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国土资源遥感  2018, Vol. 30 Issue (2): 138-146    DOI: 10.6046/gtzyyg.2018.02.19
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兰西城市群热环境格局多尺度研究
潘竟虎1(), 董磊磊1, 王娜云2, 杨紫金3
1.西北师范大学地理与环境科学学院,兰州 730070
2.南京师范大学地理科学学院,南京 210023
3.云南天地图信息技术股份有限公司,昆明 650034
A multiscale study of thermal environment pattern in Lanzhou-Xining agglomeration
Jinghu PAN1(), Leilei DONG1, Nayun WANG2, Zijin YANG3
1. College of Geographic and Environmental Science, Northwest Normal University, Lanzhou 730070, China
2. School of Geographic Science, Nanjing Normal University, Nanjing 210023, China
3. Yunnan Map World Information Technology Stock Co., Ltd., Kunming 650034,China
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摘要 

从不同空间尺度研究城市热环境的变化格局,可为城市人居环境建设提供科学参考。采用MODIS和Landsat TM/OLI/TIRS遥感影像反演地表温度(land surface temperature,LST),分别从宏观和微观尺度探索了兰西城市群热场的空间格局特征,分析了城市热岛效应在昼夜、季节和年份等不同时间尺度上的分布格局及变化特征。研究结果表明,大尺度下兰西城市群未存在明显的城市热岛效应,但中心城区内热岛效应的空间格局发生了较大变化,热场的空间格局及演变与城市空间扩展布局相一致; 兰州中心城区热岛比例指数呈现先增加后减小的变化趋势,西宁—海东中心城区热岛比例指数则呈现持续增长的态势; 河谷地段的LST低于周围黄土丘陵,主要受植被覆盖、太阳辐射时间和接收量的影响; LST与归一化差值植被指数(normalized difference vegetation index,NDVI)呈负相关关系,与归一化差值建筑用地指数(normalized difference building index,NDBI)呈正相关关系。

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潘竟虎
董磊磊
王娜云
杨紫金
关键词 城市热岛热岛效应河谷型城市兰西城市群    
Abstract

The study of the changing pattern of urban thermal environment from different spatial scales can provide a scientific reference for the construction of urban human settlements. On the basis of MODIS and Landsat TM/OLI/TIRS data, land surface temperature is retrieval. Spatial pattern of thermal field in Lanzhou-Xining agglomeration (LXA) was analyzed from macro scale and micro scale. Diurnal variation, seasonal variation, and annual variation of urban heat island effect of LXA were explored. The heat island ratio index was introduced to describe the variation characteristics of thermal field pattern in LXA from 1992 to 2015. The results show that, on the large scale, there is no obvious urban heat island effect in LXA, whereas the spatial pattern of urban heat island effect in internal areas of central urban region of Lanzhou and Xining-Haidong changed greatly from 1992 to 2015. The urban sprawl had a spatial consistency with the urban heat island extension. Specifically, the heat island ratio index first increased and then decreased in central urban area of Lanzhou, whereas the heat island ratio index continuously increased significantly in central urban area of Xining-Haidong. As a typical valley agglomeration, the temperature of central cities was lower than that of surrounding loess hilly regions. The main influence factors were vegetation and the duration and amount of solar radiation. It seems that the land surface temperature is negatively correlated with normalized difference vegetation index(NDVI) and positively correlated with normalized difference building index(NDBI).

Key wordsurban heat island    heat island effect    valley city    Lanzhou-Xining agglomeration.
收稿日期: 2016-10-08      出版日期: 2018-05-30
:  P463  
基金资助:甘肃省自然科学基金项目“近30 a兰西都市圈城市热岛效应演变、成因、模拟与调控的遥感研究”(编号: 1506RJZA117)
引用本文:   
潘竟虎, 董磊磊, 王娜云, 杨紫金. 兰西城市群热环境格局多尺度研究[J]. 国土资源遥感, 2018, 30(2): 138-146.
Jinghu PAN, Leilei DONG, Nayun WANG, Zijin YANG. A multiscale study of thermal environment pattern in Lanzhou-Xining agglomeration. Remote Sensing for Land & Resources, 2018, 30(2): 138-146.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/gtzyyg.2018.02.19      或      https://www.gtzyyg.com/CN/Y2018/V30/I2/138
Fig.1  兰西城市群位置示意图
LST等级 温度范围
低温 Ti<Tmean-2.5Ts
较低温 Tmean-2.5TsTi<Tmean-1.5Ts
次中温 Tmean-1.5TsTi<Tmean-0.5Ts
中温 Tmean-0.5TsTi< Tmean+0.5Ts
次高温 Tmean+0.5TsTi<Tmean+1.5Ts
高温 Tmean+1.5TsTi<Tmean+2.5Ts
特高温 TiTmean+2.5Ts
Tab.1  LST等级区间划分标准
Fig.2-1  白天平均LST空间分布
Fig.2-1  白天平均LST空间分布
Fig.3  夜间平均LST空间分布
Fig.4  四季白天LST空间分布
Fig.5  四季夜间LST空间分布
Fig.6  兰州中心城区LST空间分布
Fig.7  西宁—海东中心城区LST空间分布
Fig.8  兰州中心城区2015年08月14日LST与NDVI和NDBI的相关关系
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