基于自定义模型的FY-4A数据气溶胶光学厚度反演

利用第二代静止气象卫星风云四号 A 星(FY-4A)的多通道扫描成像辐射计(Advanced Geosynchronous Radiation Imager,AGRI)资料,充分考虑其通道设置,以山东为研究区域,构建适用于山东本地的气溶胶模型,研究山东地区气溶胶光学厚度(aerosol optical depth,AOD)反演算法。选取两次典型空气污染案例进行反演,并将反演结果与临近时刻的 AOD 产品进行对比验证分析。结果表明：反演结果与 Himawari-8/ AHI(Advanced Himawari Imager)的气溶胶产品在空间分布上总体一致, 能体现 AOD 的变化趋势及分布情况;和临近时刻的 MODIS 产品相关系数较高,均在0. 90 左右,最高可达0. 94。这说明基于自定义气溶胶模型,利用 FY-4A/ AGRI 数据反演山东地区气溶胶合理可行。     

HY1C/1D海表温度对Terra/Aqua产品的可替代性分析

通过卫星遥感获取的海表温度（SST）产品已经成为海洋和大气研究中的重要数据源,我国海洋水色遥感卫星（HY1C和HY1D）的海洋水色水温扫描仪（COCTS）具有两个热红外通道,可反演全球SST遥感产品。对比Terra和Aqua卫星的中分辨率成像光谱仪（MODIS）的SST产品,分析COCTS海表温度产品对MODIS相应产品的可替代性。比较了两种卫星的全球SST单日和月平均融合产品的图像空间结构,分析了匹配像元SST值的离散度,统计了HY1C/1D的误差结果,讨论了HY1C与HY1D产品的一致性、不同质量控制方案对SST产品影响以及遥感产品质量对昼夜SST变化研究影响等问题。结果表明,以2020年6月SST(Terra)为真值,HY1C白天SST的单日全球遥感产品的平均偏差、绝对偏差、均方根误差和相关系数分别为0.04℃、0.60℃、0.78℃和0.98,夜晚SST的单日全球遥感产品的平均偏差、绝对偏差、均方根误差和相关系数分别为-0.16℃、0.78℃、0.95℃和0.86。以2020年6月SST(Aqua)为真值,HY1D白天SST的单日全球遥感产品的平均偏差、绝对偏差、均方根误差和相...     

基于FY-3C微波辐射计数据的极区海冰密集度反演方法研究

极区海冰影响大气和海洋环流,对全球气候变化起着重要的作用。海冰密集度是表征海冰时空变化特征的重要参数之一。本文研究了利用FY-3C微波扫描辐射计亮温数据反演极区海冰密集度的方法。经过时空匹配、线性回归,修正了FY-3C微波辐射计亮温数据。使用两种天气滤波器和海冰掩模滤除了大气影响所造成的开阔海域虚假海冰;使用最小密集度模板去除陆地污染效应。通过计算2016年、2017年极区海冰面积及范围两个参数,对得到的海冰密集度产品进行了验证,两年的海冰范围和面积趋势基本与NSIDC产品一致,平均差异小于3%。本研究结果为发布我国自主卫星的极区海冰密集度业务化产品奠定了基础,制作的产品可保障面临中断的40多年极区海冰记录的连续性。     

HY-1C/D CZI多光谱影像云覆盖与耀斑区域绿潮自动提取方法研究

针对多光谱影像受云、雾、太阳耀斑等因素的影响,难以实现高精度的绿潮自动提取的问题,本文以我国的HY-1C/D卫星CZI载荷多光谱影像为数据源,采用数据挖掘技术,通过探索绿潮区域与非绿潮区域的光谱分布差异,提出一种适用于HY-1C/D CZI影像的高精度、全自动绿潮提取方法。首先,分析有云区域和无云区域样本的光谱差异,给出厚云去除规则;其次,选取绿潮和非绿潮区域的样本,采用决策树算法生成绿潮提取规则;然后,针对薄云和厚云边界区域常常会出现误检绿潮的问题,设计了5种错误类别修正策略。为验证方法的有效性,收集2021年黄海区域绿潮暴发周期内的25景HY-1C/D CZI影像,开展绿潮自动检测实验。结果表明,与传统的NDVI方法、VB-FAH方法等指数方法以及ResNet50、U-Net等深度学习方法相比,本文方法在准确度、Kappa系数、F1-Score和MIoU等指标上均优于其他方法,而且能够实现在厚云、薄云、无云、云斑和耀斑区域复杂情况下的绿潮的高精度自动提取。     

