山区气溶胶多角度偏振遥感地气解耦方法评估

摘要/Abstract

摘要： 山区复杂的地形特征会导致地表反射率估算误差增加，降低地气解耦精度，进而影响气溶胶反演精度。当前应用较广泛的反演方法有基于波段关系估算地表反射的暗目标算法 (DT)、基于区域地表反射率库的深蓝算法 (DB) 和基于双向反射分布函数 (BRDF)、双向偏振分布函数 (BPDF) 模型估算地表反射率的GRASP (Generalized retrieval of atmosphere and surface properties) 算法。为探究适合山区气溶胶遥感的地气解耦方法，利用地面气溶胶自动观测网 (AERONET) 气溶胶产品 (AOD_A) 对比分析了2005 年至2013 年间POLDER-3 (Polarization and directionality of the earth's reflectances) 的GRASP 气溶胶产品 (AOD_G)、中等分辨率成像光谱仪 (MODIS) 的DT 气溶胶产品 (AOD_DT) 和DB气溶胶产品 (AOD_DB) 在中国区域的精度。结果显示，非山区站点处AOD_G与AOD_A整体相关性最高 (R = 0.921)， AOD_DT 和AOD_DB 总体精度差异不大，但山区AOD_G 高于期望误差的比例达79.87%， AOD_DT 和 AOD_DB高估程度分别增加了近30%和20%。在河北兴隆和兰州大学半干旱气候与环境观测站 (SACOL) 两个山区站点分季节验证显示，植被覆盖度低的秋冬季节三种卫星产品精度均存在下降趋势，表明除去地表植被对反射率的影响后，山区地形影响了地气解耦精度。进一步分析显示，山区起伏地形对基于BRDF、BPDF模型的地气解耦方法影响较大；在山区等起伏地表上空，多角度观测的地表波段关系更有利于精确估算地表反射，而在城区BRDF、BPDF模型与波段关系估算地表反射的误差水平接近。研究结果为进一步优化多角度观测 (如高分五号DPC) 的山区气溶胶反演算法提供了新的方向。

关键词: 山区, 多角度偏振, 气溶胶光学厚度, 地气解耦

Abstract: The complex terrain characteristics of mountainous areas can increase the estimation error of surface reflectance, reduce the accuracy of land-atmospheric decoupling, and then affect the accuracy of aerosol retrieval. Currently, the widely used retrieval methods include the dark target algorithm (DT) based on the band relationship to estimate the surface reflectance, the deep blue algorithm (DB) based on the regional surface reflectance library, and the generalized retrieval of atmosphere and surface properties (GRASP) algorithm based on the bidirectional reflectance distribution function (BRDF) and bidirectional polarization distribution function (BPDF) model to estimate the surface reflectance. To explore the landatmospheric decoupling methods suitable for aerosol remote sensing in mountainous areas of China, the accuracy and applicability of GRASP aerosol optical depth (AOD_G) of polarization and directionality of the earth's reflectances (POLDER-3), DT aerosol optical depth (AOD_DT) and DB aerosol optical depth (AOD_DB) of moderate resolution imaging spectroradiometer (MODIS) in China from 2005 to 2013 were compared and analyzed using AErosol RObotic NETwork (AERONET) aerosol optical depth (AOD_A). The results show that the overall correlation between AOD_G and AOD_A at non-mountainous sites is the highest (with correlation coefficient R = 0.921), and the overall accuracy of AOD_DT and AOD_DB is not much different. However, the proportion of AOD_G higher than the expected error in mountainous areas is 79.87%, and the overestimation proportion of AOD_DT and AOD_DB increases by nearly 30% and 20%, respectively. Seasonal validation at two mountain sites, Xinglong in Hebei Province and Seimi-Arid Climate and Environment Observatory of Lanzhou University (SACOL), shows that the accuracy of all three satellite products tend to decrease in the autumn and winter seasons when the vegetation cover is low, indicating that the mountain topography can affect the accuracy of land-atmosphere decoupling after removing the influence of surface vegetation on reflectance. Further analysis shows that the mountainous terrain has a great influence on the land-atmosphere decoupling method based on BRDF and BPDF model. The multi-angle observation of surface band relationship is more conducive to accurate estimation of surface reflection over undulating surface such as mountainous areas, while there is no significant difference of estimating surface reflection between BRDF/BPDF models and band relationships in urban areas. The results provide a new direction for further optimizing the multi-angle observation (such as Gaofen-5 DPC) aerosol retrieval algorithm in mountainous areas.

