南宁市主城区不透水面与热环境效应的空间关系研究

doi:10.16258/j.cnki.1674-5906.2023.03.010

生态环境学报 ›› 2023, Vol. 32 ›› Issue (3): 525-534.DOI: 10.16258/j.cnki.1674-5906.2023.03.010

南宁市主城区不透水面与热环境效应的空间关系研究

王嘉丽¹^,²(), 冯婧珂³, 杨元征¹^,², 俎佳星¹^,², 蔡文华¹^,², 杨健¹^,²

1.南宁师范大学/北部湾环境演变与资源利用教育部重点实验室，广西南宁 530001
2.南宁师范大学广西地表过程与智能模拟重点实验室，广西南宁 530001
3.南宁师范大学地理科学与规划学院，广西南宁 530001

收稿日期:2022-07-21 出版日期:2023-03-18 发布日期:2023-06-02
作者简介:王嘉丽（1988年生），女，副研究员，博士，研究方向为城市化及其生态环境效应。E-mail: wangjiali833666@163.com
基金资助:
国家自然科学基金项目(42061053);广西科技基地和人才专项(桂科AD19110143);广西科技基地和人才专项(桂科AD21220057);广西壮族自治区第五批八桂学者专项经费

Research on Spatial Relations between Impervious Surfaces and the Urban Thermal Environment in the Central Metropolitan Area of Nanning City

WANG Jiali¹^,²(), FENG Jingke³, YANG Yuanzheng¹^,², ZU Jiaxing¹^,², CAI Wenhua¹^,², YANG Jian¹^,²

1. Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Ministry of Education/Nanning Normal University, Nanning, 530001, P. R. China
2. Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation, Nanning Normal University, Nanning, 530001, P. R. China
3. School of Geography Science and Planning, Nanning Normal University, Nanning 530001, P. R. China

Received:2022-07-21 Online:2023-03-18 Published:2023-06-02

摘要/Abstract

摘要：

快速城市化过程中不透水面持续扩张是影响城市热环境变化的重要原因。科学测度城市不透水面变化及其与热环境之间的关系，可以为有效制定合理的城市蓝绿空间规划提供依据。基于南宁市主城区2003-2019年间Landsat遥感影像，利用面向对象分类方法获取城市土地利用数据，借助辐射传输方程反演地表温度，定量分析城市不透水面与热环境效应的时空格局演变特征，运用双变量空间自相关方法探索城市不透水面与热环境效应的空间关系和集聚规律。研究结果显示，近15年来南宁市主城区不透水面的面积显著增加，城市主要沿环路以内的老城区和主要交通要道不断向外扩展，主要扩张方向为向东和向南。城市热场由中温区占主导，低温区和次低温区的面积波动下降，高温区与次高温区的范围逐渐蔓延，城市热岛效应有所加剧。南宁市热岛分布格局由单中心转变为多中心，新开发区的热岛效应明显增强。南宁市主城区不透水面与热环境效应之间呈现明显正相关关系，从2003-2019年相关性逐渐增强。空间集聚类型以高-高聚集和低-低集聚为主，高-高聚集区主要分布于城市中心，低-低聚集区位于东部绿地比例较高及河流分布集中的地区。该研究通过探讨南宁市主城区不透水面与热环境的空间关系，明确二者空间集聚与分异特征，有助于识别城市热环境亟需优化改善的区域，进而通过增加城市绿地和水体斑块，加强城市绿地生态网络建设等方式实现城市蓝绿空间优化配置以缓解热岛效应。研究结果可以为城市景观格局优化和生态宜居城市建设提供指导。

关键词: 不透水面, 热环境, 热场强度, 时空演变特征, 双变量空间自相关, 南宁市

Abstract:

