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Estimating CO2 (carbon dioxide) emissions at urban scales by DMSP/OLS (Defense Meteorological Satellite Program's Operational Linescan System) nighttime light imagery: Methodological challenges and a case study for China

Citations

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Cited by:

  1. Zhao, Jincai & Ji, Guangxing & Yue, YanLin & Lai, Zhizhu & Chen, Yulong & Yang, Dongyang & Yang, Xu & Wang, Zheng, 2019. "Spatio-temporal dynamics of urban residential CO2 emissions and their driving forces in China using the integrated two nighttime light datasets," Applied Energy, Elsevier, vol. 235(C), pages 612-624.
  2. Yun Tong & Rui Zhang & Biao He, 2022. "The Carbon Emission Reduction Effect of Tourism Economy and Its Formation Mechanism: An Empirical Study of China’s 92 Tourism-Dependent Cities," IJERPH, MDPI, vol. 19(3), pages 1-21, February.
  3. Yang, Di & Luan, Weixin & Qiao, Lu & Pratama, Mahardhika, 2020. "Modeling and spatio-temporal analysis of city-level carbon emissions based on nighttime light satellite imagery," Applied Energy, Elsevier, vol. 268(C).
  4. Jianghua Liu & Mengxu Li & Yitao Ding, 2021. "Econometric analysis of the impact of the urban population size on carbon dioxide (CO2) emissions in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(12), pages 18186-18203, December.
  5. Xiao, Hongwei & Ma, Zhongyu & Mi, Zhifu & Kelsey, John & Zheng, Jiali & Yin, Weihua & Yan, Min, 2018. "Spatio-temporal simulation of energy consumption in China's provinces based on satellite night-time light data," Applied Energy, Elsevier, vol. 231(C), pages 1070-1078.
  6. Xuemei Wang & Mingguo Ma, 2017. "The luminous intensity of regional ‘night-light’ output can predict the growing volume of published scientific research by ‘luminaries’ in developing countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 1005-1010, February.
  7. Cui, Yuanzheng & Zhang, Weishi & Wang, Can & Streets, David G. & Xu, Ying & Du, Mingxi & Lin, Jintai, 2019. "Spatiotemporal dynamics of CO2 emissions from central heating supply in the North China Plain over 2012–2016 due to natural gas usage," Applied Energy, Elsevier, vol. 241(C), pages 245-256.
  8. Yongguang Zhu & Deyi Xu & Saleem H. Ali & Ruiyang Ma & Jinhua Cheng, 2019. "Can Nighttime Light Data Be Used to Estimate Electric Power Consumption? New Evidence from Causal-Effect Inference," Energies, MDPI, vol. 12(16), pages 1-14, August.
  9. Chen, Qianli & Cai, Bofeng & Dhakal, Shobhakar & Pei, Sha & Liu, Chunlan & Shi, Xiaoping & Hu, Fangfang, 2017. "CO2 emission data for Chinese cities," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 198-208.
  10. Minghai Luo & Sixian Qin & Haoxue Chang & Anqi Zhang, 2019. "Disaggregation Method of Carbon Emission: A Case Study in Wuhan, China," Sustainability, MDPI, vol. 11(7), pages 1-17, April.
  11. Shi, Kaifang & Chen, Yun & Li, Linyi & Huang, Chang, 2018. "Spatiotemporal variations of urban CO2 emissions in China: A multiscale perspective," Applied Energy, Elsevier, vol. 211(C), pages 218-229.
  12. Michail Fragkias & José Lobo & Karen C Seto, 2017. "A comparison of nighttime lights data for urban energy research: Insights from scaling analysis in the US system of cities," Environment and Planning B, , vol. 44(6), pages 1077-1096, November.
  13. Gang Xu & Tianyi Zeng & Hong Jin & Cong Xu & Ziqi Zhang, 2023. "Spatio-Temporal Variations and Influencing Factors of Country-Level Carbon Emissions for Northeast China Based on VIIRS Nighttime Lighting Data," IJERPH, MDPI, vol. 20(1), pages 1-17, January.
  14. Fang, Guochang & Gao, Zhengye & Tian, Lixin & Fu, Min, 2022. "What drives urban carbon emission efficiency? – Spatial analysis based on nighttime light data," Applied Energy, Elsevier, vol. 312(C).
