太湖水体GF-1/WFV影像的6S逐像元大气校正

水体光谱信息微弱,常用的基于辐射传输模型的大气校正方法在水体中校正精度较差。基于覆盖太湖水体的2016年4月29日的高分一号宽幅相机影像（GF-1/WFV）和同步的实测光谱数据,对6S辐射传输模型的输入参数进行敏感性分析,逐像元计算观测几何,使用分区气溶胶类型、分区暗像元和Spline插值确定的气溶胶光学厚度（Aerosol Optical Depth,AOD）进行6S逐像元大气校正。实验结果表明:气溶胶模式对6S大气校正结果的影响最大,与FLAASH方法相比,逐像元计算观测几何和气溶胶参数的校正方法对大气校正精度有改进作用,4个波段的平均相对误差分别降低了1.84%、7.78%、4.79%和17%。结合精确大气参数输入的6S逐像元大气校正方法可以改进水体表面遥感反射率的大气校正精度。     

复杂地形下自动提取多暗像元的TM影像大气纠正方法

复杂地形条件下气溶胶的空间分布变化较大,用单一的气溶胶实测参数或单一的暗像元进行大气纠正都难以获得好的效果,手动选取暗像元还受限于专业人员的经验。通过程序自动提取图像中的浓密植被像元以及位于山区阴影的植被像元作为暗像元,使得暗像元均匀分布于图像的各个区域、各个海拔,更好地模拟复杂地形下的大气状况。根据辐射传输模型,利用迭代、插值等方法获取TM1和TM3波段光学厚度,进而推算成像时刻的气溶胶波长指数及混浊度系数,从而得到各个波段的大气光学厚度以实现大气纠正。     

京津冀冬季气溶胶光学厚度遥感反演

针对传统的暗像元算法难以满足植被稀疏陆表气溶胶遥感监测需求的问题,提出了冬季植被稀疏的京津冀地区气溶胶光学厚度的遥感反演方法。以2016—2018年连续3年1—2月的AQUA/MODIS L1B数据为数据源,采用暗像元算法与深蓝算法结合的方法对冬季京津冀地区的气溶胶光学厚度进行了遥感监测。使用AERONET数据对结果进行了验证,并与MODIS MYD04_L2暗像元-深蓝气溶胶产品进行了对比。结果表明,该算法在冬季京津冀地区的气溶胶监测效果远好于暗像元算法,并与MODIS气溶胶产品表现出了显著的相关性,且有效监测范围更大、空间分辨率更高。根据连续监测结果,分析了京津冀地区冬季气溶胶光学厚度空间分布特征及其影响因素。     

基于MODIS的大气因素对蓝藻水华信息提取的影响

本文利用MODIS提供的两种影像产品和代表大气条件的气溶胶产品,运用单波段(NIR)和比值植被指数(NIR/G)两种方法分别提取太湖蓝藻信息.在阐述气溶胶的光学厚度对遥感影像影响的基础上,定量分析了气溶胶光学厚度对两种方法提取蓝藻水华面积的净变化值和选取阈值的影响程度.研究结果表明,运用单波段和比值植被指数两种方法提取太湖蓝藻水华面积差异与气溶胶光学厚度的相关性,固定阈值情况下的相关性高于自选阈值中的对应值.两种指数中大气校正前的阈值与气溶胶光学厚度的相关性都要高于大气校正后两者的相关性.这说明大气会对阈值的设定产生一定的影响,进而影响蓝藻信息提取精度.因此,定量分析气溶胶光学厚度对监测蓝藻是至关重要的.     

利用多元遥感数据进行CBERS-02卫星大气校正研究

针对山地丘陵等复杂地表下地形对遥感数据影响较大的情况,提出了适合该区域的大气校正方法。该方法以MODIS数据为数据源,基于6S反演出陆地上空的气溶胶模式和光学厚度。使用同时相同区域的TM数据对CCD数据进行交叉定标,利用ATCOR3实现了对CBERS\|02星CCD数据进行大气校正。校正前后数据比较结果表明:该算法还原了下垫面原貌,尤其对山区丘陵等复杂地表具有很好效果。     

高分六号卫星遥感估算大气细颗粒物方法研究北大核心CSCD

针对目前利用高分六号卫星开展地区高空间分辨率大气细颗粒物监测研究较少的问题,提出了基于高分六号卫星宽幅相机数据的气溶胶光学厚度及大气细颗粒物遥感反演的技术方法,并在京津冀及周边地区开展了应用实验和对比分析。首先,基于改进暗像元法反演了高分六号卫星数据的气溶胶光学厚度;然后,结合地面大气细颗粒物监测数据与多种气象辅助数据,基于随机森林算法,构建了多参量综合的大气细颗粒物估算模型,对京津冀地区的大气细颗粒物浓度进行了估算。研究表明:高分六号气溶胶光学厚度反演结果与地基站点监测结果的相关系数为0.94,反演精度较高;大气细颗粒物估算结果与地基站点监测结果的决定系数达到0.79以上,较好地反映了京津冀地区的大气细颗粒物空间分布。     