HY-1C/D卫星中国海洋水色水温扫描仪几何定位方法

海洋一号C/D（HY-1C/D）卫星中国海洋水色水温扫描仪（Chinese Ocean Color and Temperature Scanner,COCTS）主要用于探测海洋水色、水温等要素,这些要素需要经过卫星资料处理才能获取,而几何定位是预处理的核心,直接影响这些要素的质量。COCTS具有114°视场角和四元逐点摆扫的特征,据此研究出一套完整的几何定位方法。从0级数据中提取卫星星历,利用插值法从中获取采样时间对应的卫星位置和速度,进而得到轨道（ORB）坐标系到地心旋转（ECR）坐标系的转换矩阵。基于四元逐点摆扫的特征,中心视矢量分别绕X轴、Y轴旋转相应角度,获得扫描行各采样点ORB视矢量,建立视矢量与地球交叉点关系模型,从而对根据波段数据绘制的遥感图像进行地理定位。本文使用插值法替代了传统需要6个轨道根数来计算卫星位置的复杂方法,同时直接计算ORB到ECR的转换矩阵,而不采用传统的两步转换方法。经过多组数据计算及定性定量验证,HY-1C/D COCTS几何定位结果一致;采样像元尺度效应导致从星下点到两侧边缘、从赤道到两极,误差逐渐增大,约在两个像元内。该方法满足一定的定位精度要求,可以用于COCTS的几何定位。     

基于光谱特征的HY-1C/D卫星赤潮探测方法以红夜光藻为例

红夜光藻是我国主要的赤潮优势种,在渤海、黄海、东海和南海均有发生。近年来,红夜光藻赤潮发生频率明显上升,监测需求迫切。但红夜光藻赤潮发生具有分布范围广、变化速度快、多呈条带状分布的特点,其探测对卫星影像空间分辨率、覆盖范围和重访周期要求高。虽然水色卫星在赤潮监测中发挥了重要作用,但其空间分辨率低,无法准确探测条带状分布的红夜光藻赤潮。海洋一号C、D（HY-1C/D）卫星搭载的海岸带成像仪（Coastal Zone Imager,CZI）以其高空间分辨率、大幅宽和短重访周期的优势,被越来越多地用于赤潮监测。现有的红夜光藻赤潮HY-1C/D CZI探测模型大多基于深度学习方法,需要大量赤潮样本,但赤潮样本获取困难,影响模型的精度。因此,本文以2022年3月发生在广东省汕尾市红海湾的红夜光藻赤潮为例,分析了红夜光藻赤潮光谱特征,基于红夜光藻赤潮在红光和近红外波段的高反射特性和浑浊水体在绿光波段的高反射特性,构建了一个面向HY-1C/D CZI的红夜光藻赤潮探测方法。实验结果表明,该方法可以有效地探测赤潮,并避免浑浊水体的干扰,精确率和F1-Score达到89.72%和0.90。而且,该方法具有较好的适用性,可适用于不同海洋环境、不同宽波段卫星传感器的红夜光藻赤潮探测。     

