地表温度的时空模式及其对土地覆被变化的响应:四川盆地案例研究

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2023-12-01 DOI:10.1016/j.ejrs.2023.12.002
Dongming Yan , Huan Yu , Qing Xiang , Xiaoyu Xu
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引用次数: 0

摘要

地表温度(LST)是陆地环境相互作用过程中的一个关键地理参数,与改变地表能量平衡的土地覆被变化(LCC)直接相关。本研究重建了四川盆地 2003 年至 2019 年的地表温度数据,平均 R2 为 0.85(昼间)和 0.91(夜间),有效填补了缺失像素并减少了噪声成分。利用新兴热点分析(EHSA)和土地覆被转移矩阵分析了LST时空演变的多重模式以及对LCC的响应。结果表明,LST 热点集中在低海拔盆地底层,以零星热点为主。冷点主要分布在边缘高海拔山区,但主导模式随时间尺度的变化而变化。热点和冷点的最大比例分别出现在夏季(46%)和秋季(29%)。此外,LST 冷、热点的明显上升和下降趋势分别在西部平原和边缘山地最为突出,且分别在夏季和秋季覆盖范围最大。在 LCC 总面积中,耕地-森林(CF)、耕地-不透水(CI)和森林-耕地(FC)占 93.55%。其中,CI 显著促进了日间 LST 热点的聚集和上升趋势。CF和FC对昼间低温冷点的聚集和低温降温效果最强,其中CF的效果更好。这些信息可为区域规划和气候变化减缓措施提供参考。
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Spatiotemporal patterns of land surface temperature and their response to land cover change: A case study in Sichuan Basin

Land surface temperature (LST) is a critical geo-parameter in terrestrial environmental interaction processes, directly related to land cover change (LCC) which modifies surface energy balance. In this study, LST data from 2003 to 2019 were reconstructed in the Sichuan Basin with average R2 of 0.85 (daytime) and 0.91 (nighttime), effectively filling in the missing pixels and reducing the noise components. Emerging hot spot analysis (EHSA) and land cover transfer matrix were utilized to analyze the multi-patterns of LST spatiotemporal evolution and responses to LCC. Results indicate that LST hot spots are concentrated in low-altitude basin floor and are dominated by sporadic hot spots. Cold spots are mainly in marginal high-elevation mountains, but the dominant pattern varies with time scale. The largest proportions of hot and cold spots are found in summer (>46 %) and autumn (>29 %), respectively. Moreover, the significant upward and downward trends of LST cold and hot spots are most prominent in western plain and marginal mountains, respectively, and have the largest coverage in summer and autumn, respectively. In total LCC area, cropland-to-forest (CF), cropland-to-impervious (CI), and forest-to-cropland (FC) account for 93.55 %. Among them, CI significantly promotes the aggregation and upward trend of daytime LST hot spots. CF and FC have the strongest effect of aggregating LST cold spots and cooling LST in daytime, with CF being more effective. The information can serve as a reference for regional planning and climate change mitigation measures.

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4.30%
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567
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