IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v231y2018icp1070-1078.html

Spatio-temporal simulation of energy consumption in China's provinces based on satellite night-time light data

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Du, Mengbing & Ruan, Jianhui & Zhang, Li & Niu, Muchuan & Zhang, Zhe & Xia, Lang & Qian, Shuangyue & Chen, Chuchu, 2024. "China's local-level monthly residential electricity power consumption monitoring," Applied Energy, Elsevier, vol. 359(C).
  2. 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.
  3. Luo, Yugong & Feng, Guixuan & Wan, Shuang & Zhang, Shuwei & Li, Victor & Kong, Weiwei, 2020. "Charging scheduling strategy for different electric vehicles with optimization for convenience of drivers, performance of transport system and distribution network," Energy, Elsevier, vol. 194(C).
  4. Hu, Ting & Wang, Ting & Yan, Qingyun & Chen, Tiexi & Jin, Shuanggen & Hu, Jun, 2022. "Modeling the spatiotemporal dynamics of global electric power consumption (1992–2019) by utilizing consistent nighttime light data from DMSP-OLS and NPP-VIIRS," Applied Energy, Elsevier, vol. 322(C).
  5. Wang, Jiaxin & Lu, Feng, 2021. "Modeling the electricity consumption by combining land use types and landscape patterns with nighttime light imagery," Energy, Elsevier, vol. 234(C).
  6. Kang, Jijun & Yu, Chenyang & Xue, Rui & Yang, Dong & Shan, Yuli, 2022. "Can regional integration narrow city-level energy efficiency gap in China?," Energy Policy, Elsevier, vol. 163(C).
  7. Yuanzheng Cui & Lei Jiang & Weishi Zhang & Haijun Bao & Bin Geng & Qingqing He & Long Zhang & David G. Streets, 2019. "Evaluation of China’s Environmental Pressures Based on Satellite NO 2 Observation and the Extended STIRPAT Model," IJERPH, MDPI, vol. 16(9), pages 1-16, April.
  8. Mi, Zhifu & Zheng, Jiali & Meng, Jing & Zheng, Heran & Li, Xian & Coffman, D'Maris & Woltjer, Johan & Wang, Shouyang & Guan, Dabo, 2019. "Carbon emissions of cities from a consumption-based perspective," Applied Energy, Elsevier, vol. 235(C), pages 509-518.
  9. 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.
  10. Qiao, Renlu & Liu, Xiaochang & Gao, Shuo & Liang, Diling & GesangYangji, Gesang & Xia, Li & Zhou, Shiqi & Ao, Xiang & Jiang, Qingrui & Wu, Zhiqiang, 2024. "Industrialization, urbanization, and innovation: Nonlinear drivers of carbon emissions in Chinese cities," Applied Energy, Elsevier, vol. 358(C).
  11. Tianjiao Yang & Jing Liu & Haibo Mi & Zhicheng Cao & Yiting Wang & Huichao Han & Jiahui Luan & Zhaoxuan Wang, 2022. "An Estimating Method for Carbon Emissions of China Based on Nighttime Lights Remote Sensing Satellite Images," Sustainability, MDPI, vol. 14(4), pages 1-23, February.
  12. Yunlong Zhao & Geng Kong & Chin Hao Chong & Linwei Ma & Zheng Li & Weidou Ni, 2021. "How to Effectively Control Energy Consumption Growth in China’s 29 Provinces: A Paradigm of Multi-Regional Analysis Based on EAALMDI Method," Sustainability, MDPI, vol. 13(3), pages 1-26, January.
  13. Rao, Yanchun & Wang, Xiuli & Li, Hengkai, 2024. "Forecasting electricity consumption in China's Pearl River Delta urban agglomeration under the optimal economic growth path with low-carbon goals: Based on data of NPP-VIIRS-like nighttime light," Energy, Elsevier, vol. 294(C).
  14. Liu, Qilu & Cheng, Kaiming & Zhuang, Yanjie, 2022. "Estimation of city energy consumption in China based on downscaling energy balance tables," Energy, Elsevier, vol. 256(C).
  15. Giacomo Falchetta & Michel Noussan, 2019. "Interannual Variation in Night-Time Light Radiance Predicts Changes in National Electricity Consumption Conditional on Income-Level and Region," Energies, MDPI, vol. 12(3), pages 1-20, January.
  16. Gao, Kang & Yuan, Yijun, 2022. "Spatiotemporal pattern assessment of China’s industrial green productivity and its spatial drivers: Evidence from city-level data over 2000–2017," Applied Energy, Elsevier, vol. 307(C).
  17. Naeher,Dominik & Narayanan,Raghavan & Ziulu,Virginia, 2021. "Impacts of Energy Efficiency Projects in Developing Countries : Evidence from a SpatialDifference-in-Differences Analysis in Malawi," Policy Research Working Paper Series 9842, The World Bank.
  18. Yang Zhong & Aiwen Lin & Zhigao Zhou & Feiyan Chen, 2018. "Spatial Pattern Evolution and Optimization of Urban System in the Yangtze River Economic Belt, China, Based on DMSP-OLS Night Light Data," Sustainability, MDPI, vol. 10(10), pages 1-14, October.
  19. Wang, Rongji & Zhang, Yan & Wan, Wei & Bai, Dongbei & Wang, Jue, 2025. "Circular city construction and energy efficiency: Evidence from China’s ‘circular economy demonstration cities’," Economic Analysis and Policy, Elsevier, vol. 88(C), pages 817-844.
  20. Wang, Shaobin & Liu, Haimeng & Pu, Haixia & Yang, Hao, 2020. "Spatial disparity and hierarchical cluster analysis of final energy consumption in China," Energy, Elsevier, vol. 197(C).
  21. Chen Xu & Zhenzhen Yin & Wei Sun & Zhi Cao & Mingyang Cheng, 2024. "The Urban–Rural Transformation and Its Influencing Mechanisms on Air Pollution in the Yellow River Basin," Sustainability, MDPI, vol. 16(16), pages 1-23, August.
  22. Guibor Camargo & Andrés Miguel Sampayo & Andrés Peña Galindo & Francisco J Escobedo & Fernando Carriazo & Alejandro Feged-Rivadeneira, 2020. "Exploring the dynamics of migration, armed conflict, urbanization, and anthropogenic change in Colombia," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-18, November.
  23. Zhao, Kai & Shi, Kaihe & Wu, Lifeng, 2025. "Spatiotemporal grey evolution in the dual control of the energy consumption," Energy, Elsevier, vol. 340(C).
  24. Haize Pan & Chuan Yang & Lirong Quan & Longhui Liao, 2021. "A New Insight into Understanding Urban Vitality: A Case Study in the Chengdu-Chongqing Area Twin-City Economic Circle, China," Sustainability, MDPI, vol. 13(18), pages 1-19, September.
  25. Lu, Wenlu & Zhang, Da & He, Chunyang & Zhang, Xiwen, 2024. "Modeling the spatiotemporal dynamics of electric power consumption in China from 2000 to 2020 based on multisource remote sensing data and machine learning," Energy, Elsevier, vol. 308(C).
  26. Gao, Ming & Ma, Ke & Yu, Jie, 2023. "The characteristics and drivers of China’s city-level urban-rural activity sectors’ carbon intensity gap during urban land expansion," Energy Policy, Elsevier, vol. 181(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.