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Author Li, K.; Chen, Y. url  doi
openurl 
  Title A Genetic Algorithm-Based Urban Cluster Automatic Threshold Method by Combining VIIRS DNB, NDVI, and NDBI to Monitor Urbanization Type Journal Article
  Year 2018 Publication Remote Sensing Abbreviated Journal Remote Sensing  
  Volume 10 Issue 2 Pages 277  
  Keywords Remote Sensing  
  Abstract Accurate and timely information related to quantitative descriptions and spatial distributions of urban areas is crucial to understand urbanization dynamics and is also helpful to address environmental issues associated with rapid urban land-cover changes. Thresholding is acknowledged as the most popular and practical way to extract urban information from nighttime lights. However, the difficulty of determining optimal threshold remains challenging to applications of this method. In order to address the problem of selecting thresholds, a Genetic Algorithm-based urban cluster automatic threshold (GA-UCAT) method by combining Visible-Infrared Imager-Radiometer Suite Day/Night band (VIIRS DNB), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Built-up Index (NDBI) is proposed to distinguish urban areas from dark rural background in NTL images. The key point of this proposed method is to design an appropriate fitness function of GA by means of integrating between-class variance and inter-class variance with all these three data sources to determine optimal thresholds. In accuracy assessments by comparing with ground truth—Landsat 8 OLI images, this new method has been validated and results with OA (Overall Accuracy) ranging from 0.854 to 0.913 and Kappa ranging from 0.699 to 0.722 show that the GA-UCAT approach is capable of describing spatial distributions and giving detailed information of urban extents. Additionally, there is discussion on different classifications of rural residential spots in Landsat remote sensing images and nighttime light (NTL) and evaluations of spatial-temporal development patterns of five selected Chinese urban clusters from 2012 to 2017 on utilizing this proposed method. The new method shows great potential to map global urban information in a simple and accurate way and to help address urban environmental issues.  
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  ISSN (down) 2072-4292 ISBN Medium  
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  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2340  
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Author Ma, W.; Li, P. url  doi
openurl 
  Title An Object Similarity-Based Thresholding Method for Urban Area Mapping from Visible Infrared Imaging Radiometer Suite Day/Night Band (VIIRS DNB) Data Type Journal Article
  Year 2018 Publication Remote Sensing Abbreviated Journal Remote Sensing  
  Volume 10 Issue 2 Pages 263  
  Keywords Remote Sensing  
  Abstract Nighttime light data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) provides a unique data source for mapping and monitoring urban areas at regional and global scales. This study proposes an object similarity-based thresholding method using VIIRS DNB data to map urban areas. The threshold for a target potential urban object was determined by comparing its similarity with all reference urban objects with known optimal thresholds derived from Landsat data. The proposed method includes four major steps: potential urban object generation, threshold optimization for reference urban objects, object similarity comparison, and urban area mapping. The proposed method was evaluated using VIIRS DNB data of China and compared with existing mapping methods in terms of threshold estimation and urban area mapping. The results indicated that the proposed method estimated thresholds and mapped urban areas accurately and generally performed better than the cluster-based logistic regression method. The correlation coefficients between the estimated thresholds and the reference thresholds were 0.9201–0.9409 (using Euclidean distance as similarity measure) and 0.9461–0.9523 (using Mahalanobis distance as similarity measure) for the proposed method and 0.9435–0.9503 for the logistic regression method. The average Kappa Coefficients of the urban area maps were 0.58 (Euclidean distance) and 0.57 (Mahalanobis distance) for the proposed method and 0.51 for the logistic regression method. The proposed method shows potential to map urban areas at a regional scale effectively in an economic and convenient way.  
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  ISSN (down) 2072-4292 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2341  
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Author Chen, Shanshan; Hu, Deyong url  doi
openurl 
  Title Parameterizing Anthropogenic Heat Flux with an Energy-Consumption Inventory and Multi-Source Remote Sensing Data Type Journal Article
  Year 2017 Publication Remote Sensing Abbreviated Journal Remote Sensing  
  Volume 9 Issue 11 Pages 1165  
  Keywords Remote Sensing  
  Abstract Anthropogenic heat (AH) generated by human activities is an important factor affecting the urban climate. Thus, refined AH parameterization of a large area can provide data support for regional meteorological research. In this study, we developed a refined anthropogenic heat flux (RAHF) parameterization scheme to estimate the gridded anthropogenic heat flux (AHF). Firstly, the annual total AH emissions and annual mean AHF of Beijing municipality in the year 2015 were estimated using a top-down, energy-consumption inventory method, which was derived based on socioeconomic statistics and energy consumption data. The heat released from industry, transportation, buildings (including both commercial and residential buildings), and human metabolism were taken into account. Then, the county-scale AHF estimation model was constructed based on multi-source remote sensing data, such as Suomi national polar-orbiting partnership (Suomi-NPP) visible infrared imaging radiometer suite (VIIRS) nighttime light (NTL) data and moderate resolution imaging spectroradiometer (MODIS) data. This model was applied to estimate the annual mean AHF of the counties in the Beijing–Tianjin–Hebei region. Finally, the gridded AHF data with 500-m resolution was obtained using a RAHF parameterization scheme. The results indicate that the annual total AH emissions of Beijing municipality in the year 2015 was approximately 1.704 × 1018 J. Of this, the buildings contribute about 34.5%, followed by transportation and industry with about 30.5% and 30.1%, respectively, and human metabolism with only about 4.9%. The annual mean AHF value of the Beijing–Tianjin–Hebei region is about 6.07 W·m−2, and the AHF in urban areas is about in the range of 20 W·m−2 and 130 W·m−2. The maximum AHF value is approximately 130.84 W·m−2, mostly in airports, railway stations, central business districts, and other densely-populated areas. The error analysis of the county-scale AHF results showed that the residual between the model estimation and energy consumption statistics is less than 1%. In addition, the spatial distribution of RAHF results is generally centered on urban area and gradually decreases towards suburbs. The spatial pattern of the RAHF results within urban areas corresponds well to the distribution of population density, building density, and the industrial district. The spatial heterogeneity of AHF within urban areas is well-reflected through the RAHF results. The RAHF results can be used in meteorological and environmental modeling for the Beijing–Tianjin–Hebei region. The results of this study also highlight the superiority of Suomi-NPP VIIRS NTL data for AHF estimation.  
