利用PARASOL数据反演陆地气溶胶光学厚度

研究了利用PARASOL多角度偏振数据反演我国陆地气溶胶,假设单次散射在扣除大气分子和地表的偏振辐亮度后,根据气溶胶光学性质查找表,采用最佳匹配的方法,选择最适合的气溶胶模式,得到气溶胶光学厚度。并用AERONET的北京站和香河站的地基观测数据对结果进行了验证。结果表明,多角度偏振方法反演陆地气溶胶精度稳定,受季节和地表类型的影响很小,但精度较低还需作进一步的改进。     

基于高分五号DPC数据的细模态气溶胶光学厚度反演

偏振遥感技术监测细模态气溶胶光学物理特性的优势,是监测大区域大气污染的有效手段。基于高分五号（GF-5）携带的多角度偏振成像仪（DPC）的多角度偏振观测数据开展全球陆地上空的细模态气溶胶光学厚度（AOD_f）反演研究。主要通过地表二向偏振反射（BPDF）模型估算出地表偏振反射率,结合评价函数得出了最优气溶胶模型以及AOD_f反演结果,将反演结果与AERONET地基观测数据进行了对比验证。结果显示： 地基数据与反演结果相关性系数达到0.903,平均绝对误差,平均相对误差、均方根误差分别为0.026、0.43%、0.060,反演结果总体可靠,反演方法具备可行性。     

高分一号数据的气溶胶光学厚度反演和验证

针对高分辨率卫星遥感反演气溶胶光学厚度地表噪声难以分离的问题,利用国产"高分一号"(GF-1)的数据特点,提出了一种气溶胶光学厚度反演方法和处理流程。该方法分别基于暗像元和深蓝算法去除了浓密植被和城市亮目标地区的地表贡献,并应用于我国污染较为严重的京津冀、长三角、珠三角等示范区域。利用北京、杭州、香港AERONET地基观测数据,对GF-1反演得到的气溶胶光学厚度进行验证,结果表明:气溶胶高值均集中在三大区域工业排放大和人类活动密集的核心城市,年均光学厚度值在1左右。卫星和地基的相关性总体较好,三大区域的相关系数分别达到了0.71、0.55、0.54。受云识别、亮地表覆盖和气溶胶模式假设等影响,GF-1反演的气溶胶光学厚度存在一定程度的偏差。     

地表温度热红外遥感反演的研究现状及其发展趋势

区域性或全球性的地表温度, 只有通过遥感手段才能获得, 在诸多应用中是一个非常重要的参数。地表温度反演是热红外遥感研究的热点和难点之一, 大气校正、温度与比辐射率的分离是必须考虑的两个重要方面。近年来有关的研究非常多, 主要反演方法可分为5 类: 单通道方法、分裂窗(双波段) 方法、多波段温度- 比辐射率分离方法、多角度温度反演方法和多角度与多通道相结合的方法。这些方法都各有利弊, 如何提高反演的精度和模型的适用性是地表温度热红外遥感的未来发展趋势, 理论和实验相结合的多种信息源的综合应用成为必然的要求。     

基于深蓝算法的Sentinel-2数据气溶胶光学厚度反演

中高分辨率气溶胶信息对于高精度地表反射率反演以及城市空气环境质量监测具有重大意义,但在城市及稀疏植被等高亮地表区域,气溶胶光学厚度(AOD)的高精度反演一直是定量遥感领域的难点之一。以北京城市区和包头沙漠区为例,利用MODIS地表反射率产品构建先验知识约束条件,基于深蓝算法实现了13景Sentinel-2高亮地表的AOD反演。为验证算法精度,将反演结果与全球气溶胶自动观测网(AERONET)站点实测值、Sentinel-2官方插件Sen2Cor处理结果、Landsat-8反演值作对比。结果表明:①采用深蓝算法反演的AOD值与AERONET实测值具有显著的相关性(R^2>0.9,RMSE=0.056);②无论是沙漠高亮区还是植被较少的城市高亮区,Sen2Cor插件反演的AOD值整景均为固定值,无空间分布,不符合实际情况;③Sentinel-2深蓝算法反演结果与准同步过境的Landsat-8反演的AOD产品在空间分布上具有高度一致性,较好地反映了人类活动特征。相比于目前官方产品,深蓝算法适合Sentinel-2数据高亮区域的气溶胶反演,在绝对精度和空间分布趋势方面均具有明显优势。     

