Dynamic Study on the Heat Island Effect and Landscape Pattern in Nanjing

doi:10.13466/j.cnki.lyzygl.2019.03.023

Abstract

Abstract:

In this study,Landsat5 TM(2000)and Landsat8 OLI_TIRS(2017)were used to derive land surface temperature based on radiative transfer equation,and the landscape pattern indices were calculated to analyze the evolution of the thermal landscape pattern in Nanjing.Then the relationship between urban landscape pattern and thermal environment was analyzed with mutiple linear regession model.The results showed that,from 2001 to 2014,the heat island effect was obviously enhanced,and the high temperature area of heat island increased substantially,and there was a higher growth in Liuhe,Jiangning and Pukou than that in other districts.The area and connectivity of heat island patch increased and the fragmentation decreased.The preponderance of heat island in the thermal landscape pattern increased.Generally,the fragmentation of thermal landscape in Nanjing was gradually reduced,and the patch shape was becoming regular,while the agglomeration and connectivity was increased.During the rapid urbanization process,the heat island effect can be mitigated by rational planning of urban layout and appropriately increasing the area of urban green space.

Key words: landscape pattern, ermal landscape, eat island effect, land surface temperature, Nanjing

CLC Number:

TU985

GUO Jiqiang, PAN Jie. Dynamic Study on the Heat Island Effect and Landscape Pattern in Nanjing[J]. FOREST RESOURCES WANAGEMENT, 2019, (3): 139-146.

Figures/Tables 10

Tab.1

Fig.1

Tab.2

Fig.2

Tab.3

Tab.4

Tab.5

Fig.3

Tab.6

Correlation coefficients between landscape pattern index and the surface temperature at the patch-class level

景观类型	年份	CA	PD	LPI	LSI	DIVISION	AI
建设用地	2017	0.89^**	0.20	0.76^**	0.74^**	-0.64^**	0.83^**
建设用地	2000	0.73^**	0.24^*	0.71^**	0.69^**	-0.67^**	0.72^**
林地	2017	-0.45^**	0.10	-0.52^**	0.10	0.47^**	-0.10
林地	2000	-0.39^**	0.01	-0.4 $9 * *$	-0.01	0.41^**	-0.14
水体	2017	-0.73^**	-0.20	-0.74^**	-0.05	0.70^**	-0.36^**
水体	2000	-0.67^**	-0.33	-0.65^**	-0.15	0.61^**	-0.33^**
耕地	2017	-0.36^*	0.63^**	0.03	0.84^**	-0.03	-0.46^**
耕地	2000	-0.26^*	0.62^**	0.01	0.71^**	-0.02	-0.41^**
草地	2017	-0.04	0.03	-0.11	-0.04	0.03	-0.14
草地	2000	-0.08	-0.01	-0.15	-0.04	0.06	-0.16
未利用地	2017	0.01	0.08	0.02	-0.03	-0.08	-0.02
未利用地	2000	0.16	0.06	0.12	0.12	-0.10	0.06