Key words: mountainous areas, multi-angle polarization, aerosol optical depth, land-atmospheric decoupling

中图分类号:

P422

翟颖超, 王涵, 赵梅如, 陈科, 李林森 . 山区气溶胶多角度偏振遥感地气解耦方法评估[J]. 大气与环境光学学报, 2023, 18(4): 339-356.

ZHAI Yingchao , WANG Han , ZHAO Meiru , CHEN Ke , LI Linsen . Evalutaion of land-atmospheric decoupling methods for mountainous aerosol multi-angle polarization remote sensing[J]. Journal of Atmospheric and Environmental Optics, 2023, 18(4): 339-356.

参考文献 J

[1]	Jin J N, Zhao W J, Yang X C, et al. Validation and temporal spatial distribution analysis of MODIS and Himawari-8 fine
	mode aerosol products in Asia [J]. Acta Scientiae Circumstantiae, 2019, 39(4): 1066-1085.
	金囝囡, 赵文吉, 杨兴川, 等. 亚洲地区MODIS和Himawari-8 细模态气溶胶产品验证及其时空分布分析 [J]. 环境科学学
	报, 2019, 39(4): 1066-1085.
[2]	Kaufman Y J, Wald A E, Remer L A, et al. The MODIS 2.1 μm channel-correlation with visible reflectance for use in
	remote sensing of aerosol [J]. IEEE Transactions on Geoscience and Remote Sensing, 1997, 35(5): 1286-1298.
[3]	Kaufman Y J, Sendra C. Algorithm for automatic atmospheric corrections to visible and near-IR satellite imagery [J].
	International Journal of Remote Sensing, 1988, 9(8): 1357-1381.
[4]	Hsu N C, Tsay S C, King M D, et al. Aerosol properties over bright-reflecting source regions [J]. IEEE Transactions on
	Geoscience and Remote Sensing, 2004, 42(3): 557-569.
[5]	Deuzé J L, Bréon F M, Deschamps P Y, et al. Analysis of the POLDER (POLarization and directionality of earth's
	reflectances) airborne instrument observations over land surfaces [J]. Remote Sensing of Environment, 1993, 45(2): 137-154.
[6]	Duan M Z, Lv D R. Simultaneously retrieving aerosol optical depth and surface albedo over land from POLDER's multi-angle
	polarized measurements I: Theory and simulations [J]. Chinese Journal of Atmospheric Sciences, 2007, 31(5): 757-765.
	段民征, 吕达仁. 利用多角度POLDER偏振资料实现陆地上空大气气溶胶光学厚度和地表反照率的同时反演 I. 理论与
	模拟 [J]. 大气科学, 2007, 31(5): 757-765.
[7]	Sun X, Zhao H J. Retrieval algorithm for optical parameters of aerosol over land surface from POLDER data [J]. Acta Optica
	Sinica, 2009, 29(7): 1772-1777.
	孙夏, 赵慧洁. 基于POLDER数据反演陆地上空气溶胶光学特性 [J]. 光学学报, 2009, 29(7): 1772-1777.
[8]	Wang Z T, Chen L F, Li S S. The retrieval of AOD over land surfaces in China from PARASOL [J]. Remote Sensing
	Information, 2009, 24(6): 49-54.
	王中挺, 陈良富, 李莘莘. 利用PARASOL数据反演陆地气溶胶光学厚度 [J]. 遥感信息, 2009, 24(6): 49-54.
[9]	Dubovik O, Smirnov A, Holben B N, et al. Accuracy assessments of aerosol optical properties retrieved from Aerosol
	Robotic Network (AERONET) Sun and sky radiance measurements [J]. Journal of Geophysical Research: Atmospheres, 2000,
10	5(D8): 9791-9806.
[10]	Dubovik O, Sinyuk A, Lapyonok T, et al. Application of spheroid models to account for aerosol particle nonsphericity in
	remote sensing of desert dust [J]. Journal of Geophysical Research: Atmospheres, 2006, 111(D11): D11208.
[11]	Dubovik O, Herman M, Holdak A, et al. Statistically optimized inversion algorithm for enhanced retrieval of aerosol