The continuous expansion of impervious surfaces in the rapid urbanization process is the leading cause of the change in the urban thermal environment. Research on the relationship between impervious surfaces and urban heat islands can provide a basis for effective and appropriate urban planning. Based on the Landsat images of the central metropolitan area in Nanning city during 2003-2019, we extracted the land use data using an object-oriented method and retrieved the land surface temperature of the study area by the radiative transfer equation method. Then, spatial-temporal characteristics of impervious surfaces and urban heat islands were quantitatively analyzed. Finally, we employed the bivariate spatial autocorrelation method to explore the spatial relations between urban impervious surfaces and the thermal environment. The results showed that the impervious surface of the central metropolitan area in Nanning City displayed a rapid increase trend, and the new growth expanded along the old city area and main roads. The urban thermal field was dominated by the medium temperature region, and the area of low or low-medium temperature regions had been decreasing in a fluctuated fashion. At the same time, the medium-high and high temperature regions had gradually expanded. The urban heat island pattern changed from single to multiple centers, and the heat island effect of the new development zone was noticeably enhanced. The study area had a significant positive correlation between urban impervious surface and the thermal environment, and the correlation coefficient had gradually increased from 2003 to 2019. The spatial correlation types were dominated by High-High agglomeration and Low-Low agglomeration. The High-High area was mainly distributed in the urban center, and the Low-Low area was located in the regions covered by vegetation and water. This study explored spatial relations between urban impervious surfaces and the thermal environment. It clarifies their spatial agglomeration types, which helps identify the key areas to improve the urban thermal environment. Planners concerned can optimize the allocation of urban blue-green space in these crucial areas by increasing green space and water patches and constructing green space network to alleviate the urban heat island effect. The research results provide guidance for urban landscape pattern optimization and ecologically livable city construction in Nanning City.

Key words: impervious surface, thermal environment, thermal field intensity, spatiotemporal evolution characteristics, bivariate spatial autocorrelation analysis, Nanning City

中图分类号:

王嘉丽, 冯婧珂, 杨元征, 俎佳星, 蔡文华, 杨健. 南宁市主城区不透水面与热环境效应的空间关系研究[J]. 生态环境学报, 2023, 32(3): 525-534.

WANG Jiali, FENG Jingke, YANG Yuanzheng, ZU Jiaxing, CAI Wenhua, YANG Jian. Research on Spatial Relations between Impervious Surfaces and the Urban Thermal Environment in the Central Metropolitan Area of Nanning City[J]. Ecology and Environment, 2023, 32(3): 525-534.

图/表 7

图1 研究区位置示意图

Figure 1 The location of study area

表1 均值—标准差方法划分城市热场等级

Table 1 Mean-standard deviation method to classify urban thermal field

热场等级	划分方法
低温区	H_i <μ-s
次低温区	μ-s≤H_i <μ-0.5s
中温区	μ-0.5s≤H_i <μ+0.5s
次高温区	μ+0.5s≤H_i <μ+s
高温区	H_i ≥μ+s

图2 南宁市主城区土地利用空间分布图

Figure 2 Spatial pattern of land use in the central metropolitan area of Nanning City

图3 南宁市主城区各类型土地利用动态变化图

Figure 3 Statistical map of land use change in the central metropolitan area of Nanning City

图4 南宁市主城区热场等级空间分布图

Figure 4 Spatial distribution of thermal field in the central metropolitan area of Nanning City

表2 南宁市主城区热场面积比例统计表

Table 2 Statistics of the thermal filed characteristics in the study area

热场等级	2003年		2009年		2016年		2019年
热场等级	面积/km²	比例/%	面积/km²	比例/%	面积/km²	比例/%	面积/km²	比例/%
低温区	160.60	17.78	114.11	12.63	151.29	16.75	143.67	15.91
次低温区	169.39	18.75	156.02	17.27	119.68	13.25	160.40	17.76
中温区	352.69	39.05	359.32	39.78	343.42	38.02	297.86	32.98
次高温区	84.02	9.30	122.12	13.52	137.77	15.25	151.28	16.75
高温区	136.52	15.11	151.64	16.79	151.05	16.72	150.00	16.61