二向反射遥感反演最优角度采样方法研究

地物具有二向反射特性,可由二向反射分布函数（Bi-directional Reflectance Distribution Function, BRDF）刻画,它是光学定量遥感反演的基础。BRDF的反演依赖于多角度观测,由于卫星、航空和地基观测的角度有限,如何设计可行的稀疏角度采样,对实现BRDF的高质量反演至关重要。研究引入角度信息量,基于模型模拟和传感器观测的多角度数据,通过计算不同角度组合用于核驱动模型BRDF反演的角度信息量与反演误差,探究了角度信息量与反演误差之间的关系,确定了BRDF反演的最优观测平面和角度数目,进而得到不同太阳天顶角对应的优选角度组合。验证结果表明：优选出的角度组合在大多数地表上可实现高质量的BRDF反演。研究成果可为多角度观测实验、多角度卫星载荷设计以及地表二向反射反演提供重要参考。     

热红外遥感地表温度反演研究现状与发展趋势

从Planck函数和热红外辐射传输方程出发,概述了热红外遥感反演地表温度的基本原理,总结了当前反演地表温度常用到的热红外遥感器及相应波段。将热红外遥感地表温度反演算法分为单通道、劈窗和多通道3大类,分析了每一类中较具代表性算法的原理、适用条件及精确度。从热红外遥感机理、发射率、环境辐射、混合像元、大气影响等方面概述了热红外遥感反演地表温度面临的主要问题,并对热红外遥感地表温度反演的发展趋势进行了展望。     

利用Landsat-8 OLI反演大气气溶胶的可见光谱段地表反射率估算

准确估算地表反射率的贡献一直是遥感反演大气气溶胶光学厚度过程中的重点和难点。为了促进Landsat-8OLI传感器在地表参数定量化特别是大气遥感领域的应用,本文提出一种利用OLI 1.6μm、2.2μm短波红外谱段数据估算遥感影像可见光地表反射率的方法。该方法依托于MOD04产品地表反射率估算模式,通过光谱归一化和构建新的短波红外植被指数等过程,建立OLI地表反射率估算模式,通过误差分析发现该模式能够有效地降低由于传感器光谱响应不同对估算结果的影响,对应用在OLI遥感影像的计算结果与同时间同区域MOD04产品地表反射率进行比较,表明其结果有较高的相关性和可靠性。     

模拟配准误差对结构函数法气溶胶反演的影响

为了确定清晰图像和待反演图像间的配准误差对结构函数法气溶胶光学厚度反演结果的影响程度,该文基于辐射传输模型反演了不同配准误差条件下的气溶胶光学厚度。在已知地表反射率的基础上,利用辐射传输模型得到一定气溶胶光学厚度下的表观反射率,线性插值得到不同配准误差下的表观反射率,利用这些表观反射率和地表反射率反演气溶胶光学厚度;通过不同配准误差下的反演结果分析配准误差的影响,并通过统计反演误差小且不随配准误差改变的稳定像元地表反射率结构函数值和均值等特征得到稳定像元的地表特征。结果表明,配准误差结构函数法的反演结果显著影响,当配准误差小于0.2个像元时,反演误差小于0.2的像元占总像元的比例达63%。此外,研究发现,地表反射率结构函数值与相应计算窗口地表反射率的标准差相关性强,当标准差大于0.02时,反演结果受配准误差的影响相对较小,相对误差最大不超过40%;反之,受配准误差的影响较大。     

