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A platform for research: civil engineering, architecture and urbanism
Temporal and spatial heterogeneity research of urban anthropogenic heat emissions based on multi-source spatial big data fusion for Xi’an, China
Graphical abstract Display Omitted
Highlights A method of calculating the AHE based on multi-source spatiotemporal big data. Activity trajectory and real-time traffic conditions were jointly used in spatial integration to estimate the AHF. Land use and remote sensing data were jointly used in estimating the AHF of buildings. The spatiotemporal heterogeneity of the AHE was dynamically assessed.
Abstract Anthropogenic heat emission (AHE) influences the local energy balance and intensify the urban heat island (UHI) effect. An accurate calculation of the AHE can improve the precision of UHI predictions. However, reliable AHE calculations with high temporal and spatial resolution in domestic research is still lacking. Therefore, this study proposes an approach to estimate the dynamic AHE by integrating multi-source Internet big data and high-precision urban spatial data. First, we quantified the dynamic distribution of residents’ trajectories by tracking multi-stage Internet geographic location data, real-time traffic conditions of Xi’an city, supplemented by on-site drone monitoring. Then the parameters of cooling and the thermal load coefficient of building emissions, personnel cooling loads, and traffic densities were introduced. Finally, the temporal and spatial dynamic rules of the AHE were revealed. Results showed the AHE was subject to a large changing amplitude. The diurnal AHE values of 64% of the blocks ranged from 93 to 498 W/m2, especially in some core commercial areas, the value could reach above 1000 W/m2 during the peak stages. Compared with previous research, this study dynamically evaluates the temporal and spatial heterogeneity of the AHE under different emission scenarios with a short update cycle and high spatial resolution.
Temporal and spatial heterogeneity research of urban anthropogenic heat emissions based on multi-source spatial big data fusion for Xi’an, China
Graphical abstract Display Omitted
Highlights A method of calculating the AHE based on multi-source spatiotemporal big data. Activity trajectory and real-time traffic conditions were jointly used in spatial integration to estimate the AHF. Land use and remote sensing data were jointly used in estimating the AHF of buildings. The spatiotemporal heterogeneity of the AHE was dynamically assessed.
Abstract Anthropogenic heat emission (AHE) influences the local energy balance and intensify the urban heat island (UHI) effect. An accurate calculation of the AHE can improve the precision of UHI predictions. However, reliable AHE calculations with high temporal and spatial resolution in domestic research is still lacking. Therefore, this study proposes an approach to estimate the dynamic AHE by integrating multi-source Internet big data and high-precision urban spatial data. First, we quantified the dynamic distribution of residents’ trajectories by tracking multi-stage Internet geographic location data, real-time traffic conditions of Xi’an city, supplemented by on-site drone monitoring. Then the parameters of cooling and the thermal load coefficient of building emissions, personnel cooling loads, and traffic densities were introduced. Finally, the temporal and spatial dynamic rules of the AHE were revealed. Results showed the AHE was subject to a large changing amplitude. The diurnal AHE values of 64% of the blocks ranged from 93 to 498 W/m2, especially in some core commercial areas, the value could reach above 1000 W/m2 during the peak stages. Compared with previous research, this study dynamically evaluates the temporal and spatial heterogeneity of the AHE under different emission scenarios with a short update cycle and high spatial resolution.
Temporal and spatial heterogeneity research of urban anthropogenic heat emissions based on multi-source spatial big data fusion for Xi’an, China
Xu, Duo (author) / Zhou, Dian (author) / Wang, Yupeng (author) / Meng, Xiangzhao (author) / Gu, Zhaolin (author) / Yang, Yujun (author)
Energy and Buildings ; 240
2021-03-01
Article (Journal)
Electronic Resource
English
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