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Estimation of anthropogenic heat flux of Fujian Province （China） based on Luojia 1-01 nighttime light data

  • role： First author第一作者
  • Affiliation：

    College of Architecture and Urban Planning, Fujian University of Technology, Fuzhou 350118, China

  • Email：linzl@fjut.edu.cn
  • Introduction：林中立，研究方向为城市环境遥感研究。E-mail：linzl@fjut.edu.cn
LIN Zhongli1,  
  • role： Corresponding author通信作者
  • Affiliation：

    Ministry of Education Key Laboratory of Spatial Data Mining & Information Sharing, College of Environmental and Safety Engineering, Fuzhou University, Fuzhou 350116, China

    Fujian Provincial Key Laboratory of Remote Sensing Soil Erosion and Disaster Prevention, Institute of Remote Sensing Information Engineering, Fuzhou University, Fuzhou 350116, China

  • Email：hxu@fzu.edu.cn
  • Introduction：徐涵秋，研究方向为环境遥感应用研究。E-mail：hxu@fzu.edu.cn
XU Hanqiu23*,  
  • Affiliation：

    College of Architecture and Urban Planning, Fujian University of Technology, Fuzhou 350118, China

LIN Conghua1

resumen

Nighttime light (NTL) data are important for estimating Anthropogenic Heat Flux (AHF). However, the commonly used DMSP/OLS and Suomi-NPP/VIIRS NTL data are restricted by their coarse spatial resolution and therefore, cannot exhibit the spatial details of AHF at city scale.The 130 m high-resolution NTL data obtained by the Luojia 1-01 satellite launched in June 2018 show potential to solve this problem. Therefore, this study aims to construct an AHF estimation model using the NTL data of Luojia 1-01 for Fujian Province based on three indexes, namely, normalized nighttime light data (NTLnor), Human Settlement Index (HSI), and Vegetation Adjusted NTL Urban Index (VANUI).To determine the best estimation model of AHF, the AHF of 84 county-level cities of Fujian Province has also been calculated using energy-consumption statistics data and then correlated with the corresponding data of three indexes.Results show that (1) based on a five-fold cross validation approach, VANUI power estimation model achieves the highest R2 along with the smallest RMSE; therefore, it has the highest accuracy among the three indexes; (2) according to the VANUI power estimation model, the average annual AHF of Fujian Province in 2018 is 0.88 W/m2, of which Xiamen has the highest average annual AHF of 10.98 W/m2, followed by Quanzhou, Putian, Fuzhou, and Zhangzhou, with the annual average of 0.98—1.95 W/m2, whereas the figures of Ningde, Longyan, Sanming, and Nanping are relatively low, ranging from 0.38—0.46 W/m2; (3) Luojia 1-01 NTL data can reveal the AHF differentiation details at a city scale. The AHF values of different land properties and functions show the following order: urban commercial area > large municipal public facility area > urban main road > urban residential area > suburban residential area.Studies have shown that the AHF estimation model developed by Luojia 1-01 NTL data can achieve high accuracy of the city-scale estimation of AHF.

palabra clave

remote sensing;Anthropogenic heat;AHF;Luojia 1-01;nighttime light imagery;Fujian province

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