Search Results - "Li, Qiaoxuan"

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  1. 1

    Estimation of Poverty Using Random Forest Regression with Multi-Source Data: A Case Study in Bangladesh by Zhao, Xizhi, Yu, Bailang, Liu, Yan, Chen, Zuoqi, Li, Qiaoxuan, Wang, Congxiao, Wu, Jianping

    Published in Remote sensing (Basel, Switzerland) (01-02-2019)
    “…Spatially explicit and reliable data on poverty is critical for both policy makers and researchers. However, such data remain scarce particularly in developing…”
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    Journal Article
  2. 2

    Combining ICESat-2 photons and Google Earth Satellite images for building height extraction by Zhao, Yi, Wu, Bin, Li, Qiaoxuan, Yang, Lei, Fan, Hongchao, Wu, Jianping, Yu, Bailang

    “…•A method for building height estimation by combining two datasets is proposed.•Building shadows are extracted from one dataset, Google Earth Satellite…”
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    Journal Article
  3. 3
  4. 4

    Automated Extraction of Street Lights From JL1-3B Nighttime Light Data and Assessment of Their Solar Energy Potential by Cheng, Bin, Chen, Zuoqi, Yu, Bailang, Li, Qiaoxuan, Wang, Congxiao, Li, Beibei, Wu, Bin, Li, Yong, Wu, Jianping

    “…To realize energy conservation and environmental protection, solar street lights have been widely used in urban areas in China. To reasonably and effectively…”
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    Journal Article
  5. 5

    Enhancing nighttime light remote Sensing: Introducing the nighttime light background value (NLBV) for urban applications by Liu, Shaoyang, Wang, Congxiao, Chen, Zuoqi, Li, Qiaoxuan, Wu, Qiusheng, Li, Yangguang, Wu, Jianping, Yu, Bailang

    “…•Nighttime Light Background Value (NLBV) was proposed to represent the NTL from urban lighting facilities.•The NLBV exhibited a stronger correlation with both…”
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    Journal Article
  6. 6

    The Relationship Between Urban 2-D/3-D Landscape Pattern and Nighttime Light Intensity by Wu, Bin, Yang, Chengshu, Chen, Zuoqi, Wu, Qiusheng, Yu, Siyi, Wang, Congxiao, Li, Qiaoxuan, Wu, Jianping, Yu, Bailang

    “…As spatial and socioeconomic processes are the two key aspects of urban development, revealing the relationship between these two key aspects is critical…”
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    Journal Article
  7. 7

    A New Method for Building-Level Population Estimation by Integrating LiDAR, Nighttime Light, and POI Data by Chen, Hongxing, Wu, Bin, Yu, Bailang, Chen, Zuoqi, Wu, Qiusheng, Lian, Ting, Wang, Congxiao, Li, Qiaoxuan, Wu, Jianping

    Published in Journal of remote sensing (01-01-2021)
    “…Building-level population data are of vital importance in disaster management, homeland security, and public health. Remotely sensed data, especially LiDAR…”
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    Journal Article
  8. 8

    Big Geodata Reveals Spatial Patterns of Built Environment Stocks Across and Within Cities in China by Huang, Zhou, Bao, Yi, Mao, Ruichang, Wang, Han, Yin, Ganmin, Wan, Lin, Qi, Houji, Li, Qiaoxuan, Tang, Hongzhao, Liu, Qiance, Li, Linna, Yu, Bailang, Guo, Qinghua, Liu, Yu, Guo, Huadong, Liu, Gang

    Published in Engineering (Beijing, China) (01-03-2024)
    “…The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important, yet hitherto largely missing stock…”
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    Journal Article
  9. 9

    Spatiotemporally Explicit Mapping of Built Environment Stocks Reveals Two Centuries of Urban Development in a Fairytale City, Odense, Denmark by Li, Qiaoxuan, Gummidi, Srinivasa Raghavendra Bhuvan, Lanau, Maud, Yu, Bailang, Liu, Gang

    Published in Environmental science & technology (15-11-2022)
    “…The urban built environment stocks such as buildings and infrastructure provide essential services to urban residents, and their spatiotemporal dynamics are…”
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    Journal Article
  10. 10

    Spatiotemporal responses of dengue fever transmission to the road network in an urban area by Li, Qiaoxuan, Cao, Wei, Ren, Hongyan, Ji, Zhonglin, Jiang, Huixian

    Published in Acta tropica (01-07-2018)
    “…•A critical area of dengue fever spreads during epidemic outbreak was observed.•Most dengue cases were distributed within about 500 m near narrow…”
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  11. 11

    Exploring Determinants of Spatial Variations in the Dengue Fever Epidemic Using Geographically Weighted Regression Model: A Case Study in the Joint Guangzhou-Foshan Area, China, 2014 by Ren, Hongyan, Zheng, Lan, Li, Qiaoxuan, Yuan, Wu, Lu, Liang

    “…Dengue fever (DF) is a common and rapidly spreading vector-borne viral disease in tropical and subtropical regions. In recent years, this imported disease has…”
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    Journal Article
  12. 12

    Ecological Niche Modeling Identifies Fine-Scale Areas at High Risk of Dengue Fever in the Pearl River Delta, China by Li, Qiaoxuan, Ren, Hongyan, Zheng, Lan, Cao, Wei, Zhang, An, Zhuang, Dafang, Lu, Liang, Jiang, Huixian

    “…Dengue fever (DF) is one of the most common and rapidly spreading mosquito-borne viral diseases in tropical and subtropical regions. In recent years, this…”
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    Journal Article
  13. 13

    The Relationship Between Urban 2-D/3-D Landscape Pattern and Nighttime Light Intensity by Wu, Bin, Yang, Chengshu, Chen, Zuoqi, Wu, Qiusheng, Yu, Siyi, Wang, Congxiao, Li, Qiaoxuan, Wu, Jianping, Yu, Bailang

    “…As spatial and socioeconomic processes are the two key aspects of urban development, revealing the relationship between these two key aspects is critical…”
    Get full text
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