图5 南宁市主城区不透水面与热环境效应LISA聚类分布图

Figure 5 LISA distribution of impervious surfaces and urban thermal environment in the central metropolitan area of Nanning City

参考文献 32

[1]	CHEN H Y, DENG Q L, ZHOU Z, et al., 2022. Influence of land cover change on spatio-temporal distribution of urban heat island: A case in Wuhan main urban area[J]. Sustainable Cities and Society, 103715.
[2]	FU P, WENG Q H, 2016. A time series analysis of urbanization induced land use and land cover change and its impact on land surface temperature with Landsat imagery[J]. Remote Sensing of Environment, 175(4): 205-214. DOI URL
[3]	KARLESSI T, SANTAMOURIS M, SYNNEFA A, et al., 2011. Development and testing of PCM doped cool colored coatings to mitigate urban heat island and cool buildings[J]. Building and Environment, 46(3): 570-576. DOI URL
[4]	KE X L, MEN H L, ZHOU T, et al., 2021. Variance of the impact of urban green space on the urban heat island effect among different urban functional zones: A case study in Wuhan[J]. Urban Forestry and Urban Greening, 62: 127159. DOI URL
[5]	KIM D W, DEO R C, CHUNG J H, et al., 2016. Projection of heat wave mortality related to climate change in Korea[J]. Natural Hazards, 80(1): 623-637. DOI URL
[6]	MA Y L, ZHANG S H, YANG K, et al., 2021. Influence of spatiotemporal pattern changes of impervious surface of urban megaregion on thermal environment: A case study of the Guangdong-Hong Kong-Macao Greater Bay Area of China[J]. Ecological Indicators, 121: 107106. DOI URL
[7]	MIRSANJARI M, MOHAMMADYARI F, VISOCKIENE J, et al., 2021. Relationship between land surface temperature and urbanization in Vilnius district[J]. Environmental Monitoring and Assessment, 193(8): 1-14. DOI
[8]	PENG S S, PIAO S L, CIAIS P, et al., 2012. Surface urban heat island across 419 global big cities[J]. Environmental Science and Technology, 46(2): 696-703. DOI PMID
[9]	SHAHMOHAMADI P, CHE-ANI A I, ETESSAM I, et al., 2011. Healthy environment: The need to mitigate urban heat island effects on human health[J]. Procedia Engineering, 20: 61-70. DOI URL
[10]	SUN Q Q, WU Z F, TAN J J, 2012. The relationship between land surface temperature and land use/land cover in Guangzhou, China[J]. Environmental Earth Science, 65: 1687-1694. DOI URL
[11]	YE Y Q, BRYAN B A, ZHANG J E, et al., 2018. Changes in land-use and ecosystem services in the Guangzhou-Foshan Metropolitan Area, China from 1990 to 2010: Implications for sustainability under rapid urbanization[J]. Ecological indicators, 93: 930-941. DOI URL
[12]	YU Z W, YAO Y W, YANG G Y, et al., 2019. Spatiotemporal patterns and characteristics of remotely sensed region heat islands during the rapid urbanization (1995-2015) of Southern China[J]. Science of the Total Environment, 674: 242-254. DOI URL
