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The relationships between urban-rural temperature difference and vegetation in eight cities of the Great Plains

机译:大平原八个城市的城乡温差与植被的关系

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摘要

Interpreting the relationship between urban heat island (UHI) and urban vegetation is a basis for understanding the impacts of underlying surfaces on UHI. The calculation of UHI intensity (UHII) requires observations from paired stations in both urban and rural areas. Due to the limited number of paired meteorological stations, many studies have used remotely sensed land surface temperature, but these time-series land surface temperature data are often heavily affected by cloud cover and other factors. These factors, together with the algorithm for inversion of land surface temperature, lead to accuracy problems in detecting the UHII, especially in cities with weak UHII. Based on meteorological observations from the Oklahoma Mesonet, a world-class network, we quantified the UHII and trends in eight cities of the Great Plains, USA, where data from at least one pair of urban and rural meteorological stations were available. We examined the changes and variability in urban temperature, UHII, vegetation condition (as measured by enhanced vegetation index, EVI), and evapotranspiration (ET). We found that both UHI and urban cold islands (UCI) occurred among the eight cities during 2000-2014 (as measured by impervious surface area). Unlike what is generally considered, UHII in only three cities significantly decreased as EVI and ET increased (p0.1), indicating that the UHI or UCI cannot be completely explained simply from the perspective of the underlying surface. Increased vegetative cover (signaled by EVI) can increase ET, and thereby effectively mitigate the UHI. Each study station clearly showed that the underlying surface or vegetation affects urban-rural temperature, and that these factors should be considered during analysis of the UHI effect over time.
机译:解释城市热岛(UHI)与城市植被之间的关系是了解地下表面对UHI影响的基础。 UHI强度(UHII)的计算需要从城乡配对站点进行观测。由于成对的气象站数量有限,许多研究都使用了遥感的地表温度,但是这些时间序列的地表温度数据通常会受到云量和其他因素的严重影响。这些因素,再加上地表温度反演的算法,会导致检测UHII的准确性问题,特别是在UHII较弱的城市。根据世界一流网络俄克拉荷马气象台的气象观测结果,我们对美国大平原的八个城市的UHII和趋势进行了量化,那里至少有一对城市和农村气象站的数据可供使用。我们研究了城市温度,UHII,植被状况(通过增强的植被指数EVI衡量)和蒸散量(ET)的变化和变异性。我们发现,UHI和城市冷岛(UCI)在2000-2014年期间都发生在八个城市中(以不透水表面积衡量)。与通常认为的不同,只有三个城市的UHII随着EVI和ET的增加而显着下降(p <0.1),这表明UHI或UCI不能仅从底层表面的角度完全解释。增加的植物覆盖率(由EVI发出信号)可以增加ET,从而有效缓解UHI。每个研究站清楚地表明,其下垫面或植被会影响城乡温度,并且在分析UHI随时间变化时应考虑这些因素。

著录项

  • 来源
    《Frontiers of earth science》 |2019年第2期|290-302|共13页
  • 作者单位

    Henan Univ, Lab Geospatial Technol Middle & Lower Yellow Rive, Kaifeng 475004, Peoples R China|Univ Oklahoma, Ctr Spatial Anal, Dept Microbiol & Plant Biol, Norman, OK 73019 USA;

    Univ Oklahoma, Ctr Spatial Anal, Dept Microbiol & Plant Biol, Norman, OK 73019 USA|Fudan Univ, Minist Educ, Key Lab Biodivers Sci & Ecol Engn, Inst Biodivers Sci, Shanghai 200438, Peoples R China;

    Univ Oklahoma, Ctr Spatial Anal, Dept Microbiol & Plant Biol, Norman, OK 73019 USA;

    Henan Univ, Lab Geospatial Technol Middle & Lower Yellow Rive, Kaifeng 475004, Peoples R China;

    Henan Univ, Lab Geospatial Technol Middle & Lower Yellow Rive, Kaifeng 475004, Peoples R China;

    Henan Univ, Lab Geospatial Technol Middle & Lower Yellow Rive, Kaifeng 475004, Peoples R China;

    Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China;

    Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    urbanization; evapotranspiration; urban cold island; background climate; air temperature;

    机译:城市化;蒸散量;城市冷岛;背景气候;气温;

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