利用MODIS资料反演杭州市500米分辨率气溶胶光学厚度

反演城市/区域范围内高空间分辨率的气溶胶光学厚度时,如果气溶胶类型选取的不合理造成的反演误差会很大,甚至超过地表反射率确定误差导致的反演误差。针对这一问题,本文提出了一种结合MODIS L1B资料和AERONET(Aerosol Robotic Network)的气溶胶光学厚度产品,基于6S大气辐射传输模型的计算,确定杭州市在2008年12月16日的气溶胶类型的方法。利用得到的气溶胶类型,结合改进的暗像元法,反演了杭州市500m空间分辨率的气溶胶光学厚度。将气溶胶光学厚度反演结果与采用标准气溶胶类型时的反演结果进行比较,结果表明,本文确定的气溶胶类型更符合杭州市当天的情况,应用到气溶胶光学厚度反演中,精度也最好,相对误差的绝对值在20%以内。     

山区可见光—近红外遥感影像浓密植被暗像元自动识别方法研究

暗目标法是目前气溶胶光学厚度遥感反演中应用最为广泛的方法,浓密植被暗像元的识别是暗目标法的基础。针对可见光—近红外影像缺少中红外波段难以有效识别浓密植被暗像元的问题,引入红波段直方图阈值法识别山区可见光—近红外影像的浓密植被暗像元。该方法利用浓密森林像元在可见光波段反射率低的特点,通过搜索红波段直方图的最小峰值自动识别浓密植被暗像元。试验中选取Landsat TM影像前4个波段利用红波段直方图阈值法识别可见光—近红外影像的浓密植被暗像元,并与在中红外波段影像和可见光—近红外影像中广泛应用的两种暗像元识别方法进行对比分析,探讨红波段直方图阈值法的有效性,最后将该方法应用于环境减灾卫星(HJ-1)CCD影像的暗像元识别和气溶胶反演。实验结果表明:红波段直方图阈值法明显优于常用的可见光—近红外影像暗像元识别方法,识别精度接近传统的中红外波段影像识别方法,相似度指数小于2和小于3的暗像元分别为83.12%和93.48%。该方法为山区可见光—近红外影像浓密植被暗像元自动识别提供了一种新的适用方法,识别结果能够满足暗目标法反演气溶胶光学厚度的要求。     

利用地物光谱仪测算大气气溶胶光学厚度方法

气溶胶光学厚度是进行大气校正的重要参数，本文提出了一种通过地物光谱仪测量太阳辐射来测算气溶胶光学厚度的方法。并将测算结果与6S大气辐射传输模型的模拟结果进行比较，详细分析了误差来源。研究表明该方法是一种实用有效的方法，可用于遥感数据大气校正及大气气溶胶光学厚度的估算。     

资源一号02D高光谱数据大气校正及应用北大核心CSCD

针对高光谱数据大气校正耗时长和查找表构建不准确等问题,提出基于MODTRAN辐射传输模型实时创建大气校正参数查找表的方法,并应用于水体叶绿素浓度反演。首先,基于高光谱数据实时构建大气校正参数查找表;其次,根据循环迭代反演得到水汽含量和气溶胶光学厚度对查找表插值得到各个波段的大气校正参数,从而完成所有波段数据的大气校正;最后,选择植被、土壤和水体3类典型地物精度分析,并基于反演水体的叶绿素a浓度验证大气校正精度的可靠性。实验结果表明:该方法明显优于6S、FLAASH等大气校正方法;在运行效率上,在多线程并行加速后,运行效率提升了2~4倍;基于水体反射率数据反演水体叶绿素a浓度,反演模型预测集验证中ρ为0.804 7,RMSE为1.8。     

Atmospheric Correction of GF-1/WFV Image in Taihu Lake based on the 6S Model Pixel by Pixel

The spectral information of water is weak, and the commonly used radiation transfer model has poor accuracy in atmospheric correction of water body. Based on the Gaofen-1 WFV image (GF-1/WFV) and the synchronous in situ spectra covering Taihu Lake on 29^th, April, 2016, the sensitivity analysis of the input parameters in 6S model was first performed, and then the image was corrected using 6S model using the observation geometry calculated pixel-by-pixel, the partitioned aerosol type and the Aerosol Optical Depth (AOD) determined by the partitioned dark pixel and Spline interpolation. The experimental results show that the aerosol type has the greatest influence on the 6S atmospheric correction results. Compared with the FLAASH method, the 6S method using the observation geometry and aerosol parameters calculated pixel-by-pixel significantly improved the atmospheric correction accuracy, with the ARE (Average Relative Error) of the four bands reduced by 1.84%，7.78%，4.79%，17%. The 6S atmospheric correction method pixel by pixel with the input of accurate atmospheric parameters can improve the correction accuracy of the remote sensing reflectance above water surface.     

