耦合地表方向反射特性的城市地区气溶胶光学厚度遥感反演
文献类型：期刊论文
| 作者 | 田信鹏1,2; 高志强1,2 ; 刘强3; 王德1,2; 王跃启1,2
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| 刊名 | 遥感学报
 |
| 出版日期 | 2022 |
| 卷号 | 26期号:11页码:2219-2233 |
| 关键词 | 气溶胶光学厚度 地表方向反射 核驱动模型 MODIS Landsat 8 OLI |
| ISSN号 | 1007-4619 |
| 其他题名 | Retrieval of aerosol optical depth over urban area by coupling the characteristics of surface directional reflection |
| 文献子类 | 期刊论文 |
| 英文摘要 | Aerosols play an important role in determining the Earth's radiation budget and its impact on climate change. Aerosol optical depth (AOD) is a crucial fundamental parameter for meteorological observation and a basic optical property of aerosol derived from satellites. Over land, the aerosol contribution in satellite signals is small compared with the surface, making it difficult to separate the aerosol path radiance from satellite measurements, particularly over the urban area. In the past several decades, numerous different AOD retrieval algorithms have been proposed by using different satellite sensors, but most of them do not consider surface anisotropy. The main purpose of this work is to improve the accuracy of aerosol retrievals and reduce the uncertainty of the operational MODIS AOD products over mixed surfaces. On this basis, a new generic high-performance aerosol retrieval algorithm is presented and explained. The new method is developed by coupling the non-Lambertian atmospheric radiative transfer model and semiempirical linear kernel-driven BRDF model. First, an a priori surface BRDF shape parameter database is constructed using the daily MODIS BRDF/Albedo product by using penalized least square regression based on a 3D discrete cosine transform (DCT-PLS) method. Then, the estimation of surface reflectance, including bidirectional reflectance, directional to hemispheric reflectance, hemispheric to directional reflectance, and bihemispheric reflectance (also called white-sky albedo, WSA), is based on this database and kernel-driven BRDF model. The presented method is tested on the Landsat 8 OLI images around the Beijing area, which features highly heterogeneous surfaces and severe air pollution problems. AOD retrievals with 500 m resolution can be successfully obtained over dark and bright surfaces. An accuracy assessment of the new algorithm, WSA-derived and HARLS AOD retrievals against AERONET AOD, from the four selected stations indicated the superiority of new algorithm, which is reflected in the high PWE and low RMSE. The comparison results show that the new algorithm is in good agreement with ground-based AOD (R=0.911) compared with the WSA-derived and HARLS AOD retrievals. Furthermore, the new algorithm and MODIS aerosol algorithms have similar spatial patterns of AOD. The new algorithm significantly improves the accuracy of aerosol retrievals, which is verified by AERONET AOD data, especially over brighter surfaces, because surface anisotropy is considered in this algorithm. The new algorithm can provide a detailed AOD spatial distribution over mixed surfaces and shows high ability in capturing fine-scale features. The new algorithm and MAIAC AOD retrievals have a similar spread of uncertainty envelopes. However, the new algorithm AOD retrievals have a higher correlation and smaller RMSE than the MAIAC retrievals, and the number of collections with AERONET for the new algorithm is almost 1.5 times those for MAIAC. This new AOD retrieval algorithm can provide a possibility for high-precision urban aerosol remote sensing monitoring and solve other pressing issues, such as long-term trend analysis of urban aerosols and air quality conditions, especially in heavily polluted areas. Based on the collocated observations, the new algorithm achieved satisfactory retrieval accuracy. However, several issues remain to be solved in the future. First, the retrieval errors of the MODIS BRDF kernel parameters are also a major source of uncertainty. Second, more analyses of the aerosol models and model selection are required. Third, the application in other regions and sensors is required in further work to evaluate the applicability of new algorithm. |
| 语种 | 中文 |
| CSCD记录号 | CSCD:7365160 |
| 源URL | [http://ir.yic.ac.cn/handle/133337/34251]  |
| 专题 | 烟台海岸带研究所_中科院海岸带环境过程与生态修复重点实验室 烟台海岸带研究所_海岸带信息集成与综合管理实验室 |
| 作者单位 | 1.中国科学院烟台海岸带研究所海岸带环境过程与生态修复重点实验室,烟台264003; 2.中国科学院烟台海岸带研究所山东省海岸带环境过程重点实验室,烟台264003; 3.鹏成国家实验室,深圳518055 |
| 推荐引用方式 GB/T 7714 | 田信鹏,高志强,刘强,等. 耦合地表方向反射特性的城市地区气溶胶光学厚度遥感反演[J]. 遥感学报,2022,26(11):2219-2233. |
| APA | 田信鹏,高志强,刘强,王德,&王跃启.(2022).耦合地表方向反射特性的城市地区气溶胶光学厚度遥感反演.遥感学报,26(11),2219-2233. |
| MLA | 田信鹏,et al."耦合地表方向反射特性的城市地区气溶胶光学厚度遥感反演".遥感学报 26.11(2022):2219-2233. |
入库方式： OAI收割
来源：烟台海岸带研究所
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