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Analysis of remotely-sensed ecological indexes' influence on urban thermal environment dynamic using an integrated ecological index: a case study of Xi'an, China

机译:综合生态指数分析远程感知生态指标对城市热环境动态的影响 - 以西安西安市为例

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摘要

The spatio-temporal pattern of surface ecological status affects urban thermal environment distribution significantly. Urban thermal pattern, however, is a complicated physical phenomenon involving a series of terrestrial environmental parameters. Thus, it is insufficient to employ only one ecological parameter for depicting the variation of land surface temperature (LST). This paper begins with the analysis of four ecological parameters' influence on LST using regression analysis, based on 24 Landsat images which cover Xi'an of China from 1992 to 2014. These four parameters include greenness degree (i.e. the soil adjusted vegetation index, SAVI), soil moisture degree (i.e. the normalized difference moisture index, NDMI), dryness degree (i.e. the normalized difference soil index, NDSI) and resident aggregation degree (i.e. the normalized difference build-up index, NDBI). Besides, contribution intensity index was introduced to investigate the contribution effect of four ecological parameters on LST, and a new ecological index, integrated ecological index (IEI), was founded using the principal component analysis technique to integratedly represent its spatial and mathematical correlations with LST. Results indicate that four ecological parameters all possessed pronounced performance in impacting LST pattern in all dates: SAVI and NDMI were found to be correlated negatively with LST, whereas NDBI and NDSI correlated positively with LST. Additionally, SAVI had a profound impact on LST distribution compared with the other three parameters, and there was the biggest heating contribution in the lowest SAVI category. Further finding suggests that IEI as a new ecological index can be used to integratedly estimate the spatio-temporal change of LST, manifesting a negative correlation with LST. Our study thinks that the comprehensive characterization of surface ecological status is conducive to benefit us to better understand the spatio-temporal mechanism of thermal environment and ecosystem and to help urban decision-makers to execute effective conservation policies for the ecosystem.
机译:表面生态状态的时空模式显着影响城市热环境分布。然而,城市热模式是一种复杂的物理现象,涉及一系列陆地环境参数。因此,不足以仅使用一种用于描绘陆地温度(LST)的变化的生态参数。本文始于采用回归分析对LST的四种生态参数影响的分析,基于1992年至2014年的西安覆盖Xi'an。这四个参数包括绿色学位(即土壤调整后植被指数,Savi ),土壤湿度(即标准化差异湿度指数,NDMI),干燥度(即归一化差异土壤指数,NDSI)和常规聚集度(即标准化差异累积指数,NDBI)。此外,还引入了贡献强度指数来研究四个生态参数对LST的贡献效果,以及新的生态指数,综合生态指数(IEI),采用主成分分析技术综合地代表其与LST的空间和数学相关性。 。结果表明,在所有日期中,四个生态参数都具有影响LST模式的明显性能:SAVI和NDMI与LST负相关,而NDBI和NDSI与LST正面相关。此外,与其他三个参数相比,Savi对LST分布产生了深远的影响,最低的Savi类别中最大的供热贡献。进一步的发现表明,IEI作为一种新的生态指数可用于综合估计LST的时空变化,表现出与LST的负相关。我们的研究认为,表面生态地位的全面表征有利于使我们更好地了解热环境和生态系统的时空机制,并帮助城市决策者为生态系统执行有效的保护政策。

著录项

  • 来源
    《International journal of remote sensing》 |2019年第10期|3421-3447|共27页
  • 作者单位

    Northwest Univ Coll Urban & Environm Sci Xuefu Rd 1 Xian 710127 Shaanxi Peoples R China|Northwest Univ Shaanxi Key Lab Earth Surface Syst & Environm Car Xian Shaanxi Peoples R China;

    Northwest Univ Coll Urban & Environm Sci Xuefu Rd 1 Xian 710127 Shaanxi Peoples R China|Northwest Univ Shaanxi Key Lab Earth Surface Syst & Environm Car Xian Shaanxi Peoples R China;

    Northwest Univ Coll Urban & Environm Sci Xuefu Rd 1 Xian 710127 Shaanxi Peoples R China|Northwest Univ Shaanxi Key Lab Earth Surface Syst & Environm Car Xian Shaanxi Peoples R China;

    Northwest Univ Coll Urban & Environm Sci Xuefu Rd 1 Xian 710127 Shaanxi Peoples R China|Northwest Univ Shaanxi Key Lab Earth Surface Syst & Environm Car Xian Shaanxi Peoples R China;

    Northwest Univ Coll Urban & Environm Sci Xuefu Rd 1 Xian 710127 Shaanxi Peoples R China|Northwest Univ Shaanxi Key Lab Earth Surface Syst & Environm Car Xian Shaanxi Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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