厦门市绿色植被降温服务功能核算及其时空动态特征

赵伟; 文凤平; 张林波; 高艳妮; 何珏霖

doi:10.13198/j.issn.1001-6929.2018.06.20

厦门市绿色植被降温服务功能核算及其时空动态特征

doi: 10.13198/j.issn.1001-6929.2018.06.20

赵伟^1,,
文凤平^{1, 2},
张林波³,
高艳妮³,
何珏霖⁴

1.
中国科学院·水利部成都山地灾害与环境研究所, 成都四川 610041
2.
中国科学院大学, 北京 10049
3.
中国环境科学研究院, 北京 100012
4.
成都理工大学地球科学学院, 成都四川 610059

基金项目:

国家生态文明试验区(福建)项目

中国科学院水利部成都山地灾害与环境研究所青年百人团队计划项目 SDSQB-2015-02

中国科学院青年创新促进会项目 2016333

详细信息

作者简介:
赵伟(1984-), 男, 江西上高人, 副研究员, 博士, 主要从事热红外定量遥感理论与方法研究, zhaow@imde.ac.cn

中图分类号: X87
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- 被引次数: 0
出版历程
- 收稿日期: 2018-03-02
- 修回日期: 2018-06-06
- 刊出日期: 2019-01-25

Quantifying the Cooling Effects of the Green Vegetation in Xiamen City and Its Dynamics

1.
Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
2.
University of Chinese Academy of Sciences, Beijing 100049, China
3.
Chinese Research Academy of Environmental Sciences, Beijing 100012, China
4.
College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China

Funds:

National Ecological Civilization Pilot Zone (Fujian Province) Program, China

Hundred Young Talents Program of the Institute of Mountain Hazards and Environment, China SDSQB-2015-02

Youth Innovation Promotion Association CAS, China 2016333

摘要

摘要: 为了准确核算厦门市绿色植被降温服务功能，收集厦门市2010年和2015年18个气象站点数据，采用30 m空间分辨率Landsat卫星数据和250 m空间分辨率、16 d合成的MODIS植被指数产品，在已有基于能量平衡估算模型的基础上，通过考虑植被覆盖及降温服务时长，构建了绿色植被降温服务功能核算的改进模型，并对厦门市2010—2015年绿色植被降温服务功能时空动态特征进行分析.结果表明：①改进模型能够较为准确且合理地描述绿色植被降温服务功能的时空变化特征.②厦门市北部山区由于高植被覆盖度降温服务功能高于南部城市建成区，而城市建成区中的城市绿地也具有明显的降温作用.③2010—2015年各区降温服务功能实物量整体呈增加趋势.其中，同安区降温服务功能实物量变化量最多，为166.12×10⁶ kW·h；湖里区变化量最少，为9.72×10⁶ kW·h；其余各区变化量都在40×10⁶~75×10⁶ kW·h范围内.④森林在降温服务中贡献最大，达60%以上.相比2010年，2015年降温服务功能实物量除了灌木林地变化率为-4.29%外，其余绿色植被类型均呈增长趋势，如森林和农田的增长率为11.97%、14.23%，草地和城市绿地的增长率为87.45%、92.11%.研究显示，厦门市2010—2015年的绿色植被降温服务功能总体呈明显增强趋势，其中城市绿地的降温服务功能增强尤为明显.
- 厦门市 /
- 降温服务功能 /
- 绿色植被 /
- Landsat /
- MODIS
Abstract: The vegetation cooling service is an important component in ecosystem services, playing a key role in regulating climate, especially for urban areas. To accurately evaluate the effects of green vegetation cooling service, an accounting model of cooling service was proposed with the use of meteorological data and multi-source remote sensing data based on previous assessing method. The method was successfully applied to assess the cooling services of the green vegetation surfaces in 2010 and 2015 in Xiamen City, China. The spatio-temporal analysis indicates that the region with more vegetation coverage in the north had significant cooling effects than the built-up area in the south, and the green space in the built-up area also had greater cooling effects. From 2010 to 2015, the physical volume of ecosystem cooling effects in all districts had a large increase. Tong'an District had the maximum change of 166.12×10⁶ kW·h, and Huli District had the minimum change of 9.72×10⁶ kW·h. The changes in other districts were between 40×10⁶ and 75×10⁶ kW·h. Forest contributed the most to the total cooling service, more than 60%. The growth rates for cooling service's physical volume of shrubbery, forest, farmland, grassland, and urban green space were -4.29%, 11.97%, 14.23%, 87.45% and 92.11% respectively. These results showed that the cooling service of the green vegetation increased in Xiamen city from 2010 to 2015, especially for the cooling service of urban green spaces.
- Xiamen City /
- cooling service /
- green vegetation /
- Landsat /
- MODIS

