地球信息科学学报 ›› 2014, Vol. 16 ›› Issue (4): 592-601.doi: 10.3724/SP.J.1047.2014.00592

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河谷型城市热岛空间分布格局演变及对策——以西宁市区为例

贾伟(), 高小红*()   

  1. 青海师范大学生命与地理科学学院,青藏高原环境与资源教育部重点实验室,西宁 810008
  • 收稿日期:2013-11-07 修回日期:2014-02-19 出版日期:2014-07-10 发布日期:2014-07-10
  • 作者简介:

    作者简介:贾 伟(1988-),男,内蒙古人,硕士生,研究方向为遥感与地理信息系统应用。E-mail:jiawei1212@126.com

  • 基金资助:
    国家自然科学基金项目(40861022)

Analysis of Urban Heat Island Environment in a Valley City for Policy Formulation: A Case Study of Xining City in Qinghai Province of China

JIA Wei(), GAO Xiaohong*()   

  1. College of Life and Geographical Sciences, Key Laboratory of Ministry of Education on Environment and Resource in Qinghai-Tibetan Plateau, Qinghai Normal University, Xining 810008, China
  • Received:2013-11-07 Revised:2014-02-19 Online:2014-07-10 Published:2014-07-10
  • About author:

    *The author: CHEN Nan, E-mail:fjcn99@163.com

摘要:

城市热岛效应直接反映着城市的气候特征,这对于研究由城市化发展与环境改变引起的城市气温的变化及保护城市的生态环境具有重要的现实意义。本文利用Landsat TM影像、气象台站资料,基于GIS的空间分析技术及单窗算法,对河谷型城市西宁市的地表温度进行反演,分析了地表温度与NDVI、NDBI的空间对应关系。结果表明:西宁市存在明显的城市热岛效应,热场分布及延伸与西宁市空间扩展布局相一致,热岛范围呈逐年增长的趋势;低、中温区的热岛面积大幅度减少,高温区的热岛范围显著增加;热岛效应冬季最强,夏季次之,秋季有明显减弱的趋势。在河谷型城市的空间格局上,地表温度与NDVI呈负相关关系、与NDBI呈正相关关系。最后,依据热岛时空演化、成因分析和策略研究的思路,从不同角度提出了缓解城市热岛效应的措施和对策,为未来西宁市热环境的改善提供科学参考和决策支持。

关键词: 城市热岛, 单窗算法, 河谷型城市, 定量反演, 西宁市区

Abstract:

Urban thermal environment is an important part of urban ecosystem, and urban heat island (UHI) effect directly reflects the climate characteristics of the city. It has an important practical significance to analyze comprehensively the urban heat island for studying urban air temperature change resulting from urbanization and environment change, and protecting urban eco-environment .Taking the valley city of Xining as a case study area, six Landsat 5 TM scenes were adopted from USGS website, and meteorological station data were obtained from China Meteorological Data Sharing Service System respectively. Firstly, the six Landsat 5 TM scenes were preprocessed by using ArcGIS 10.0 and ENVI 5.0 and the meteorological station data was processed using EXCEL software. Secondly, based on mono-window algorithm, the land surface temperature (LST) of the study area was retrieved. Then, all LST retrieval results obtained from the six Landsat 5 TM scenes were normalized to 0-1 for comparing the temporal differences of varied urban heat island. Thirdly, all normalized results were divided into five equal interval levels based on density separation technology of ENVI 5.0 software. Finally, the correlations between LST and NDVI as well as LST and NDBI were analyzed respectively. The results show that an obvious urban heat island effect exists in Xining city from 1996 to 2011. In addition, the spatial distribution pattern and extension of the urban heat island is consistent with urban sprawl. The urban heat island area is respectively 54.2 km2 in August 1996, 85.9 km2 in July 2001, 147.1 km2 in July 2007, 166.7 km2 in March 2009, 148.9 km2 in July 2010, and 158.7 km2 in September 2011, showing an expanding trend from 1996 to 2011 in general. Specifically, the heat island area has reduced substantially in the low and medium LST sub-region, whereas the heat island area has increased significantly in the high LST sub-region. The heat island effect is the strongest in winter, and it decreases evidently in the summer, then the autumn. In the spatial pattern of valley city, the land surface temperature is negatively correlated with NDVI, and positively correlated with NDBI. According to the spatio-temporal evolution of urban heat island, with the adoption of analysis of causes and strategic thinking, the constructive strategies and measures to alleviate urban heat island effect are proposed from different aspects, thus providing a scientific reference for decision making to improve the thermal environment of Xining City in the future.

Key words: urban heat island, mono-window algorithm, quantitative inversion, Xining City, valley city