武汉地区环境卫星气溶胶光学厚度反演

针对难以及时、准确掌握中部地区气溶胶污染状况的问题,选用适用于城市等亮地表区域的结构函数法,结合环境一号A/B卫星CCD影像数据,开展武汉及周边地区气溶胶光学厚度反演研究。首先对卫星遥感数据进行预处理,然后根据结构函数法的原理和模型,选择了合适的结构函数公式、窗口范围和距离值。通过选取研究时间范围内的"清洁日",在原始影像预处理的基础上使用归一化植被指数剔除水体影响,实现环境一号卫星CCD影像的武汉地区气溶胶光学厚度反演。通过CE318实测数据、湖北省环保厅的大气污染数据、MODIS产品检验结果,对反演结果进行了对比验证,从精度、准确度、空间分布和时间分布趋势等方面验证了模型反演的可靠性。     

Toward aerosol optical depth retrievals over land from GOES visible radiances: determining surface reflectance

Frequent observations of aerosol over land are desirable for aviation, air pollution and health applications. Thus, a method is proposed here to correct surface effects and retrieve aerosol optical depth using visible reflectance measurements from the Geostationary Operational Environmental Satellite (GOES). The surface contribution is determined from temporal compositing of visible imagery, where darker pixels correspond to less atmospheric attenuation and surface reflectance is deduced from the composite using radiative transfer. The method is applied to GOES‐8 imagery over the eastern US. Retrieved surface reflectance is compared with separate retrievals using a priori ground‐based observations of aerosol optical depth. The results suggest that surface reflectances can be determined to within ±0.04. The composite‐derived surface reflectance is further analysed by retrieving aerosol optical depth and validating retrievals with Aerosol Robotic Network (AERONET) observations. This analysis indicates that the retrieved optical depth is least biased, hence the surface reflectance is most accurate, when the composite time period varies seasonally. Aerosol optical depth retrievals from this validation are within ±0.13 of AERONET observations and have a correlation coefficient of 0.72. While aerosol optical depth retrieval noise at low optical depths may be limiting, the retrieval accuracy is adequate for monitoring large outbreaks of aerosol events.     

Aerosol mapping over land with imaging spectroscopy using spectral autocorrelation

A new method for aerosol retrieval over land is proposed that makes explicit use of the contiguous, high-resolution spectral coverage of imaging spectrometers. The method is labelled Aerosol Retrieval by Interrelated Abundances (ARIA) and is based on unmixing of the short-wave infrared sensor signal by region-specific endmembers, assuming low aerosol radiative influence in this spectral region. Derived endmember abundances are transferred to the visible part of the spectrum in order to approximate surface reflectance where aerosol influence is generally strongest. Spectral autocorrelation of surface spectra is a precondition for ARIA and demonstrated using a reference spectrum database. The re-mixed surface reflectance is used as input quantity for the inversion of aerosol optical depth τ_a at 0.55 µm wavelength on a pixel basis. Except for the choice of endmembers and the atmospheric vertical profile, no a priori assumptions on the image scene are required. The potential of the presented method for aerosol retrieval is demonstrated for an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) scene, collected in California in 2000. Comparisons with existing aerosol retrieval methods showed encouraging results in terms of achieved spatial smoothness and degree of uncertainty of aerosol optical depth across the scene.     

An atmospheric correction procedure for the ATSR-2 visible and near-infrared land surface data

An atmospheric correction procedure for the solar reflecting channels of the Second Along Track Scanning Radiometer (ATSR-2) is described in which the aerosol optical thickness is retrieved from atmospheric simulations using the top-of-atmosphere (TOA) reflectances. The aerosol optical thickness is obtained when the ratio of the corresponding surface reflectances, in the off-nadir view to the nadir view, for two selected sensor channels, are equal. Directional reflectance models have been used to determine the validity of this approach and to determine suitable channel combinations. Simulations of the procedure for realistic surfaces indicate the retrieval of tau A 550 is better than 0.1 when the aerosol meteorology is known. The accuracy of the retrieval of surface reflectance is significantly affected by deviations from the expected aerosol meteorology. Factors affecting the accuracy of the correction procedure are described.     