HTML全文

图 1 厦门市气象站点空间分布

Figure 1. Spatial distribution of meteorological stations in Xiamen City

下载: 全尺寸图片幻灯片

图 2 2010年和2015年厦门市绿色植被类型空间分布

Figure 2. Spatial distribution of the green vegetation types in 2010 and 2015 in Xiamen City

下载: 全尺寸图片幻灯片

图 3 2010年和2015年厦门市绿色植被降温服务功能实物量(以节约用电量表征)空间分布

Figure 3. Spatial distribution of physical volume (electricity saving) for green vegetation cooling service in 2010 and 2015 in Xiamen City

下载: 全尺寸图片幻灯片

图 4 2010年和2015年厦门市绿色植被降温服务时长空间分布

Figure 4. Duration of the cooling service provision for the green vegetation in 2010 and 2015 in Xiamen City

下载: 全尺寸图片幻灯片

图 5 2010年和2015年厦门市绿色植被降温幅度空间分布

Figure 5. Air temperature reduction of the cooling effects for the green vegetation in 2010 and 2015 in Xiamen City

下载: 全尺寸图片幻灯片

表 1 厦门市2010和2015年主要绿色植被类型面积统计

Table 1. Area statistics of the green vegetation types in 2010 and 2015 in Xiamen City

km²
绿色植被类型	2010年	2015年	变化量
针叶林	61.57	61.59	0.02
阔叶林	268.43	268.43	0.00
混交林	88.90	88.90	0.00
稀疏林	4.31	4.27	-0.04
灌木林	5.16	5.15	-0.01
草地	2.60	4.11	1.51
园地	144.42	139.47	-4.95
城市绿地	167.20	227.37	60.17

下载: 导出CSV

表 2 不同绿色植被类型最大降温幅度

Table 2. Maximum extent of temperature reduction for different green vegetation types

绿色植被类型	最大降温幅度/(℃/h)
常绿阔叶林	2.34
常绿针叶林	2.34
针阔混交林	2.34
稀疏林	2.34
灌木林地	1.60
草地	0.85
乔木园地	2.34
灌木园地	1.30
其他园地	0.85
乔木绿地	2.34
灌木绿地	1.30
草本绿地	0.85

下载: 导出CSV

表 3 厦门市各辖区绿色植被降温服务功能实物量

Table 3. Physical volume of the green vegetation cooling services in different districts of Xiamen City

辖区	降温服务功能实物量总量/(10⁶ kW·h)			降温服务功能实物量平均值/(10⁶ kW·h/km²)
辖区	2010年	2015年	变化量	2010年	2015年	变化量
厦门市	1 847.27	2 241.91	394.64	1.09	1.32	0.23
思明区	28.98	73.43	44.45	0.34	0.87	0.53
湖里区	4.29	14.00	9.72	0.06	0.19	0.13
集美区	311.42	360.62	49.19	1.14	1.31	0.18
海沧区	155.17	207.21	52.04	0.83	1.11	0.28
同安区	1 094.38	1 260.50	166.12	1.63	1.88	0.25
翔安区	253.03	326.15	73.12	0.61	0.79	0.18

下载: 导出CSV

表 4 厦门市各绿色植被类型降温服务功能实物量

Table 4. Physical volume of the cooling service for different green vegetation types in Xiamen City

绿色植被类型		降温服务功能实物量总量/(10⁶ kW·h)			降温服务功能实物量平均值/(10⁶ kW·h/km²)
绿色植被类型		2010年	2015年	变化量	2010年	2015年	变化量
森林	阔叶林	185.66	212.44	26.78	3.02	3.45	0.43
	针叶林	769.59	864.74	95.15	2.87	3.22	0.35
	针阔混交林	267.31	292.44	25.13	3.01	3.29	0.28
	稀疏林	9.55	9.98	0.43	2.22	2.34	0.12
	合计	1 232.11	1 379.60	147.49	2.91	3.26	0.35
灌木林地		7.00	6.70	-0.3	1.36	1.30	-0.06
草地		2.39	4.48	2.09	0.92	1.09	0.17
园地		401.43	458.57	57.14	2.78	3.29	0.51
城市绿地		204.35	392.57	188.22	1.22	1.73	0.51

下载: 导出CSV

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