HY-1C卫星海岸带成像仪叶绿素a浓度反演研究

叶绿素a作为最重要的水质参数之一,是评价水体富营养化和初级生产力状况的主要因素。我国海洋一号C（HY-1C）卫星海岸带成像仪（CZI）具有高时空分辨率的观测优势。本文基于东海和南海现场实测数据建立了HY-1C卫星CZI叶绿素a浓度反演模型并在实测水域进行反演,与MODIS叶绿素a浓度反演产品进行了对比验证,应用CZI叶绿素a浓度模型在珠江口、长江口、渤海湾水域进行了叶绿素a浓度反演示例试验。结果表明,叶绿素a浓度模型估算浓度与实测浓度相关系数为0.774 3,平均相对误差为24.58%,利用实测叶绿素a浓度对模型进行精度验证,相关系数达到0.993 9,平均相对误差为18.49%。模型在实测水域反演得到的叶绿素a浓度分布与MODIS叶绿素a浓度产品分布大体一致。在珠江口水域反演得到叶绿素a浓度空间分布为由西北向东南逐级递减,峰值出现在珠江口西沿岸。在长江口、渤海湾反演叶绿素a浓度空间分布均符合地理实情。研究表明HY-1C卫星CZI数据可应用于中国近海水色定量化研究。     

HJ-1B 卫星海表温度定量反演业务化算法研究——以中国北部海区为例

利用中国2008年9月发射的自主 HJ-1B 卫星热红外遥感影像数据,基于实测数据对已有海表温度反演的单窗算法进行了改进与简化,重新订正了大气透射率和大气平均作用温度估算方程,建立了基于实测数据验证的 HJ-1B 卫星海表温度定量反演业务化算法.将本算法与段四波等的改进算法用于实验海区海表温度的反演,反演结果与卫星同步实测海温数据的对比表明:本研究算法反演结果与现场同步实测海表温度平均误差约为0.76,℃段四波等改进算法反演结果平均误差约为1.09℃.本算法为 HJ-1B 卫星海表温度产品的业务化应用提供了便捷可行的方案     

基于C/S与B/S混合结构的海洋科技档案管理系统的分析和设计

分析了目前海洋科技档案管理的现状和存在的问题,针对海洋科技档案管理的特点和具体的应用需求,提出了基于C／S与B／S混合结构的海洋科技档案管理系统（Marine Science＆Technology Archives Management System,MSTAMS）设计方案．基于海洋科技档案管理的工作流程,从系统的总体设计、数据库设计、功能模块划分以及安全管理体束等方面进行了论述,对其中的关键技术进行了分析和研究,为糸纯的开发和实施提供一套切实、可行、全面、先进的理论体来和技术指导,以实现海洋科技档案管理信息化、自动化和可视化,从而提高海洋科技档案管理的效率,满足目前各海洋研究系统及单位对档案管理和应用的需要．     

Arctic sea ice concentration retrieval using the DT-ASI algorithm based on FY-3B/MWRI data

Sea ice concentration (SIC) is one of the most important indicators when monitoring climate changes in the polar region. With the development of the Chinese satellite technology, the FengYun (FY) series has been applied to retrieve the sea ice parameters in the polar region. In this paper, to improve the SIC retrieval accuracy from the passive microwave (PM) data of the Microwave Radiation Imager (MWRI) aboard on the FengYun-3B (FY-3B) Satellite, the dynamic tie-point (DT) Arctic Radiation and Turbulence Interaction Study (ARTIST) Sea Ice (ASI) (DT-ASI) SIC retrieval algorithm is applied and obtained Arctic SIC data for nearly 10 a (from November 18, 2010 to August 19, 2019). Also, by applying a land spillover correction scheme, the erroneous sea ice along coastlines in melt season is removed. The results of FY-3B/DT-ASI are obviously improved compared to that of FY-3B/NT2 (NASA-Team2) in both SIC and sea ice extent (SIE), and are highly consistent with the results of similar products of AMSR2 (Advanced Microwave Scanning Radiometer 2)/ASI and AMSR2/DT-ASI. Compared with the annual average SIC of FY-3B/NT2, our result is reduced by 2.31％. The annual average SIE difference between the two FY- 3Bs is 1.65×106 km2, of which the DT-ASI algorithm contributes 87.9％ and the land spillover method contributes 12.1％. We further select 58 MODIS (Moderate-resolution Imaging Spectroradiometer) cloud-free samples in the Arctic region and use the tie-point method to retrieve SIC to verify the accuracy of these SIC products. The root mean square difference (RMSD) and mean absolute difference (MAD) of the FY-3B/DT-ASI and MODIS results are 17.2％ and 12.7％, which is close to those of two AMSR2 products with 6.25 km resolution and decreased 8％ and 7.2％ compared with FY-3B/NT2. Further, FY-3B/DT-ASI has the most significant improvement where the SIC is lower than 60％. A high-quality SIC product can be obtained by using the DT-ASI algorithm and our work will be beneficial to promote the application of FengYun Satellite.     