Remote sensing of aerosols optical thickness over various sites using SeaWiFS or VEGETATION and ground measurements

A key problem in aerosol retrieval is to distinguish between surface and atmospheric contributions to the variability in the satellite signal. A major contribution in the surface-related variability is caused by the non-Lambertian nature of the Earth surface reflectance and the fact that the illumination/observation geometry varies considerably between successive observations of the same area (with a polar orbiting sensor). In principle, if the surface boundary condition can be specified with sufficient accuracy by means of a bidirectional reflectance distribution function (BRDF), the two contributions can be unfolded and aerosol information retrieved. This approach has been tested using combined datasets made of satellite measured “top of atmosphere” (TOA) radiance and corresponding ground estimation of the aerosol optical thickness. Studying a time series of data, taking into account geometrical conditions and assuming the ground BRDF to be constant during the time period, a coupled surface/atmosphere model was used to investigate the retrieval of aerosol optical thickness (AOT) over several sites. By fitting a subset of satellite observations associated with ground photometer data, a best fit of BRDF model parameters could be determined. This surface characterization is then used to reduce the model unknowns to AOT only and thereby to permit its retrieval from the satellite data alone, by means of a simple inversion process. The study was conducted on three European AERONET sites and using satellite data from both the VEGETATION and Sea viewing Wide Field of view (SeaWiFS) sensors. In all cases, the AOT retrieved from satellite was in good agreement with the measurements.     

Retrieval of AOD from Sentinel-2 Data based on Deep Blue Algorithm

Medium-to-high resolution aerosol information is of great significance for surface reflectance inversion and urban ambient air quality monitoring. However, the high-precision aerosol optical thickness (AOD) retrieval in bright areas, such as cities and sparse vegetation areas, has long plagued the quantitative remote sensing applications. Taking Beijing urban area and Baotou desert area as examples, using MODIS surface reflectance products to construct prior knowledge constraints, the AOD inversion of 13 scenes Sentinel-2 images in bright areas was realized based on the deep blue algorithm. To verify the accuracy of the algorithm, the result were compared with the Sentinel-2 official algorithm processing result, the Landsat-8 official aerosol products and the ground-measured AOD data from the Global Aerosol Automated Observing Network (AERONET). The results indicate that the retrieved AOD values from deep blue algorithm is significantly correlated with the measured value of AERONET(R² > 0.90, RMSE = 0.056 0), and the AOD spatial distributions are also well consistent with those from Landsat-8, which reflects the characteristics of human activities. But, whether in desert bright area or urban bright area with less vegetation, the AOD values retrieved by Sen2Cor plug-in are fixed, no spatial distribution and do not conform to the actual situation. In general, compared with the current official products, the deep blue algorithm is suitable for aerosol retrieval in high-brightness areas of Sentinel-2 data，and has obvious advantages in terms of estimation accuracy and spatial distribution trend.     

Influence of land surface effects on MODIS aerosol retrieval using the BAER method over Korea

As satellite receiving signals are affected by complex radiative transfer processes in the atmosphere and on land surfaces, aerosol retrieval over land from space requires the ability to determine surface reflectance from the remote measurements. To use the Bremen Aerosol Retrieval (BAER) method for aerosol optical thickness (AOT) retrieval over land at a spatial scale of 1×1 km² from Moderate Resolution Imaging Spectroradiometer (MODIS) data, a linear mixing model with a vegetation index was used to calculate surface reflectances. As the vegetation index is affected by the aerosol present in the atmosphere, an empirical linear relationship between short wavelength infrared (SWIR) channel reflectance and visible reflectance was estimated to calculate a modified aerosol free vegetation index (AFRI) value. Based on a modified AFRI obtained from MODIS SWIR channel reflectance, an improved linear mixing model was applied for aerosol retrieval. A comparison of results between calculated and apparent surface reflectance was satisfactory, with a linear fit slope above 0.94, correlation coefficients above 0.84, and standard deviation below 0.008 for the study area. These results can therefore be used for improved aerosol retrieval over land by the BAER method with MODIS Level 1 data.     