Aerosol optical depth spatio-temporal characterization over the Canadian BOREAS domain

A complete set of Advanced Very High Resolution Radiometer (AVHRR) data (75 images) is used to retrieve aerosol optical depth (AOD) over dense vegetation and over lake water in the visible AVHRR channel. The present approach for remote sensing of aerosols from the National Oceanic and Atmospheric Administration (NOAA)-11 AVHRR sensor is based on the detection of atmospherically dominated signals over dark surface covers such as dense dark vegetation (DDV). Such targets were identified using the reflective portion of the middle-wave AVHRR channel 3 signal. When a fixed DDV surface reflectance is subtracted from the observed reflectance after correction for all other atmospheric effects, the remaining part, which is due to aerosols, is inverted to derive aerosol optical thickness using a look-up table (LUT) similar to that used in water surface inversion. The algorithm was applied to the daily afternoon NOAA-11 AVHRR (1?km×1?km) data acquired from the end of May to mid-August 1994 over the Canadian 1000?km×1000?km Boreal Ecosystem Atmosphere Study (BOREAS) domain. A validation analysis using five ground-based Sun photometers within the studied area shows the good performance of the retrieval algorithm. The approach allows detailed analysis of the AOD spatio-temporal behaviour at the regional scale useful for climate and transport model validation.     

Atmospheric correction for inland waters—application to SeaWiFS

Inland waters are an increasingly valuable natural resource that has major impact and benefits for population and environment. The new generation of ocean colour sensors has better spatial resolution, and hence are suitable for monitoring water quality of lakes. As an alternative to standard algorithms developed for oceans, which often fail over inland waters, we propose here a scheme based on aerosol remote sensing over land. The ocean colour sensors have spectral bands that allow characterization of aerosols over dark land pixels (vegetation in the blue and in the red spectral bands). It is then possible to use a representative aerosol model (aerosol optical thickness and aerosol type) for atmospheric correction over inland waters after validating the spatial homogeneity of the aerosol model in the lake vicinity. The performance of this new algorithm is shown in Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS) scenes of Lakes Balaton (Hungary) and Constance (Germany). We demonstrate the good spatial homogeneity of the aerosols and the meaningfulness of the water‐leaving reflectances derived over these two lakes.

We also addressed the particularity of Fresnel reflection computation. The direct to diffuse term of this Fresnel contribution is reduced because of the limited size of the lake. Based on the primary scattering approximation, we propose a simple formulation of this component. A specific Fresnel correction needs to be developed to fulfil the accuracy requirements.     

Water property monitoring and assessment for China's inland Lake Taihu from MODIS-Aqua measurements

We provide results of quantitative measurements and characterization for inland freshwater Lake Taihu from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellite Aqua. China's Lake Taihu, which is located in the Yangtze River delta in one of the world's most urbanized and heavily populated areas, contains consistently highly turbid waters in addition to frequent large seasonal algae blooms in various lake regions. Thus, satellite data processing requires use of the shortwave infrared (SWIR) atmospheric correction algorithm. Specifically for Lake Taihu, an iterative SWIR-based atmospheric correction algorithm has been developed and proven to provide reasonably accurate water-leaving radiance spectra data. Using MODIS-Aqua measurements, the blue-green algae bloom in Lake Taihu in 2007 has been studied in detail, demonstrating the importance and usefulness of satellite water color remote sensing for effectively monitoring and managing a bloom event.Seasonal and interannual variability, as well as spatial distributions, of lake water properties were studied and assessed using the MODIS-Aqua measurements from 2002 to 2008. Results show that overall waters in Lake Taihu are consistently highly turbid all year round, with the winter and summer as the most and least turbid seasons in the lake, respectively. Extremely turbid waters in the winter are primarily attributed to strong winter winds that lead to significant amounts of total suspended sediment (TSS) in the water column. In addition, MODIS-Aqua-measured water-leaving radiance at the blue band is consistently low in various bay regions in Lake Taihu, indicating high algae concentration in these regions. Climatological water property maps, including normalized water-leaving radiance spectra nL_w(λ), chlorophyll-a concentration, and water diffuse attenuation coefficient at the wavelength of 490 nm (K_d(490)), are derived from all MODIS-Aqua data from 2002 to 2008 for Lake Taihu, showing overall spatial distribution features for the lake water property.     