	properties from spectral multi-angle polarimetric satellite observations [J]. Atmospheric Measurement Techniques, 2011, 4(5):
97	5-1018.
[12]	Chen C, Dubovik O, Fuertes D, et al. Validation of GRASP algorithm product from POLDER/PARASOL data and
	assessment of multi-angular polarimetry potential for aerosol monitoring [J]. Earth System Science Data, 2020, 12(4): 3573-
	3620.
[13]	Dubovik O, Li Z Q, Mishchenko M I, et al. Polarimetric remote sensing of atmospheric aerosols: Instruments,
	methodologies, results, and perspectives [J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2019, 224:
47	4-511.
[14]	Li Z Q, Hou W Z, Hong J, et al. Directional Polarimetric Camera (DPC): Monitoring aerosol spectral optical properties over
	land from satellite observation [J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2018, 218: 21-37.
[15]	Chen L F, Shang H Z, Fan M, et al. Mission overview of the GF-5 satellite for atmospheric parameter monitoring [J].
	National Remote Sensing Bulletin, 2021, 25(9): 1917-1931.
	陈良富, 尚华哲, 范萌, 等. 高分五号卫星大气参数探测综述 [J]. 遥感学报, 2021, 25(9): 1917-1931.
[16]	Hasekamp O P, Landgraf J. Retrieval of aerosol properties over land surfaces: Capabilities of multiple-viewing-angle intensity
	and polarization measurements [J]. Applied Optics, 2007, 46(16): 3332-3344.
[17]	Wang H, Yang L K, Du W B, et al. Inversion of aerosol optical depth over land surface from airborne polarimetric
	measurements [J]. Spectroscopy and Spectral Analysis, 2018, 38(4): 1019-1024.
	王涵, 杨磊库, 都伟冰, 等. 航空偏振遥感数据反演陆地上空气溶胶光学厚度 [J]. 光谱学与光谱分析, 2018, 38(4): 1019-
	1024.
[18]	Kaufman Y J, Tanré D, Remer L A, et al. Operational remote sensing of tropospheric aerosol over land from EOS moderate
	resolution imaging spectroradiometer [J]. Journal of Geophysical Research: Atmospheres, 1997, 102(D14): 17051-17067.
[19]	Levy R C, Remer L A, Mattoo S, et al. Second-generation operational algorithm: Retrieval of aerosol properties over land
	from inversion of Moderate Resolution Imaging Spectroradiometer spectral reflectance [J]. Journal of Geophysical Research:
	Atmospheres, 2007, 112(D13): D13211.
[20]	Hsu N C, Jeong M J, Bettenhausen C, et al. Enhanced Deep Blue aerosol retrieval algorithm: The second generation [J].
	Journal of Geophysical Research: Atmospheres, 2013, 118(16): 9296-9315.
[21]	Dubovik O, Lapyonok T, Litvinov P, et al. GRASP: A versatile algorithm for characterizing the atmosphere [J]. SPIE
	Newsroom, 2014, 25: 1-4.
[22]	Li X, Strahler A H. Geometric-optical bidirectional reflectance modeling of the discrete crown vegetation canopy: Effect of
	crown shape and mutual shadowing [J]. IEEE Transactions on Geoscience and Remote Sensing, 1992, 30(2): 276-292.
[23]	Roujean J L, Leroy M, Deschamps P Y. A bidirectional reflectance model of the Earth's surface for the correction of remote
	sensing data [J]. Journal of Geophysical Research: Atmospheres, 1992, 97(D18): 20455-20468.
