城市环境中地表温度分布的形态特征:确定优先区域的方法

IF 3 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Climate Pub Date : 2023-12-28 DOI:10.3390/cli12010004
Karina Angélica García-Pardo, David Moreno-Rangel, Samuel Domínguez-Amarillo, José Roberto García-Chávez
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引用次数: 0

摘要

城市生物物理结构对城市地区环境过程的影响已得到证实,这就更加强调通过研究形态模式来确定城市气候条件的精确位置和根本原因。本研究旨在根据生物物理变量的先期分类,描述陆面温度(LST)分布的形态模式特征,生物物理变量包括城市密度(建筑密度和平均高度)、地表特征、太阳短波辐射(宽带反照率)以及植被覆盖的季节性变化(高、中、低水平),这些变量均从多源数据集中获取。为了描述 LST 的分布情况,对这些变量进行了计算和分类,随后对西班牙马德里一个城市街区的冬季和夏季 LST 值进行了单独和综合分析。通过比较分析方法(观测、相关性和多元回归)得出的结果来确定形态模式。从形态模式中选出的 LST 值最不利的区域,夏季的吻合度高达 89%,冬季的吻合度高达 70%,这表明所采用的方法在按季节确定优先干预区域方面是可行的。值得注意的是,与其他特征相比,低植被水平和高植被水平成为影响 LST 分布的关键生物物理特征,这强调了将详细的季节性植被变化纳入城市分析的重要性。
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Characterisation of Morphological Patterns for Land Surface Temperature Distribution in Urban Environments: An Approach to Identify Priority Areas
The validated influence of urban biophysical structure on environmental processes within urban areas has heightened the emphasis on studies examining morphological patterns to determine precise locations and underlying causes of urban climate conditions. The present study aims to characterise morphological patterns describing the distribution of Land Surface Temperature (LST) based on a prior classification of biophysical variables, including urban density (building intensity and average height), surface characteristics, shortwave solar radiation (broadband albedo), and seasonal variations in vegetation cover (high, medium, and low levels), retrieved from multisource datasets. To describe the distribution of LST, the variables were calculated, classified, and subsequently, analysed individually and collectively concerning winter and summer LST values applied in an urban neighbourhood in Madrid, Spain. The results from the analytical approaches (observation, correlations, and multiple regressions) were compared to define the morphological patterns. The selection of areas resulting from the morphological patterns with the most unfavourable LST values showed agreement of up to 89% in summer and up to 70% for winter, demonstrating the feasibility of the methods applied to identify priority areas for intervention by season. Notably, low and high vegetation levels emerged as pivotal biophysical characteristics influencing LST distribution compared to the other characteristics, emphasising the significance of integrating detailed seasonal vegetation variations in urban analyses.
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来源期刊
Climate
Climate Earth and Planetary Sciences-Atmospheric Science
CiteScore
5.50
自引率
5.40%
发文量
172
审稿时长
11 weeks
期刊介绍: Climate is an independent, international and multi-disciplinary open access journal focusing on climate processes of the earth, covering all scales and involving modelling and observation methods. The scope of Climate includes: Global climate Regional climate Urban climate Multiscale climate Polar climate Tropical climate Climate downscaling Climate process and sensitivity studies Climate dynamics Climate variability (Interseasonal, interannual to decadal) Feedbacks between local, regional, and global climate change Anthropogenic climate change Climate and monsoon Cloud and precipitation predictions Past, present, and projected climate change Hydroclimate.
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