[13]	ZHOU W Q, HUANG G L, CADENASSO M, 2011. Does spatial configuration matter? Understanding the effects of land cover pattern on land surface temperature in urban landscapes[J]. Landscape and Urban Planning, 102(1): 54-63. DOI URL
[14]	曹琦, 师满江, 周亮, 等, 2019. 山地城市裸地时空变化的热环境响应特征研究[J]. 国土资源遥感, 31(4): 190-198.
	CAO Q, SHI M J, ZHOU L, et al., 2019. Study of the response characteristics of thermal environment with spatial and temporal changes of bare land in the mountain city[J]. Remote Sensing for Land and Resources, 31(4): 190-198.
[15]	陈正华, 马小雨, 张威, 等, 2020. 利用Landsat资料的南宁近年来城市热岛效应研究[J]. 广西大学学报(自然科学版), 45(2): 378-388.
	CHEN Z H, MA X Y, ZHANG W, et al., 2020. Using Landsat data to calculate urban heat island effect in recent years of Nanning[J]. Journal of Guangxi University (Natural Science Edition), 45(2): 378-388.
[16]	郭宇, 王宏伟, 张喆, 等, 2020. 南京市热环境与地表覆被的时空尺度效应及驱动机制研究[J]. 生态环境学报, 29(7): 1403-1411. DOI
	GUO Y, WANG H W, ZHANG Z, et al., 2020. Spatio-temporal scale effect and driving mechanism of thermal environment and land surface cover in Nanjing[J]. Ecology and Environmental Sciences, 29(7): 1403-1411.
[17]	贾艳艳, 王少杰, 刘福胜, 等, 2020. 黄河三角洲高效生态经济区土地利用变化及其与生境质量的相关性[J]. 水土保持通报, 40(6): 213-220.
	JIA Y Y, WANG S J, LIU F S, et al., 2020. Land use change and its correlation with habitat quality in high efficiency eco-economic zone of Yellow River delta[J]. Bulletin of Soil and Water Conservation, 40(6): 213-220.
[18]	雷金睿, 陈宗铸, 吴庭天, 等, 2019. 海南岛东北部土地利用与生态系统服务价值空间自相关格局分析[J]. 生态学报, 39(7): 2366-2377.
	LEI J R, CHEN Z Z, WU T T, et al., 2019. Spatial autocorrelation pattern analysis of land use and the value of ecosystem services in northeast Hainan Island[J]. Acta Ecologica Sinica, 39(7): 2366-2377.
[19]	李恒凯, 阮永俭, 杨柳, 等, 2017. 中小城市城区扩张的热效应演变及响应[J]. 测绘科学, 42(2): 71-77, 83.
	LI H K, RUAN Y J, YANG L, et al., 2017. Thermal effect evolution and response of small and medium size cities' expansion[J]. Science of Surveying and Mapping, 42(2): 71-77, 83.
[20]	李膨利, Muhammad Amir Siddique, 樊柏青, 等, 2020. 下垫面覆盖类型变化对城市热岛的影响——以北京市朝阳区为例[J]. 北京林业大学学报, 42(3): 99-109.
	LI P L, MUHAMMAD A S, FAN B Q, et al., 2020. Effects of land surface type changes on urban heat island: A case study of Chaoyang District, Beijing[J]. Journal of Beijing Forestry University, 42(3): 99-109.
[21]	李喆, 陈圣宾, 陈芝阳, 2022. 地表温度与土地利用类型间的空间尺度依赖性——以成都为例[J]. 生态环境学报, 31(5): 999-1007. DOI
	LI Z, CHEN S B, CHEN Z Y, 2022. Spatial scale dependence between land surface temperature and land use types: A case study of Chengdu City[J]. Ecology and Environmental Sciences, 31(5): 999-1007.
[22]	刘清, 范城城, 刘润东, 等, 2019. 近60年南宁市城区城市空间扩展遥感监测研究[J]. 广西大学学报(自然科学版), 44(6): 1573-1583.
	LIU Q, FAN C C, LIU R D, et al., 2019. Remote sensing monitoring of urban spatial expansion of Nanning city in the past 60 years[J]. Journal of Guangxi University (Natural Science Edition), 44(6): 1573-1583.
[23]	潘莹, 崔林林, 刘昌脉, 等, 2018. 基于MODIS数据的重庆市城市热岛效应时空分析[J]. 生态学杂志, 37(12): 3736-3745.