[24]	Maignan F, Bréon F M, Fédèle E, et al. Polarized reflectances of natural surfaces: Spaceborne measurements and analytical
	modeling [J]. Remote Sensing of Environment, 2009, 113(12): 2642-2650.
[25]	Yan K, Li H L, Song W J, et al. Extending a linear kernel-driven BRDF model to realistically simulate reflectance anisotropy
	over rugged terrain [J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 1-16.
[26]	Shu C M, Sun X B, Wang H, et al. Model optimization of didirectional polarization reflectance distribution function of land
	surface based on airborne polarimetric data [J]. Journal of Atmospheric and Environmental Optics, 2016, 11(2): 125-133.
	舒存铭, 孙晓兵, 王涵, 等. 基于航空偏振数据的地表BPDF 模型优化研究 [J]. 大气与环境光学学报, 2016, 11(2):
12	5-133.
[27]	Waquet F, Léon J F, Cairns B, et al. Analysis of the spectral and angular response of the vegetated surface polarization for the
	purpose of aerosol remote sensing over land [J]. Applied Optics, 2009, 48(6): 1228-1236.
[28]	Holben B N, Eck T F, Slutsker I, et al. AERONET―A federated instrument network and data archive for aerosol
	characterization [J]. Remote Sensing of Environment, 1998, 66(1): 1-16.
[29]	Che H Z, Zhang X Y, Chen H B, et al. Instrument calibration and aerosol optical depth validation of the China Aerosol
	Remote Sensing Network [J]. Journal of Geophysical Research: Atmospheres, 2009, 114(D3): D03206.
[30]	Che H Z, Xia X G, Zhao H J, et al. Spatial distribution of aerosol microphysical and optical properties and direct radiative
	effect from the China Aerosol Remote Sensing Network [J]. Atmospheric Chemistry and Physics, 2019, 19(18): 11843-11864.
[31]	Li Z Q, Xu H, Li K T, et al. Comprehensive study of optical, physical, chemical, and radiative properties of total columnar
	atmospheric aerosols over China: An overview of Sun-sky radiometer observation network (SONET) measurements [J].
	Bulletin of the American Meteorological Society, 2018, 99(4): 739-755.
[32]	Wang L. A brief introduction to US shuttle radar topography mission [J]. Bulletin of Surveying and Mapping, 2000, (12):
38	-40.
	汪凌. 美国航天飞机雷达地形测绘使命简介 [J]. 测绘通报, 2000, (12): 38-40.
[33]	Sayer A M, Hsu N C, Lee J, et al. Validation of SOAR VIIRS over-water aerosol retrievals and context within the global
	satellite aerosol data record [J]. Journal of Geophysical Research: Atmospheres, 2018, 123(23): 13496-13526.
[34]	Sogacheva L, Popp T, Sayer A M, et al. Merging regional and global aerosol optical depth records from major available
	satellite products [J]. Atmospheric Chemistry and Physics, 2020, 20(4): 2031-2056.
[35]	Eck T F, Holben B N, Reid J S, et al. Wavelength dependence of the optical depth of biomass burning, urban, and desert
	dust aerosols [J]. Journal of Geophysical Research: Atmospheres, 1999, 104(D24): 31333-31349.
[36]	Tan Y, Li E, Zhang Z, et al. Validation of POLDER-3/GRASP aerosol products using AERONET measurements over China
[J]	Atmospheric Environment, 2019, 215: 116893.