Spatialization of electricity consumption by combining high-resolution nighttime light remote sensing and urban functional zoning information
An accurate and timely spatialization of electricity consumption is fundamental for energy management and sustainable urban development. While previous research has relied heavily on statistical data or moderate-resolution nighttime light data, this study has presented a new spatialization method by...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-03-01
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| Series: | Geo-spatial Information Science |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/10095020.2024.2356757 |
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| author | Siyan Lu Yue Xiao Yifan Lu Jinyao Lin |
| author_facet | Siyan Lu Yue Xiao Yifan Lu Jinyao Lin |
| author_sort | Siyan Lu |
| collection | DOAJ |
| description | An accurate and timely spatialization of electricity consumption is fundamental for energy management and sustainable urban development. While previous research has relied heavily on statistical data or moderate-resolution nighttime light data, this study has presented a new spatialization method by combining high-resolution Luojia 1–01 nighttime light and urban functional zoning information. The total electricity consumption volume can be allocated to each land use pixel based on its strong linear relationship with nighttime light. Specifically, urban functional zoning data were connected with the corresponding economic sectors to differentiate the complex relationships between electricity consumption and nighttime light within different zones. The digital number value of every pixel can be multiplied by its corresponding electricity consumption coefficient. A number of comparisons have indicated that the proposed method can more accurately characterize the spatial distribution of electricity consumption. Our results can exhibit much clearer outlines and more detailed internal characteristics. More importantly, urban functional zoning information can be used to distinguish the electricity consumption of various economic sectors at fine scales. The proposed method is expected to capture the spatial characteristics of electricity consumption in a timely and accurate manner. The findings can help local authorities formulate sustainable energy utilization and emission reduction strategies. |
| format | Article |
| id | doaj-art-486aafb4680d4574baf4a389e4e521c0 |
| institution | Matheson Library |
| issn | 1009-5020 1993-5153 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geo-spatial Information Science |
| spelling | doaj-art-486aafb4680d4574baf4a389e4e521c02025-06-27T09:55:24ZengTaylor & Francis GroupGeo-spatial Information Science1009-50201993-51532025-03-0128252754010.1080/10095020.2024.2356757Spatialization of electricity consumption by combining high-resolution nighttime light remote sensing and urban functional zoning informationSiyan Lu0Yue Xiao1Yifan Lu2Jinyao Lin3School of Geography and Remote Sensing, Guangzhou University, Guangzhou, ChinaSchool of Geography and Remote Sensing, Guangzhou University, Guangzhou, ChinaSchool of Geography and Remote Sensing, Guangzhou University, Guangzhou, ChinaSchool of Geography and Remote Sensing, Guangzhou University, Guangzhou, ChinaAn accurate and timely spatialization of electricity consumption is fundamental for energy management and sustainable urban development. While previous research has relied heavily on statistical data or moderate-resolution nighttime light data, this study has presented a new spatialization method by combining high-resolution Luojia 1–01 nighttime light and urban functional zoning information. The total electricity consumption volume can be allocated to each land use pixel based on its strong linear relationship with nighttime light. Specifically, urban functional zoning data were connected with the corresponding economic sectors to differentiate the complex relationships between electricity consumption and nighttime light within different zones. The digital number value of every pixel can be multiplied by its corresponding electricity consumption coefficient. A number of comparisons have indicated that the proposed method can more accurately characterize the spatial distribution of electricity consumption. Our results can exhibit much clearer outlines and more detailed internal characteristics. More importantly, urban functional zoning information can be used to distinguish the electricity consumption of various economic sectors at fine scales. The proposed method is expected to capture the spatial characteristics of electricity consumption in a timely and accurate manner. The findings can help local authorities formulate sustainable energy utilization and emission reduction strategies.https://www.tandfonline.com/doi/10.1080/10095020.2024.2356757Electric power consumptionnighttime lightssocioeconomic conditionsgeographic information systemshigh-resolution mapping |
| spellingShingle | Siyan Lu Yue Xiao Yifan Lu Jinyao Lin Spatialization of electricity consumption by combining high-resolution nighttime light remote sensing and urban functional zoning information Geo-spatial Information Science Electric power consumption nighttime lights socioeconomic conditions geographic information systems high-resolution mapping |
| title | Spatialization of electricity consumption by combining high-resolution nighttime light remote sensing and urban functional zoning information |
| title_full | Spatialization of electricity consumption by combining high-resolution nighttime light remote sensing and urban functional zoning information |
| title_fullStr | Spatialization of electricity consumption by combining high-resolution nighttime light remote sensing and urban functional zoning information |
| title_full_unstemmed | Spatialization of electricity consumption by combining high-resolution nighttime light remote sensing and urban functional zoning information |
| title_short | Spatialization of electricity consumption by combining high-resolution nighttime light remote sensing and urban functional zoning information |
| title_sort | spatialization of electricity consumption by combining high resolution nighttime light remote sensing and urban functional zoning information |
| topic | Electric power consumption nighttime lights socioeconomic conditions geographic information systems high-resolution mapping |
| url | https://www.tandfonline.com/doi/10.1080/10095020.2024.2356757 |
| work_keys_str_mv | AT siyanlu spatializationofelectricityconsumptionbycombininghighresolutionnighttimelightremotesensingandurbanfunctionalzoninginformation AT yuexiao spatializationofelectricityconsumptionbycombininghighresolutionnighttimelightremotesensingandurbanfunctionalzoninginformation AT yifanlu spatializationofelectricityconsumptionbycombininghighresolutionnighttimelightremotesensingandurbanfunctionalzoninginformation AT jinyaolin spatializationofelectricityconsumptionbycombininghighresolutionnighttimelightremotesensingandurbanfunctionalzoninginformation |