FY-3A/MERSI, ocean color algorithm, products and demonstrative applications

A medium resolution spectral imager (MERSI) on-board the first spacecraft of the second generation of China’s polar-orbit meteorological satellites FY-3A, is a MODIS-like sensor with 20 bands covering visible to thermal infrared spectral region. FY-3A/MERSI is capable of making continuous global observations, and ocean color application is one of its main targets. The objective is to provide information about the ocean color products of FY-3A/MERSI, including sensor calibration, ocean color algorithms, ocean color products validation and applications. Although there is a visible on-board calibration device, it cannot realize the on-board absolute radiometric calibration in the reflective solar bands. A multisite vicarious calibration method is developed, and used for monitoring the in-flight response change and providing post-launch calibration coefficients updating. FY-3A/MERSI ocean color products consist of the water-leaving reflectance retrieved from an atmospheric correction algorithm, a chlorophyll a concentration (CHL1) and a pigment concentration (PIG1) from global empirical models, the chlorophyll a concentration (CHL2), a total suspended mater concentration (TSM) and the absorption coefficient of CDOM and NAP (YS443) from China’s regional empirical models. The atmospheric correction algorithm based on lookup tables and ocean color components concentration estimation models are described. By comparison with in situ data, the FY-3A/MERSI ocean color products have been validated and preliminary results are presented. Some successful ocean color applications such as algae bloom monitoring and coastal suspended sediment variation have demonstrated the usefulness of FY-3A/MERSI ocean color products.     

利用FY-4A气象卫星观测海洋内波

随着遥感技术的迅猛发展,可用于观测海洋内波的数据源越来越丰富.本文基于静止轨道气象卫星连续观测的优势,开展了FY-4A气象卫星海洋内波观测研究.首先计算得到了FY-4A遥感影像耀斑区位置,并基于遥感影像对结果进行了验证;然后,以此为依据选择了适用于内波观测的FY-4A数据,对比了FY-4A与MODIS遥感影像成像的差异...     

使用参数化初猜测谱算法提取VV极化Sentinel-1 SAR图像的海浪要素并与ECMWF再分析数据以及浮标数据进行验证对比

The purpose is to study the accuracy of ocean wave parameters retrieved from C-band VV-polarization Sentinel-1Synthetic Aperture Radar(SAR) images, including both significant wave height(SWH) and mean wave period(MWP), which are both calculated from a SAR-derived wave spectrum. The wind direction from in situ buoys is used and then the wind speed is retrieved by using a new C-band geophysical model function(GMF) model,denoted as C-SARMOD. Continuously, an algorithm parameterized first-guess spectra method(PFSM) is employed to retrieve the SWH and the MWP by using the SAR-derived wind speed. Forty–five VV-polarization Sentinel-1 SAR images are collected, which cover the in situ buoys around US coastal waters. A total of 52 subscenes are selected from those images. The retrieval results are compared with the measurements from in situ buoys. The comparison performs good for a wind retrieval, showing a 1.6 m/s standard deviation(STD) of the wind speed, while a 0.54 m STD of the SWH and a 2.14 s STD of the MWP are exhibited with an acceptable error.Additional 50 images taken in China's seas were also implemented by using the algorithm PFSM, showing a 0.67 m STD of the SWH and a 2.21 s STD of the MWP compared with European Centre for Medium-range Weather Forecasts(ECMWF) reanalysis grids wave data. The results indicate that the algorithm PFSM works for the wave retrieval from VV-polarization Sentinel-1 SAR image through SAR-derived wind speed by using the new GMF C-SARMOD.     

