Estimation of anthropogenic heat flux of Fujian Province （China） based on Luojia 1-01 nighttime light data
- Vol. 26, Issue 6, Pages: 1236-1246(2022)
Received：22 July 2020，
Published：07 June 2022
DOI： 10.11834/jrs.20210295
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摘要
夜间灯光数据是估算人为热通量（AHF）的重要数据，但当前应用最广的DMSP/OLS和Suomi-NPP/VIIRS夜间灯光数据由于受限于粗糙的空间分辨率，而无法刻画城市内部的AHF分布细节。中国2018年6月发射的Luojia 1-01卫星所获取的130 m高空间分辨率夜间灯光数据，则有望解决这一问题。因此本文利用Luojia 1-01夜间灯光数据，通过将统计年鉴中的能源统计数据细化至福建省84个县（市、区），然后与3个夜间灯光指数（NTL
nor
、HSI、VANUI）进行回归分析，分别构建了基于这3个指数的福建省AHF空间估算模型，并采用交叉验证法对其进行筛选。结果显示：（1）在3个指数中，基于VANUI的乘幂估算模型的
R
2
最高，且RMSE最小，因此精度最高；（2）利用VANUI乘幂估算模型反演得到的2018年福建省年均AHF为0.88 W/m
2
，其中厦门市的年均AHF最高，达10.98 W/m
2
，泉州、莆田、福州、漳州等沿海城市次之，年均值在0.98—1.95 W/m
2
，而宁德、龙岩、三明、南平等城市的AHF则较低，均值在0.38—0.46 W/m
2
；（3）Luojia 1-01夜间灯光数据可以揭示城市内部的AHF分异细节。根据用地属性和功能的不同，AHF数值表现为：城市集中商业区
>
大型市政公共设施区
>
城市主干道
>
城市住宅区
>
近郊住宅区。研究表明，基于Luojia 1-01夜间灯光数据建立的AHF估算模型可以较好地揭示城市尺度AHF的空间分异情况。
Abstract
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 (NTL
nor
)
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
R
2
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/m
2
of which Xiamen has the highest average annual AHF of 10.98 W/m
2
followed by Quanzhou
Putian
Fuzhou
and Zhangzhou
with the annual average of 0.98—1.95 W/m
2
whereas the figures of Ningde
Longyan
Sanming
and Nanping are relatively low
ranging from 0.38—0.46 W/m
2
; (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.
关键词
Keywords
references
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ZHOU Xiao-cheng 福州大学福建省空间信息工程研究中心空间数据挖掘与信息共享教育部重点实验室 ; 福州大学福建省空间信息工程研究中心空间数据挖掘与信息共享教育部重点实验室 福建福州350002
LI Hui-guo 福州大学福建省空间信息工程研究中心空间数据挖掘与信息共享教育部重点实验室 ; 福州大学福建省空间信息工程研究中心空间数据挖掘与信息共享教育部重点实验室 福建福州350002
WANG Xiao-qin 福州大学福建省空间信息工程研究中心空间数据挖掘与信息共享教育部重点实验室 ; 福州大学福建省空间信息工程研究中心空间数据挖掘与信息共享教育部重点实验室 福建福州350002
YANG Yunjie 西南交通大学 地球科学与工程学院
ZHANG Rui 西南交通大学 地球科学与工程学院
JIANG Han 西南交通大学 地球科学与工程学院
ZHANG Bo 西南交通大学 地球科学与工程学院
SONG Yunfan 中国气象局成都高原气象研究所
相关机构
Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education,Spatial Information Research Centerof Fujian Province,Fuzhou University
福州大学福建省空间信息工程研究中心空间数据挖掘与信息共享教育部重点实验室 福建福州350002
Faculty of Geosciences and Engineering, Southwest Jiaotong University
Chengdu Institute of Plateau Meteorology, China Meteorological Administration
School of Environmental and Geographical Sciences, Shanghai Normal University
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