governance, few studies have directly illustrated the spatial integration of urban agglomeration and its relationship with industrial development. This paper employs nighttime light data and industrial enterprise datasets to investigate the spatial integration and industrial development in the Yangtze River Economic Belt (YREB) of China for 1995–2015. We here illustrate the significant relationship between the spatial integration of urban agglomerations and the characteristics of industrial development. In the process of spatial integration, urban form, intercity relation and their evolution show clear regional differences. Because of the differences in socio-economic and geographical characteristics, urban systems are more advanced and closely related in developed areas. A significant negative (positive) spatial correlation between industrial specialization (diversification) and urban form is supported by using bivariate Moran's I, and spatial clustering patterns are clearly different across the three urban agglomerations. A panel regression reveals that intercity relations are significantly associated with the characteristics of industrial development. Higher levels of industrial diversification and competition are associated with weaker intercity relations, while industrial structures similarities are reversed. These findings could be used to formulate reasonable policies and plans and to support future regional spatial integration and coordinated development.
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 0264-2751 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2986
Permanent link to this record