| 杭州村镇下垫面遥感指数与地表温度的相关性 |
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| 引用本文： | 金嘉乐,孙剑,杨利斌,董程锋,齐锋.杭州村镇下垫面遥感指数与地表温度的相关性[J].浙江农林大学学报,2020,37(3):563-570. |
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| 作者姓名： | 金嘉乐 孙剑 杨利斌 董程锋 齐锋 |
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| 作者单位： | 1.浙江农林大学 环境与资源学院，浙江 杭州 3113002.浙江农林大学 风景园林与建筑学院，浙江 杭州 311300 |
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| 基金项目： | 国家自然科学基金资助项目(51978627)；浙江省自然科学基金资助项目(LY19E080024)；国家大学生创新项目(201910341034)；浙江农林大学大学生创新项目(KX20180142) |
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| 摘 要： | 目的 分析不同类型村镇下垫面特征与地表温度(LST)的相关关系，对明晰村镇热环境的影响规律具有重要意义。 方法 利用单通道算法反演村镇的下垫面温度，针对遥感数据不同波段的特性计算了归一化植被指数(NDVI)、归一化建筑指数(NDBI)、不透水面信息指数(NDISI)、归一化水汽指数(NDMI)和改进型归一化差异水体指数(MNDWI)。基于杭州市夏、冬两季的地表温度及遥感指数计算结果，统计分析不同类型村镇下垫面两者间的线性相关性。 结果 地表温度与NDVI呈显著负相关，与NDBI呈显著正相关，与NDMI呈显著负相关。NDMI和NDBI对地表温度的影响大于NDVI，NDISI和MNDWI对地表温度的影响则相对更小；冬季地表温度与遥感指数的相关性弱于夏季。 结论 降低建筑密度，提高下垫面湿度和植被覆盖度都有利于降低村镇夏季地表温度，优化村镇热环境。图7表2参27
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| 关 键 词： | 景观生态学 村镇 地表遥感指数 地表温度 相关性 |
| 收稿时间： | 2019-06-24 |
Correlation between the remote sensing index of the underlying surface and the surface temperature in the villages in Hangzhou |
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| JIN Jiale,SUN Jian,YANG Libin,DONG Chengfeng,QI Feng.Correlation between the remote sensing index of the underlying surface and the surface temperature in the villages in Hangzhou[J].Journal of Zhejiang A&F University,2020,37(3):563-570. |
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| Authors: | JIN Jiale SUN Jian YANG Libin DONG Chengfeng QI Feng |
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| Affiliation: | 1.Collage of Environmental and Resource Sciences, Zhejiang A&F University, Hangzhou 311300, Zhejiang, China2.School of Landscape Architecture, Zhejiang A&F University, Hangzhou 311300, Zhejiang, China |
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| Abstract: | Objective In order to figure out how the underlying surface influences the thermal environment of villages and towns, the current study is aimed at a further analysis of the correlation between the characteristics of the underlying surface and the surface temperature of various villages and towns. Method First, single-channel algorithm was used to invert the underlying surface temperature of villages and towns. Then, based on the the features of different wave bands of remote sensing data, the normalized difference vegetation index (NDVI), normalized difference build-up index(NDBI), normalized difference impervious surface index(NDISI), normalized difference moisture index(NDMI) and modified normalized difference water index(MNDWI) were calculated. Lastly, on the basis of the results of surface temperature and remote sensing index in summer and winter in Hangzhou, a statistic analysis was conducted of the linear correlation between the characteristics of the underlying surface and the surface temperature of different types of villages and towns. Result The land surface temperature had a significant negative correlation with NDVI and NDMI; but a significant positive correlation with NDBI. The influence of NDMI and NDBI on surface temperature was greater than that of NDVI index, while the influence of NDISI and MNDWI on surface temperature was relatively weaker. The correlation between land surface temperature and surface remote sensing index in winter was weaker than in summer. Conclusion Reducing the building density, improving the underlying surface humidity and increasing vegetation coverage were all conducive to the reduction of the surface temperature of villages and towns in summer and the optimization of the thermal environment of villages and towns. Ch, 7 fig. 2 tab. 27 ref.] |
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