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Development of an Environment and energy Geographical Information System (E-GIS) construction model to support environmentally friendly urban planning

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  • Yeo, In-Ae
  • Yoon, Seong-Hwan
  • Yee, Jurng-Jae

Abstract

This study proposes a method to create an urban planning support model, applying the Environment and energy Geographical Information System Database (E-GIS DB) through the urban life cycle to reduce energy use for environmentally friendly urban planning. The results deduced from this study are organized as follows.

Suggested Citation

  • Yeo, In-Ae & Yoon, Seong-Hwan & Yee, Jurng-Jae, 2013. "Development of an Environment and energy Geographical Information System (E-GIS) construction model to support environmentally friendly urban planning," Applied Energy, Elsevier, vol. 104(C), pages 723-739.
    • Handle: RePEc:eee:appene:v:104:y:2013:i:c:p:723-739
    DOI: 10.1016/j.apenergy.2012.11.053
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    Cited by:

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    5. Franco, Camilo & Bojesen, Mikkel & Hougaard, Jens Leth & Nielsen, Kurt, 2015. "A fuzzy approach to a multiple criteria and Geographical Information System for decision support on suitable locations for biogas plants," Applied Energy, Elsevier, vol. 140(C), pages 304-315.
    6. Shad, Rouzbeh & Khorrami, Mohammad & Ghaemi, Marjan, 2017. "Developing an Iranian green building assessment tool using decision making methods and geographical information system: Case study in Mashhad city," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 324-340.
    7. Guan, Panbo & Huang, Guohe & Wu, Chuanbao & Wang, Linrui & Li, Chaoci & Wang, Yuanyi, 2019. "Analysis of emission taxes levying on regional electric power structure adjustment with an inexact optimization model - A case study of Zibo, China," Energy Economics, Elsevier, vol. 84(C).
    8. Hyunkyo Yu & Erik O. Ahlgren, 2023. "Enhancing Urban Heating Systems Planning through Spatially Explicit Participatory Modeling," Energies, MDPI, vol. 16(11), pages 1-26, May.
    9. Santagata, R. & Ripa, M. & Ulgiati, S., 2017. "An environmental assessment of electricity production from slaughterhouse residues. Linking urban, industrial and waste management systems," Applied Energy, Elsevier, vol. 186(P2), pages 175-188.
    10. Johansson, Tim & Olofsson, Thomas & Mangold, Mikael, 2017. "Development of an energy atlas for renovation of the multifamily building stock in Sweden," Applied Energy, Elsevier, vol. 203(C), pages 723-736.
    11. Yeo, In-Ae & Yee, Jurng-Jae, 2014. "A proposal for a site location planning model of environmentally friendly urban energy supply plants using an environment and energy geographical information system (E-GIS) database (DB) and an artifi," Applied Energy, Elsevier, vol. 119(C), pages 99-117.
    12. Sikder, Sujit Kumar & Nagarajan, Magesh & Mustafee, Navonil, 2023. "Augmenting EV charging infrastructure towards transformative sustainable cities: An equity-based approach," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    13. Xie, Y.L. & Huang, G.H. & Li, W. & Ji, L., 2014. "Carbon and air pollutants constrained energy planning for clean power generation with a robust optimization model—A case study of Jining City, China," Applied Energy, Elsevier, vol. 136(C), pages 150-167.
    14. Zhang, Chen & Li, Zhixin & Jiang, Haihua & Luo, Yongqiang & Xu, Shen, 2021. "Deep learning method for evaluating photovoltaic potential of urban land-use: A case study of Wuhan, China," Applied Energy, Elsevier, vol. 283(C).
    15. Kazutoshi Tsuda & Michinori Uwasu & Keishiro Hara & Yukari Fuchigami, 2017. "Approaches to induce behavioral changes with respect to electricity consumption," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 7(1), pages 30-38, March.
    16. Ma, Weiwu & Fang, Song & Liu, Gang & Zhou, Ruoyu, 2017. "Modeling of district load forecasting for distributed energy system," Applied Energy, Elsevier, vol. 204(C), pages 181-205.
    17. Sujit Kumar Sikder & Francis Eanes & Henok Birhanu Asmelash & Shiba Kar & Theo Koetter, 2016. "The Contribution of Energy-Optimized Urban Planning to Efficient Resource Use–A Case Study on Residential Settlement Development in Dhaka City, Bangladesh," Sustainability, MDPI, vol. 8(2), pages 1-19, February.
    18. Huang, Zishuo & Yu, Hang & Peng, Zhenwei & Zhao, Mei, 2015. "Methods and tools for community energy planning: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 1335-1348.
    19. Ji, L. & Niu, D.X. & Huang, G.H., 2014. "An inexact two-stage stochastic robust programming for residential micro-grid management-based on random demand," Energy, Elsevier, vol. 67(C), pages 186-199.
    20. Chen, Shaoqing & Chen, Bin, 2015. "Urban energy consumption: Different insights from energy flow analysis, input–output analysis and ecological network analysis," Applied Energy, Elsevier, vol. 138(C), pages 99-107.
    21. Yeo, In-Ae & Lee, Eunok, 2018. "Quantitative study on environment and energy information for land use planning scenarios in eco-city planning stage," Applied Energy, Elsevier, vol. 230(C), pages 889-911.
    22. Chen, Han & Chen, Wenying, 2019. "Potential impact of shifting coal to gas and electricity for building sectors in 28 major northern cities of China," Applied Energy, Elsevier, vol. 236(C), pages 1049-1061.
    23. Yeo, In-Ae & Yoon, Seong-Hwan & Yee, Jurng-Jae, 2013. "Development of an urban energy demand forecasting system to support environmentally friendly urban planning," Applied Energy, Elsevier, vol. 110(C), pages 304-317.
    24. Bonati, A. & De Luca, G. & Fabozzi, S. & Massarotti, N. & Vanoli, L., 2019. "The integration of exergy criterion in energy planning analysis for 100% renewable system," Energy, Elsevier, vol. 174(C), pages 749-767.

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