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Assessing the effect of green cover spatial patterns on urban land surface temperature using landscape metrics approach

机译:利用景观度量方法评估绿化空间格局对城市地表温度的影响

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摘要

The present study was aimed to investigate how and to what extent urban land surface temperature (ULST) is affected by spatial pattern of green cover patch in an urban ambient in Isfahan, Iran. To materialize the effects of spatial pattern of green cover on ULST, Landsat ETM+image data on May 5, 2002 was acquired to be processed for ULST estimation and to generate Land Use/Land Cover (LULC) classes. Given to five percent of total available cells with a randomized distribution across the built-up areas, the linkage between ULST and composition, configuration and structure of green cover class was quantified. Five patch level landscape metrics including nearest distance (ND), patch area (AREA), perimeter to area (PARA), shape index (SHAPE) and core area index (CAI) were chosen and applied as explaining variables in statistical analyses due to their potential effects on ULST. Results of the present study have revealed that all the landscape metrics values of the green cover class were significantly correlated to their nearest ULST sample points, amongst which a stronger linkage was observed between ND (r=0.611, p <0.05) and ULST compared to others. Stepwise generalized additive modeling method-based multiple linear regression model was then fitted to dataset and resulted in developing the model (r~2= 0.41, p <0.05), explaining the relationship between spatial pattern of green cover and ULST. Finally, we concluded that the present study could provide additional level of knowledge through which urban planners can optimize composition, configuration and structure of green cover patches to mitigate the adverse impacts of LST phenomenon especially where urbanization is still ongoing.
机译:本研究旨在调查伊朗伊斯法罕的城市环境中绿化覆盖斑块的空间格局对城市地表温度(ULST)的影响程度以及影响程度。为了实现绿色覆盖的空间格局对ULST的影响,已获取2002年5月5日的Landsat ETM +图像数据以进行ULST估计,并生成土地利用/土地覆盖(LULC)类。假设有5%的可用单元在整个建筑区域内具有随机分布,则可以量化ULST与绿色覆盖类别的组成,配置和结构之间的联系。选择了五个补丁级别景观度量标准,包括最近距离(ND),补丁区域(AREA),周长到区域(PARA),形状指数(SHAPE)和核心区域指数(CAI),并将其用作统计分析中的解释变量对ULST的潜在影响。本研究结果表明,绿色覆盖类别的所有景观度量值均与其最接近的ULST采样点显着相关,其中与相比,ND(r = 0.611,p <0.05)与ULST之间的联系更为紧密。其他。然后将基于逐步广义加法建模方法的多元线性回归模型拟合到数据集,并进行了模型开发(r〜2 = 0.41,p <0.05),解释了绿色覆盖物的空间格局与ULST之间的关系。最后,我们得出的结论是,本研究可以提供更多的知识水平,城市规划者可以通过这些知识来优化绿化覆盖区的组成,配置和结构,以减轻LST现象的不利影响,尤其是在城市化仍在进行的地方。

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