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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Night and day: The influence and relative importance of urban characteristics on remotely sensed land surface temperature
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Night and day: The influence and relative importance of urban characteristics on remotely sensed land surface temperature

机译:夜晚:城市特色对远程感应陆地温度的影响及相对重要性

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摘要

The characteristics of urban land surfaces contribute to the urban heat island, and, in turn, can exacerbate the severity of heat wave impacts. However, the mechanisms and complex interactions in urban areas underlying land surface temperature are still being understood. Understanding these mechanisms is necessary to design strategies that mitigate land temperatures in our cities. Using the recently available night-time moderate-resolution thermal satellite imagery and employing advanced nonlinear statistical models, we seek to answer the question "What is the influence and relative importance of urban characteristics on land surface temperature, during both the day and night?" To answer this question, we analyze urban land surface temperature in four cities across the United States. We devise techniques for training and validating nonlinear statistical models on geostatistical data and use these models to assess the interdependent effects of urban characteristics on urban surface temperature. Our results suggest that vegetation and impervious surfaces are the most important urban characteristics associated with land surface temperature. While this may be expected, this is the first study to quantify this relationship for Landsat-resolution nighttime temperature estimates. Our results also demonstrate the potential for using nonlinear statistical analysis to investigate land surface temperature and its relationships with urban characteristics. Improved understanding of these relationships influencing both night and day land surface temperature will assist planners undertaking climate change adaptation and heat wave mitigation.
机译:城市陆地面积的特点为城市热岛有贡献,而且反过来会加剧热波影响的严重程度。然而,仍然被理解城市地区下面的城市地区的机制和复杂的相互作用。了解这些机制是设计减轻城市土地温度的策略所必需的。使用最近可用的夜间分辨率的热卫星图像和采用先进的非线性统计模型,我们寻求回答“城市特色对陆地温度的影响和相对重要的问题,在白天和夜晚?”为了回答这个问题,我们分析了美国四个城市的城市土地面积温度。我们设计了用于在地统计数据上培训和验证非线性统计模型的技术,并使用这些模型来评估城市特征对城市表面温度的相互依赖效果。我们的研究结果表明,植被和不渗透的表面是与土地表面温度相关的最重要的城市特征。虽然这可能是预期的,但这是第一项对Landsat分辨夜间温度估计量化这种关系的第一研究。我们的结果还展示了使用非线性统计分析来研究陆地表面温度及其与城市特征的关系的可能性。改善了这些关系影响夜晚和日陆面积温度的关系,将帮助策划者进行气候变化适应和热波缓解。

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