基于局地气候分区的济南市热环境空间分异及其 影响因素

doi:10.12082/dqxxkx.2022.210440

摘要/Abstract

摘要：

城市地表覆被及空间结构不同,导致热岛效应不同,城市热环境存在空间差异。局地气候分区（LCZ）在城市热岛研究方面得到了广泛应用。合理划分LCZ、科学制定LCZ分类标准,是基于LCZ研究城市热岛的关键技术问题。本文基于济南市城市路网、DEM和建筑大数据划分LCZ,利用Landsat 8遥感影像反演地表温度,采用克里金法进行气温空间插值,以地表温度和气温综合表达城市热环境。在此基础上,采用方差分析方法研究了城市热环境的空间分异特征和LCZ类内热环境差异,采用相关分析方法研究了城市热环境的影响因素。结果表明：① 济南市地表温度和4:00、8:00、14:00的气温空间分布格局差异明显,存在较高温度异常值的LCZ数量分别占全市LCZ总数的0.25%、1.60%、4.05%和3.96%。建筑密集区域地表温度较高,同时包含分散的较高气温区,呈现热岛效应;② 不同类型LCZ的地表温度和不同时刻气温平均值存在明显差异。高层低密度、高层中密度、中层低密度等类型存在较高气温异常值的数量分别占较高异常值总数的47.37%和33.33%、9.65%,类内热岛效应明显;③ LCZ类型不同,类内热岛效应存在差异。低层低密度、中层低密度、高层低密度和高层中密度等类型所处位置高程不同,其方差分析的P值均小于0.05,热岛效应存在显著差异;④ LCZ所处位置高程不同,建筑空间分布指标对城市热环境的影响各异。总体而言,地表温度与建筑平均高度呈负相关,且达到了0.05以上的显著性水平,而气温与之呈正相关,且达到了0.001的显著性水平;城市热环境与建筑基底面积及建筑体积的平均值和标准差、建筑密度、容积率等指标的正相关性达到了0.001的显著性水平,这些指标对城市热环境的正向影响作用明显。

关键词: 局地气候分区, 城市热岛, 空间分异, 影响因素, 温度反演, 空间插值, 方差分析, 相关分析, 济南市

Abstract:

Different urban land surface covers and spatial structures lead to different heat island effects and different urban spatial thermal environment. Local Climate Zones (LCZ) have been widely applied in the study of urban heat island. Reasonable division of LCZ and scientific formulation of LCZ classification standards are the key technical problems in the study of urban heat island based on LCZ. In this study, the LCZ of Jinan city was divided by the urban road network, Digital Elevation Model (DEM), and big data of buildings, and the quantitative classification standard of LCZ was determined by the building height and the building density. The land surface temperature was retrieved by Landsat 8 remote sensing image, and the Kriging method was used for air temperature spatial interpolation. The urban thermal environment was expressed by land surface temperature and air temperature. Based on this, the spatial differentiation characteristics of urban thermal environment and the differences of thermal environment in the same type of LCZ were studied by the method of variance analysis, and the factors of urban thermal environment were studied by the method of correlation analysis. The results show that: (1) There were obvious differences in the spatial distribution pattern of land surface temperature and air temperature at 4:00 a.m., 8:00 a.m., and 14:00 p.m. in Jinan city. Among the four types of temperature, the number of LCZ with high temperature outliers respectively accounted for 0.25%, 1.60%, 4.05%, and 3.96% of the total LCZ in the city. The area with higher land surface temperature was located in the area with dense buildings, which includes scattered areas with higher air temperature, showing heat island effect; (2) There were obvious differences in land surface temperature and air temperature at different times of a day in different types of LCZ. The number of high air temperature outliers in the LCZ of high height and low density, the LCZ of high height and medium density, and the LCZ of medium height and low density respectively accounted for 47.37%, 33.33%, and 9.65% of the total high temperature outliers, the intraclass heat island effect of these LCZ was obvious; (3) Different types of LCZ had different intraclass heat island effects. LCZ types such as low height and low density, medium height and low density, high height and low density, and high height and medium density had significant differences in heat island effect, the p values of their variance analysis were less than 0.05; (4) The impact of building spatial distribution index on urban thermal environment was different due to different location and elevation of LCZ. Overall, the negative correlation between land surface temperature and the average values of building height reached the significant level of more than 0.05, and the positive correlation between the air temperature and average building height reached the significant level of 0.001. The average values and standard deviations of building base area and building volume, building density, and floor area ratio were significantly (p<0.001) positively correlated with urban thermal environment, which indicated a significant positive impact on the urban thermal environment.

Key words: local climate zones, urban heat island, spatial differentiation, influence factors, temperature inversion, spatial interpolation, variance analysis, correlation analysis, Jinan city

单宝艳, 张巧, 任启新, 樊文平, 吕永强. 基于局地气候分区的济南市热环境空间分异及其
影响因素[J]. 地球信息科学学报, 2022, 24(4): 711-722.DOI:10.12082/dqxxkx.2022.210440

SHAN Baoyan, ZHANG Qiao, REN Qixin, FAN Wenping, Lü Yongqiang. Spatial Differentiation of Urban thermal Environment and its Influencing Factors based on Local Climate Zones in Jinan[J]. Journal of Geo-information Science, 2022, 24(4): 711-722.DOI:10.12082/dqxxkx.2022.210440

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数据	时间	来源
济南市行政边界矢量数据	2020年12月21日	http://www.sdmap.gov.cn/page/ResourceCenter.html（天地图）^[24]
Landsat 8遥感影像	2017年6月1日、6月17日,2019年6月7日	https://earthexplorer.usgs.gov/^[25]
气温数据	2020年6月1日—30日	济南市气象站点观测数据
城市道路矢量数据	2020年3月17日	百度大数据
建筑物矢量数据	2020年3月17日	百度大数据
DEM数据	2020年3月17日	Google earth

建筑高度H/m	建筑密度S/%	LCZ类型
H≤9	S≤15	低层低密度(LCZ11)
	15<S≤28	低层中密度(LCZ12)
	S>28	低层高密度(LCZ13)
9<H≤16.14	S≤15	中层低密度(LCZ21)
	15<S≤28	中层中密度(LCZ22)
	S>28	中层高密度(LCZ23)
H>16.14	S≤15	高层低密度(LCZ31)
	15<S≤28	高层中密度(LCZ32)
	S>28	高层高密度(LCZ33)

检验值	时刻
检验值	4:00	8:00	14:00
平均误差	0.0156	0.0150	0.0086
均方根误差	0.7347	1.4077	1.4557
平均标准误差	0.0155	0.0078	0.0072
平均值标准化误差	0.5348	1.2113	1.2542
标准化均方根误差	1.3365	1.1501	1.1445

方差分析	地表温度	4:00气温	8:00气温	14:00气温
F值	59.21	24.02	24.9	20.11
P值	2.93×10^-81	2.19×10^-34	1.18×10^-35	1.10×10^-28

类别	范围/m	LCZ数量/个	地表温度/℃	4:00气温/℃	8:00气温/℃	14:00气温/℃
1	20.4~65.1	755	32.9	23.4	27.9	32.2
2	65.2~135.5	234	32.3	23.5	28.4	32.4
3	135.6~235.1	123	31.1	23.9	28.9	33.0
4	235.2~433.5	38	29.7	23.7	28.3	32.3
5	433.6~747.3	27	26.7	23.2	28.4	32.6