| 基于Landsat数据的关中盆地腹地AOD时空格局及城市化对其影响 |
| 摘要点击 2392 全文点击 757 投稿时间：2020-10-07 修订日期：2020-11-19 |
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| 中文关键词 气溶胶光学厚度(AOD) 深蓝算法(DB) 经验正交函数分析方法(EOF) 时空变化 城市化 |
| 英文关键词 aerosol optical depth (AOD) deep blue algorithm (DB) empirical orthogonal function (EOF) spatial and temporal changes urbanization |
| 作者 | 单位 | E-mail | | 郑玉蓉 | 西北大学城市与环境学院, 西安 710127
西北大学陕西省地表系统与环境承载力重点实验室, 西安 710127
西北大学陕西西安城市生态系统定位观测研究站, 西安 710127 | 3246671038@qq.com | | 王旭红 | 西北大学城市与环境学院, 西安 710127
西北大学陕西省地表系统与环境承载力重点实验室, 西安 710127
西北大学陕西西安城市生态系统定位观测研究站, 西安 710127 | jqy_wxh@nwu.edu.cn | | 张秀 | 西北大学城市与环境学院, 西安 710127
西北大学陕西省地表系统与环境承载力重点实验室, 西安 710127
西北大学陕西西安城市生态系统定位观测研究站, 西安 710127 | | | 胡贵贵 | 西北大学城市与环境学院, 西安 710127
西北大学陕西省地表系统与环境承载力重点实验室, 西安 710127 | | | 梁秀娟 | 西北大学城市与环境学院, 西安 710127
西北大学陕西省地表系统与环境承载力重点实验室, 西安 710127
西北大学陕西西安城市生态系统定位观测研究站, 西安 710127 | | | 牛林芝 | 西北大学城市与环境学院, 西安 710127
西北大学陕西省地表系统与环境承载力重点实验室, 西安 710127
西北大学陕西西安城市生态系统定位观测研究站, 西安 710127 | | | 韩海青 | 西北大学城市与环境学院, 西安 710127
西北大学陕西省地表系统与环境承载力重点实验室, 西安 710127
西北大学陕西西安城市生态系统定位观测研究站, 西安 710127 | |
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| 中文摘要 |
| 气溶胶光学厚度（aerosol optical depth，AOD）是气溶胶最基本的光学特性之一，表征气溶胶对光的消减作用，对区域大气污染有一定的指示作用.首先，以2000~2019年长时间序列MOD09A1产品数据为基础，利用ASTER波谱数据库，构建了Landsat TM/OLI蓝光波段地表反射率数据集，利用深蓝算法（deep blue algorithm，DB）对关中盆地腹地AOD进行了反演估算.其次，通过测算2000~2019多年平均/各年平均AOD和季节AOD值，研究分析了AOD空间分布特征和时间变化趋势；利用经验正交函数分析方法（empirical orthogonal function，EOF）剖析了AOD主要的空间分布模式.最后，探索分析了城市化对AOD时空分布特征的影响.结果表明：①研究区多年平均AOD空间分布受地形和人类活动影响显著，低海拔且人类活动强度大的盆地内部AOD值和变化幅度均高于周围山系.AOD呈现出明显的季节差异性：春季（0.34） > 夏季（0.33） > 秋季（0.23） > 冬季（0.12），夏季AOD区域差异性最大.②年均AOD呈先增大后减小再增大的变化趋势，2005年达到最大值；春夏两季AOD数值分布离散，而冬季则表现为低值集聚的状态.③EOF分析结果表明，研究区AOD存在3种主要的空间分布模态：第一，AOD空间分布模式表现为区域一致型，特征向量空间分布与海拔梯度一致，反映了不同海拔下AOD变化程度的差异；第二，以秦岭山脉为界，大致呈现南北反相的分布特征，反映出关中盆地地域发展的独特性和与南部秦岭山区的差异性；第三，"东南-西北"的分布格局，表明了AOD在"城镇-乡村"呈反相变化趋势；④研究区AOD值与常住人口密度（R2=0.707，P<0.05）、不透水面密度（R2=0.377，P<0.05）以及工业POI密度（R2=0.727，P<0.5）呈正相关关系，说明城市化对AOD时空分布有一定影响.本研究对加强关中盆地空气质量监测和城市生态环境建设具有重要的意义. |
| 英文摘要 |
| Aerosol optical depth (AOD) is one of the most fundamental optical properties of aerosols that characterizes the attenuation of light by aerosols and is an indicator of regional air pollution. Based on the blue band surface reflectance database from the MOD09A1 products for the period 2000-2019 and the ASTER spectral database, AOD was estimated from Landsat TM/OLI data using the deep blue algorithm (DB). Multi-year average/annual average and seasonal AOD values for the period 2000-2019 were then calculated to analyze the spatial characteristics and temporal variations of AOD using the empirical orthogonal function method (EOF). Furthermore, the impacts of urbanization on the spatio-temporal distribution of AOD were analyzed. The obtained results are summarized as follows:① The multi-year average AOD spatial distribution in the hinterland of the Guanzhong Basin was significantly affected by topography and human activities, with higher AOD values and variationsin areas of low altitude and high-intensity human activities compared to the surrounding mountains. Thus, changes in AOD in the study area are mainly affected by anthropogenic factors. AOD also showed significant seasonal variations, whereby spring (0.34) > summer (0.33) > autumn (0.23) > winter (0.12), and the largest regional differences occurred in summer; ② The annual average AOD (from 2000-2019) showed the trend of "increase-decrease-increase", and reached a maximum in 2005, with the high AOD area gradually moving to the south. The distribution of AOD values in spring and summer was relatively discrete, while it is in a low-value agglomeration state in winter; ③ Three main AOD spatial distribution modes were identified based on the EOF, which had cumulative contribution rate of 83.0%. The spatial distribution trend of AOD showed regional consistency, with feature vectors consistent with the altitude, thus reflecting the difference of AOD at different altitudes. Taking the Qinling Mountains as the dividing line, the AOD presented the "north-south" pattern, AOD showed a "north-south" pattern, reflecting the uniqueness of the regional development in the Guanzhong Basin compared to the southern Qinling Mountains. The "southeast-northwest" distribution pattern indicated that the AOD presented a reverse change trend between urban and non-urban; and ④ The results of correlation analysis between the AOD and urbanization revealed a positive correlation with permanent population density (R2=0.707, P<0.05), impervious surface density (R2=0.377, P<0.05), and industrial POI density (R2=0.727, P<0.5). These results are significant for improving the monitoring of air quality in the Guanzhong Basin and for the construction of an urban ecological environment. |
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