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  ISSN (down) 2072-4292 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2342  
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Author Jiang, W.; He, G.; Long, T.; Wang, C.; Ni, Y.; Ma, R. url  doi
openurl 
  Title Assessing Light Pollution in China Based on Nighttime Light Imagery Type Journal Article
  Year 2017 Publication Remote Sensing Abbreviated Journal Remote Sensing  
  Volume 9 Issue 2 Pages 135  
  Keywords Remote Sensing  
  Abstract Rapid urbanization and economic development inevitably lead to light pollution, which has become a universal environmental issue. In order to reveal the spatiotemporal patterns and evolvement rules of light pollution in China, images from 1992 to 2012 were selected from the Defense Meteorological Satellite Program Operational Linescan System (DMSP/OLS) and systematically corrected to ensure consistency. Furthermore, we employed a linear regression trend method and nighttime light index method to demonstrate China’s light pollution characteristics across national, regional, and provincial scales, respectively. We found that: (1) China’s light pollution expanded significantly in provincial capital cities over the past 21 years and hot-spots of light pollution were located in the eastern coastal region. The Yangtze River Delta, Pearl River Delta, and Beijing–Tianjin–Hebei regions have formed light pollution stretch areas; (2) China’s light pollution was mainly focused in areas of north China (NC) and east China (EC), which, together, accounted for over 50% of the light pollution for the whole country. The fastest growth of light pollution was observed in northwest China (NWC), followed by southwest China (SWC). The growth rates of east China (EC), central China (CC), and northeast China (NEC) were stable, while those of north China (NC) and south China (SC) declined; (3) Light pollution at the provincial scale was mainly located in the Shandong, Guangdong, and Hebei provinces, whereas the fastest growth of light pollution was in Tibet and Hainan. However, light pollution levels in the developed provinces (Hong Kong, Macao, Shanghai, and Tianjin) were higher than those of the undeveloped provinces. Similarly, the light pollution heterogeneities of Taiwan, Beijing, and Shanghai were higher than those of undeveloped western provinces.  
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  ISSN (down) 2072-4292 ISBN Medium  
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  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2442  
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Author Huang, Q.; Yang, X.; Gao, B.; Yang, Y.; Zhao, Y. url  doi
openurl 
  Title Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review Type Journal Article
  Year 2014 Publication Remote Sensing Abbreviated Journal Remote Sensing  
  Volume 6 Issue 8 Pages 6844-6866  
  Keywords Remote Sensing  
  Abstract Since the release of the digital archives of Defense Meteorological Satellite Program Operational Line Scanner (DMSP/OLS) nighttime light data in 1992, a variety of datasets based on this database have been produced and applied to monitor and analyze human activities and natural phenomena. However, differences among these datasets and how they have been applied may potentially confuse researchers working with these data. In this paper, we review the ways in which data from DMSP/OLS nighttime light images have been applied over the past two decades, focusing on differences in data processing, research trends, and the methods used among the different application areas. Five main datasets extracted from this database have led to many studies in various research areas over the last 20 years, and each dataset has its own strengths and limitations. The number of publications based on this database and the diversity of authors and institutions involved have shown promising growth. In addition, researchers have accumulated vast experience retrieving data on the spatial and temporal dynamics of settlement, demographics, and socioeconomic parameters, which are “hotspot” applications in this field. Researchers continue to develop novel ways to extract more information from the DMSP/OLS database and apply the data to interdisciplinary research topics. We believe that DMSP/OLS nighttime light data will play an important role in monitoring and analyzing human activities and natural phenomena from space in the future, particularly over the long term. A transparent platform that encourages data sharing, communication, and discussion of extraction methods and synthesis activities will benefit researchers as well as public and political stakeholders.  
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  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 2482  
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