  15. Hu, Ting & Huang, Xin, 2019. "A novel locally adaptive method for modeling the spatiotemporal dynamics of global electric power consumption based on DMSP-OLS nighttime stable light data," Applied Energy, Elsevier, vol. 240(C), pages 778-792.
  16. Shi, Kaifang & Yang, Qingyuan & Fang, Guangliang & Yu, Bailang & Chen, Zuoqi & Yang, Chengshu & Wu, Jianping, 2019. "Evaluating spatiotemporal patterns of urban electricity consumption within different spatial boundaries: A case study of Chongqing, China," Energy, Elsevier, vol. 167(C), pages 641-653.
  17. Shi, Kaifang & Yu, Bailang & Zhou, Yuyu & Chen, Yun & Yang, Chengshu & Chen, Zuoqi & Wu, Jianping, 2019. "Spatiotemporal variations of CO2 emissions and their impact factors in China: A comparative analysis between the provincial and prefectural levels," Applied Energy, Elsevier, vol. 233, pages 170-181.
  18. Kacprzyk, Andrzej & Kuchta, Zbigniew, 2020. "Shining a new light on the environmental Kuznets curve for CO2 emissions," Energy Economics, Elsevier, vol. 87(C).
  19. Yingli Lou & Liyin Shen & Zhenhua Huang & Ya Wu & Heng Li & Guijun Li, 2018. "Does the Effort Meet the Challenge in Promoting Low-Carbon City?—A Perspective of Global Practice," IJERPH, MDPI, vol. 15(7), pages 1-21, June.
  20. Yajing Liu & Shuai Zhou & Ge Zhang, 2023. "Spatio-Temporal Dynamics and Driving Forces of Multi-Scale Emissions Based on Nighttime Light Data: A Case Study of the Pearl River Delta Urban Agglomeration," Sustainability, MDPI, vol. 15(10), pages 1-24, May.
  21. Wang, Ailun & Hu, Shuo & Li, Jianglong, 2021. "Does economic development help achieve the goals of environmental regulation? Evidence from partially linear functional-coefficient model," Energy Economics, Elsevier, vol. 103(C).
  22. Mladenović, Igor & Sokolov-Mladenović, Svetlana & Milovančević, Milos & Marković, Dušan & Simeunović, Nenad, 2016. "Management and estimation of thermal comfort, carbon dioxide emission and economic growth by support vector machine," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 466-476.
  23. Shengyun Wang & Liancheng Duan & Qin Zhu & Yaxin Zhang, 2022. "Spatial Differences of Ecological Well-Being Performance in the Poyang Lake Area at the Local Level," IJERPH, MDPI, vol. 19(18), pages 1-19, September.
  24. Shi, Kaifang & Chen, Yun & Yu, Bailang & Xu, Tingbao & Chen, Zuoqi & Liu, Rui & Li, Linyi & Wu, Jianping, 2016. "Modeling spatiotemporal CO2 (carbon dioxide) emission dynamics in China from DMSP-OLS nighttime stable light data using panel data analysis," Applied Energy, Elsevier, vol. 168(C), pages 523-533.
  25. Xie, Yanhua & Weng, Qihao, 2016. "Detecting urban-scale dynamics of electricity consumption at Chinese cities using time-series DMSP-OLS (Defense Meteorological Satellite Program-Operational Linescan System) nighttime light imageries," Energy, Elsevier, vol. 100(C), pages 177-189.
  26. Shi, Kaifang & Chen, Yun & Yu, Bailang & Xu, Tingbao & Yang, Chengshu & Li, Linyi & Huang, Chang & Chen, Zuoqi & Liu, Rui & Wu, Jianping, 2016. "Detecting spatiotemporal dynamics of global electric power consumption using DMSP-OLS nighttime stable light data," Applied Energy, Elsevier, vol. 184(C), pages 450-463.
  27. Wang, Kunlun & Zheng, Leven J. & Zhang, Justin Zuopeng & Yao, Hongjiang, 2022. "The impact of promoting new energy vehicles on carbon intensity: Causal evidence from China," Energy Economics, Elsevier, vol. 114(C).
  28. Lina Meng & Bo Huang, 2018. "Shaping the Relationship Between Economic Development and Carbon Dioxide Emissions at the Local Level: Evidence from Spatial Econometric Models," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(1), pages 127-156, September.
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