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Retrieval of aerosol optical depth over urban area by coupling the characteristics of surface directional reflection

  • role： First author第一作者
  • Affiliation：

    CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China

    Shandong Key Laboratory of Coastal Environmental Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China

  • Email：xptian@yic.ac.cn
  • Introduction：田信鹏，研究方向为大气环境遥感。E-mail： xptian@yic.ac.cn
TIAN Xinpeng12,  
  • role： Corresponding author通信作者
  • Affiliation：

    CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China

    Shandong Key Laboratory of Coastal Environmental Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China

  • Email：zqgao@yic.ac.cn
  • Introduction：高志强，研究方向为定量遥感、海岸带遥感应用等。E-mail： zqgao@yic.ac.cn
GAO Zhiqiang12*,  
  • Affiliation：

    Peng Cheng Laboratory, Shenzhen 518055, China

LIU Qiang3,  
  • Affiliation：

    CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China

    Shandong Key Laboratory of Coastal Environmental Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China

WANG De12,  
  • Affiliation：

    CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China

    Shandong Key Laboratory of Coastal Environmental Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China

WANG Yueqi12

resumen

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 bi-hemispheric 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.

palabra clave

aerosol optical depth;surface anisotropy;kernel-driven BRDF model;MODIS;Landsat 8 OLI

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