Tab.6

Fig.4

References 20

[1]	魏后凯. 新时期中国城镇化转型的方向[J]. 中国发展观察, 2014(7):4-7.
[2]	Feizizadeh B, Blaschke T. Land suitability analysis for Tabriz County,Iran:a multi-criteria evaluation approach using GIS[J]. Journal of Environmental Planning and Management, 2013,56(1):1-23.
[3]	Mohan M, Kandya A. Impact of urbanization and land-use/land-cover change on diurnal temperature range:a case study of tropical urban airshed of India using remote sensing data[J]. Science of the Total Environment, 2015(506/507):453-465.
[4]	肖荣波, 欧阳志云, 李伟峰, 等. 城市热岛的生态环境效应[J]. 生态学报, 2005,25(8):2055-2060.
[5]	戴晓燕, 张利权, 过仲阳, 等. 上海城市热岛效应形成机制及空间格局[J]. 生态学报, 2009,29(7):3995-4004.
[6]	陶康华, 陈云浩, 周巧兰, 等. 热力景观在城市生态规划中的应用[J]. 城市研究, 1999(1):20-22.
[7]	Weng Qihao, Liu Hua, Lu Dengsheng. Assessing the effects of land use and land cover patterns on thermal conditions using landscape metrics in city of Indianapolis,United States[J]. Urban Ecosystems, 2007,10(2):203-219.
[8]	周雅星, 刘茂松, 徐驰, 等. 南京市市域热场分布与景观格局的关联分析[J]. 生态学杂志, 2014,33(8):2199-2206.
[9]	赵璊璊, 冯莉, 郭松, 等. 景观格局影响下的南京市热舒适度动态变化[J]. 长江流域资源与环境, 2018,27(8):1712-1724.
[10]	徐涵秋. 新型Landsat8卫星影像的反射率和地表温度反演[J]. 地球物理学报, 2015,58(3):741-747.
[11]	孟宪红, 吕世华, 张宇, 等. 使用LANDSAT-5 TM数据反演金塔地表温度[J]. 高原气象, 2005,24(5):721-726.
[12]	白洁, 刘绍民, 扈光. 针对TM/ETM+遥感数据的地表温度反演与验证[J]. 农业工程学报, 2008,24(9):148-154.
[13]	覃志豪, 李文娟, 徐斌, 等. 陆地卫星TM6波段范围内地表比辐射率的估计[J]. 国土资源遥感, 2004,16(3):28-32.
[14]	查勇, 倪绍祥, 杨山. 一种利用TM图像自动提取城镇用地信息的有效方法[J]. 遥感学报, 2003,7(1):37-40.
[15]	王天星, 陈松林, 阎广建. 地表参数反演及城市热岛时空演变分析[J]. 地理科学, 2009,29(5):697-702.
[16]	肖笃宁, 李秀珍, 高峻, 等. 景观生态学[M]. 北京: 科学出版社, 2003.
[17]	苟睿坤, 赵选, 卜元坤, 等. 杭州市城区热岛效应与景观格局的动态研究[J]. 水土保持研究, 2019,26(1):316-322.
[18]	谢启姣, 段吕晗, 汪正祥. 夏季城市景观格局对热场空间分布的影响——以武汉为例[J]. 长江流域资源与环境, 2018,27(8):1735-1744.
[19]	邬建国. 景观生态学:格局、过程尺度与等级[M]. 北京: 高等教育出版社, 2007.
[20]	卢惠敏, 李飞, 张美亮, 等. 景观格局对杭州城市热环境年内变化的影响分析[J]. 遥感技术与应用, 2018,33(3):398-407.

热力等级	划分区间
高温区	T>u+std
次高温区	u+0.5std<T≤u+std
中温区	u-0.5std≤T≤u+0.5std
次低温区	u-std≤T<u-0.5std
低温区	T< u-std

热力等级	2000年		2017年
热力等级	面积/km²	比例/%	面积/km²	比例/%
低温区	658.8	10.01	870.14	13.21
次低温区	875.99	13.31	866.19	13.15
中温区	3334.81	50.67	2817.92	42.78
次高温区	1132.01	17.2	1114.52	16.92
高温区	579.82	8.81	918.23	13.94

热力等级	年份	PD	LPI	SHAPE_AM	COHESION
低温区	2000	1.82	3.52	7.41	98.70
低温区	2017	1.81	3.33	4.85	98.33
次低温区	2000	3.65	0.70	8.13	97.63
次低温区	2017	2.44	0.48	9.11	97.91
中温区	2000	2.65	24.53	98.69	99.82
中温区	2017	0.72	23.55	50.24	99.93
次高温区	2000	5.00	1.48	15.21	98.22
次高温区	2017	1.29	0.97	15.41	98.78
高温区	2000	1.18	0.61	5.08	97.60
高温区	2017	1.00	1.15	5.10	98.23

年份	NP	PD	SHAPE_AM	COHESION	SHDI	SHEI	AI
2000	93760	14.25	54.21	99.76	1.36	0.85	84.72
2017	47821.	7.27	39.49	99.74	1.47	0.76	88.25