Ozone Monitoring Instrument aerosol products: a comparison study with ground-based airborne sun photometer measurements over Europe

Airborne sun photometer measurements are used to evaluate retrievals of extinction aerosol optical depth (AOD). These data are extracted from spatially coincident and temporally near-coincident measurements by the Ozone Monitoring Instrument (OMI) aboard the Aura satellite taken during 2005. OMI-measured top of atmosphere (TOA) reflectances are routinely inverted to yield aerosol products such as AOD using two different retrieval techniques: the Aura OMI Near-Ultraviolet Aerosol Data Product, OMAERUV, and the multi-wavelength Aura OMI Aerosol Data Product, OMAERO. In this work, we propose a study that specifically compares the instantaneous aerosol optical thicknesses retrieved from OMI at several locations containing sites and those of the Aerosol Robotic Network (AERONET). The result of the comparison shows that, just over Europe, OMI aerosol optical thicknesses are better retrieved in the multi-wavelength retrieval than in the near-ultraviolet. Correlations have been improved by applying a simple criterion to avoid scenes probably contaminated by thin clouds, and surface scattering. The ultraviolet irradiance positive bias in the OMI data is corrected using a procedure based on global climatological fields of aerosol absorption optical depth. The results generally show a bias significantly reduced by 5–20%, a lower variability and an unchanged, high correlation coefficient.     

Validation of MODIS derived aerosol optical depth over the Yangtze River Delta in China

MODIS derived aerosol optical depths (AODs) at 550 nm are compared with sunphotometer CE318 measurements at 7 sites located at Yangtze River Delta (YRD) in China from July to October, 2007. The evaluation result indicates that MODIS AODs (Collection 5, C005) are in good agreement with those from CE318 in dense vegetation regions, but show more differences in those regions with complex underlying surface (such as at lake water and urban surface sites). Reasons for these differences are discussed after removing cases with significant errors caused by validation scheme. The final validation result shows that MODIS AODs are in good agreement with CE318 with a correlation coefficient of 0.85 and RMS of 0.15. 90% of MODIS cases fall in the range of Δτ = ± 0.05 ± 0.20τ, indicating MODIS aerosol retrieval algorithm, aerosol models and surface reflectance estimate are generally suitably reasonable for aerosol retrieval in YRD. However, MODIS AODs show a systemic errors with fitted line of y = 0.75x + 0.13, indicating underestimation of AOD when aerosol loadings are high. Aerosol models and surface reflectance estimations are dominant sources of MODIS aerosol retrieval errors.     

MERIS atmospheric correction over coastal waters: validation of the MERIS aerosol models using AERONET

Standard aerosol models (SAMs) are used for the Medium-Resolution Imaging Spectrometer (MERIS) level-2 processing over water, first to remotely sense the aerosols in the near-infrared and secondly to perform the atmospheric correction for ocean colour analysis. However, are these SAMs still suitable over coastal areas? The present work was intended to answer that question through the use of the Aerosol Robotic Network (AERONET) by selecting CIMEL radiometers operating over the sea surface or near the coastline. The current official MERIS algorithm overestimates aerosol optical thickness (AOT) over coastal waters at 865 nm. This can be related either to incorrect assumptions of the underlying surface assumption or to the assumptions of the aerosol properties (e.g. phase function). This study looks at the importance of aerosol modelling and confirms that the improved aerosol models must be used in the retrieval chain. Extinction measurements were first used to derive the aerosol optical thicknesses (AOTs). The spectral dependency of the AOTs between 670 nm and 865 nm allowed the selection of a standard aerosol model. The ability of the standard aerosol models to retrieve the AOTs at 440 nm was then analysed as a key element in the extrapolation of the aerosol path radiance from the near-infrared to the blue spectral range. The two outputs of this analysis are systematic biases in this retrieval process and accordingly they are an estimation of the dispersion. The first output can be defined as a corrective factor in the aerosol path radiance at 440 nm and the second output can be used for error analysis. A radiative transfer code was used to simulate the sky radiance in the principal plane of acquisition. Comparisons at 870 nm illustrated the ability of the standard aerosol models to retrieve the aerosol path radiances with a direct impact on the AOT retrieval from satellite observations at 865 nm.