Dynamic analysis of landscape drivers in the thermal environment of Guanzhong plain urban agglomeration

Long Chen , Heng Li , Chunxiao Zhang , Wenhao Chu , Jonathan Corcoran , Tianbao Wang
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Abstract

Climate change caused by rapid urbanization in the Guanzhong region of China is becoming an increasingly significant problem. Previous empirical studies have confirmed that landscape patterns inextricably linked with the thermal environment, but static results based on a single temporal cross section of image data provide only a partial understanding. In this paper, we constructed a dynamic framework using Weather Research and Forecasting Model (WRF) for temperature simulation and Geodetector to study the landscape factors and their interactions that influence near-surface temperature (NST) changes in the Guanzhong Plain Urban Agglomeration (GPUA) between 2000 and 2020. Results showed that the GPUA average NST increased by 0.012 °C and 0.053 °C in January and July from 2000 to 2020, respectively. In terms of the dynamic correlation between landscape patterns and NST, cropland (CPL) was negative, urban land (UBL) was positive, and the remainder of the landscapes differed in winter and summer. Furthermore, results from the Geodetector showed that UBL embodied a stronger influence in summer than during winter months. This finding helps to explain why the average NST increase is higher in summer than during winter. The Dynamic Q values (DQ) of the area-based landscape metrics were generally larger than those of other spatial configuration metrics, and the interaction results showed that the landscape metrics of various land-cover classifications were enhanced, indicating that the superposition effect among landscape metrics needs to be taken into account in landscape planning in addition to area factors. The study of the relationship between landscape patterns and thermal environment considering dynamic perspective using WRF offers an important theoretical reference allied with practical guidance for understanding and adapting to forthcoming change in our climate through which we can help drive sustainable development decisions of the GPUA.
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关中平原城市群热环境景观动因动态分析
中国关中地区因快速城市化而导致的气候变化正成为一个日益严重的问题。以往的实证研究证实,景观格局与热环境密不可分,但基于单一时间截面图像数据的静态结果只能提供部分认识。在本文中,我们利用天气研究与预报模型(WRF)进行温度模拟,并利用 Geodetector 构建了一个动态框架,以研究影响关中平原城市群 2000-2020 年间近地面温度(NST)变化的景观因素及其相互作用。结果表明,2000-2020年关中平原城市群1月和7月平均近地面温度分别上升了0.012 ℃和0.053 ℃。从景观格局与 NST 的动态相关性来看,耕地(CPL)为负,城市用地(UBL)为正,其余景观在冬季和夏季存在差异。此外,Geodetector 的结果表明,UBL 在夏季比冬季的影响更大。这一发现有助于解释为什么夏季的 NST 平均增幅高于冬季。基于面积的景观指标的动态 Q 值(DQ)普遍大于其他空间配置指标的动态 Q 值,交互结果表明,不同土地覆被分类的景观指标得到了增强,这表明在景观规划中除了考虑面积因素外,还需要考虑景观指标之间的叠加效应。利用 WRF 从动态角度研究景观格局与热环境之间的关系,为理解和适应即将到来的气候变化提供了重要的理论参考和实践指导,有助于推动 GPUA 的可持续发展决策。
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来源期刊
International journal of applied earth observation and geoinformation : ITC journal
International journal of applied earth observation and geoinformation : ITC journal Global and Planetary Change, Management, Monitoring, Policy and Law, Earth-Surface Processes, Computers in Earth Sciences
CiteScore
12.00
自引率
0.00%
发文量
0
审稿时长
77 days
期刊介绍: The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.
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