A multiple scattering algorithm for atmospheric correction of remotely sensed ocean colour (MERIS instrument): Principle and implementation for atmospheres carrying various aerosols including absorbing ones

A multiple scattering algorithm for atmospheric correction of satellite ocean colour observations is described. This algorithm, precisely designed for the MERIS instrument, globally assesses the combined contributions of aerosols and molecules to the multiple scattering regime. The approach was introduced in a previous work, where it was shown that, for a given aerosol, multiple scattering effects can be assessed through the relationship between the aerosol optical thickness and the relative increase in the path radiance that results from the progressive introduction of this aerosol within an aerosol-free atmosphere. Based on considerations about the accuracy to which the water-leaving radiances should be retrieved, the need to account for multiple scattering is argued. The principle of the algorithm is then presented, and tests and sensitivity studies (especially as regards aerosol type and vertical distribution) are performed to assess its performance in terms of errors on the retrieved water-leaving reflectances and pigment concentrations. The algorithm is able to perform the correction for atmospheres carrying several aerosol types, including absorbing ones, through their identification in the near-infrared, and through the detection of their absorption by means of appropriate assumptions on the marine signals at 510 and 705nm.     

A consistency analysis of surface reflectance and leaf area index retrieval from overlapping clear-sky Landsat ETM+ imagery

In this study, the consistency of systematic retrievals of surface reflectance and leaf area index was assessed using overlap regions in adjacent Landsat Enhanced Thematic Mapper-Plus (ETM+) scenes. Adjacent scenes were acquired within 7-25 days apart to minimize variations in the land surface reflectance between acquisition dates. Each Landsat ETM+ scene was independently geo-referenced and atmospherically corrected using a variety of standard approaches. Leaf area index (LAI) models were then applied to the surface reflectance data and the difference in LAI between overlapping scenes was evaluated. The results from this analysis show that systematic LAI retrieval from Landsat ETM+ imagery using a baseline atmospheric correction approach that assumes a constant aerosol optical depth equal to 0.06 is consistent to within ±0.61 LAI units. The average absolute difference in LAI retrieval over all 10 image pairs was 26% for a mean LAI of 2.05 and the maximum absolute difference over any one pair was 61% for a mean LAI of 1.13. When no atmospheric correction was performed on the data, the consistency in LAI retrieval was improved by 1%. When a scene-based dense, dark vegetation atmospheric correction algorithm was used, the LAI retrieval differences increased to 28% for a mean LAI of 2.32. This implies that a scene-based atmospheric correction procedure may improve the absolute accuracy of LAI retrieval without having a major impact on retrieval consistency. Such consistency trials provide insight into the current limits concerning surface reflectance and LAI retrieval from fine spatial resolution remote sensing imagery with respect to the variability in clear-sky atmospheric conditions.     

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.     

Evaluation of four MERIS atmospheric correction algorithms in Lake Kasumigaura,Japan

Accurate atmospheric correction for turbid inland waters remains a significant challenge. Several atmospheric correction algorithms have been proposed to address this issue, but their performance is unclear in regard to Asian lakes, some of which have extremely high turbidity and different inherent optical properties from lakes in other continents. Here, four existing atmospheric correction algorithms were tested in Lake Kasumigaura, Japan (an extremely turbid inland lake), using in situ water-leaving reflectance and concurrently acquired medium resolution imaging spectrometer (MERIS) images. The four algorithms are (1) GWI (the standard Gordon and Wang algorithm with an iterative process and a bio-optical model) (2) MUMM (Management Unit of the North Sea Mathematical Models); (3) SCAPE-M (Self-Contained Atmospheric Parameters Estimation for MERIS Data) and (4) C2WP (Case-2 Water Processor). The results show that all four atmospheric correction algorithms have limitations in Lake Kasumigaura, even though SCAPE-M and MUMM gave acceptable accuracy for atmospheric correction in several cases (relative errors less than 30% for the 2006 and 2008 images). The poor performance occurred because the conditions in Lake Kasumigaura (i.e. the atmospheric state and/or turbidity) did not always meet the assumptions in each atmospheric correction algorithm (e.g. in 2010, the relative errors ranged from 42% to 83%). These results indicate that further improvements are necessary to address the issue of atmospheric correction for turbid inland waters such as Lake Kasumigaura, Japan.