	PAN Y, CUI L L, LIU C M, et al., 2018. Spatiotemporal distribution of urban heat island effect based on MODIS data in Chongqing, China[J]. Chinese Journal of Ecology, 37(12): 3736-3745.
[24]	王俊凝, 单宝艳, 刘洋洋, 等, 2022. 城市空间结构对城市热场的影响——以济南市夏季为例[J]. 地球环境学报, 13(1): 100-109.
	WANG J N, SHAN B Y, LIU Y Y, et al., 2022. The influence of urban spatial structure on urban thermal field: A case study of Jinan in summer[J]. Journal of Earth Environment, 13(1): 100-109.
[25]	王宪凯, 孟庆岩, 李娟, 等, 2021. 北京市主城区不透水面时空演变及其热环境效应研究[J]. 生态科学, 40(1): 169-181.
	WANG X K, MENG Q Y, LI J, et al., 2021. Spatiotemporal evolution and thermal environmental effects of impervious surfaces in the main urban area of Beijing[J]. Ecological Science, 40(1): 169-181.
[26]	王煜, 唐力, 朱海涛, 等, 2021. 基于多源遥感数据的城市热环境响应与归因分析——以深圳市为例[J]. 生态学报, 41(22): 8771-8782.
	WANG Y, TANG L, ZHU H T, et al., 2021. The study of urban thermal environment dynamics and attribution analysis based on multiple remote sensing dataset: In the case of Shenzhen[J]. Acta Ecologica Sinica, 41(22): 8771-8782.
[27]	吴子璇, 张强, 宋长青, 等, 2019. 珠三角城市化对气温时空差异性影响[J]. 地理学报, 74(11): 2342-2357. DOI
	WU Z X, ZHANG Q, SONG C Q, et al., 2019. Impacts of urbanization on spatio-temporal variations of temperature over the Pearl River Delta[J]. Acta Geographica Sinica, 74(11): 2342-2357. DOI
[28]	谢启姣, 陈昆仑, 金贵, 2017. 武汉城镇化与热岛效应的定量研究[J]. 测绘科学, 42(9): 71-76, 87.
	XIE Q J, CHEN K L, JIN G., 2017. Quantifying urbanization and its impact on urban heat island effect in Wuhan[J]. Science of Surveying and Mapping, 42(9): 71-76, 87.
[29]	谢启姣, 刘进华, 胡道华, 2016. 武汉城市扩张对热场时空演变的影响[J]. 地理研究, 35(7): 1259-1272. DOI
	XIE Q J, LIU J H, HU D H., 2016. Urban expansion and its impact on spatio-temporal variation of urban thermal characteristics: A case study of Wuhan[J]. Geographical Research, 35(7): 1259-1272.
[30]	杨玉婷, 汤家法, 边金虎, 等, 2021. 加尔各答市地表温度与不透水面比例季相相关性研究[J]. 遥感技术与应用, 36(1): 79-89.
	YANG Y T, TANG J F, BIAN J H, et al., 2021. Seasonal Variations in the Relationship between Land Surface Temperature and Impervious Surface Percentage in Kolkata[J]. Remote Sensing Technology and Application, 36(1): 79-89.
[31]	姚晓洁, 王霞, 姚侠妹, 2021. 基于RS技术的皖北城市阜阳市主城区热环境效应分析[J]. 生态学杂志, 40(10): 3290-3303.
	YAO X J, WANG X, YAO X M, 2021. Thermal environmental effect of the main urban area of Fuyang City in northern Anhui based on RS technology[J]. Chinese Journal of Ecology, 40(10): 3290-3303.
[32]	虞文娟, 任田, 周伟奇, 等, 2020. 区域城市扩张对森林景观破碎化的影响——以粤港澳大湾区为例[J]. 生态学报, 40(23): 8474-8481.
	YU W J, REN T, ZHOU W Q, et al., 2020. Forest fragmentation and its relationship with urban expansion in Guangdong-Hong Kong- Macao Great Bay Area, China[J]. Acta Ecologica Sinica, 40(23): 8474-8481.

南宁市主城区不透水面与热环境效应的空间关系研究

Research on Spatial Relations between Impervious Surfaces and the Urban Thermal Environment in the Central Metropolitan Area of Nanning City

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