Cross-calibration of brightness temperature obtained by FY-3B/MWRI using Aqua/AMSR-E data for snow depth retrieval in the Arctic

This study cross-calibrated the brightness temperatures observed in the Arctic by using the FY-3B/MWRI L1 and the Aqua/AMSR-E L2A. The monthly parameters of the cross-calibration were determined and evaluated using robust linear regression. The snow depth in case of seasonal ice was calculated by using parameters of the crosscalibration of data from the MWRI T_b. The correlation coefficients of the H/V polarization among all channels T_b of the two sensors were higher than 0.97. The parameters of the monthly cross-calibration were useful for the snow depth retrieval using the MWRI. Data from the MWRI T_b were cross-calibrated to the AMSR-E baseline.Biases in the data of the two sensors were optimized to approximately 0 K through the cross-calibration, the standard deviations decreased significantly in the range of 1.32 K to 2.57 K, and the correlation coefficients were as high as 99%. An analysis of the statistical distributions of the histograms before and after cross-calibration indicated that the FY-3B/MWRI T_b data had been well calibrated. Furthermore, the results of the cross-calibration were evaluated by data on the daily average T_b at 18.7 GHz, 23.8 GHz, and 36.5 GHz(V polarization), and at 89 GHz(H/V polarization), and were applied to the snow depths retrieval in the Arctic. The parameters of monthly cross-calibration were found to be effective in terms of correcting the daily average T_b. The results of the snow depths were compared with those of the calibrated MWRI and AMSR-E products. Biases of 0.18 cm to 0.38 cm were observed in the monthly snow depths, with the standard deviations ranging from 4.19 cm to 4.80 cm.     

HY-1 CCD宽波段水色要素反演算法

利用2003年春季黄海、东海区现场实测数据,建立了HY1卫星4波段CCD成像仪水色要素反演算法.由于HY1CCD的宽波段特性阻碍了黄色物质的反演,因此反演的水色要素仅包括水体表层的总悬浮物、悬浮泥沙(SS)以及叶绿素a的浓度.现场遥感反射率光谱由ASD地物波谱仪测量,对于叶绿素a的浓度利用现场萃取荧光法测量,总悬浮物、悬浮泥沙由实验室滤膜称重法获得.反演算法的拟合相关系数均大于0.88,平均相对误差在40%以下.对反演算法进行了误差灵敏度分析,结果表明对于总悬浮物、悬浮泥沙和低浊度水体中的叶绿素a的浓度反演算法能够满足日常的业务运行要求,但是对于高浊度水体中叶绿素a的浓度反演算法对某个波段组合比较敏感,仍需要进一步探讨.     

一套具有更高时空分辨率的全球海洋叶绿素浓度遥感融合产品数据集

认识海洋在全球碳循环中的作用及其对环境变化的响应,需要高时空分辨率的观测数据。由于轨道宽度、云雨天气、太阳耀斑等的影响,单一的水色传感器的观测能力十分有限,将多源海洋水色卫星进行融合是提高水色数据时空覆盖的一种有效途径。SeaWiFS和MERIS分别于2010年12月11日和2012年5月9日停止运行,在很大程度上降低了水色融合产品时空覆盖的提升。我们在融合过程中加入了FY-3 MERSI数据,生成了全球海洋叶绿素浓度遥感融合产品数据集。数据源包括SeaWiFS、MERIS、MODIS-Aqua、VIIRS和MERSI。结果表明：加入MERSI后,融合产品的日平均有效空间覆盖提高了9%;采样频率（同一区域一年中获取有效数据的次数）由57天/年提高到109天/年。利用实测数据和国外同类融合产品（ESA GlobColour和NASA MEaSUREs）对新的数据集进行了质量评价。与实测数据相比,加入MERSI的融合产品精度与未加入MERSI的融合产品基本一致;与国外同类融合产品的偏差小于10%。新数据集的时间序列特性与未加入MERSI的融合产品以及单传感器的一致。     

Algorithm for estimating sea surface temperatures based on Aqua/MODIS global ocean data. 1. Development and validation of the algorithm

An algorithm for estimating global sea surface temperatures (SST) from data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite has been developed empirically. Four atmospheric correction models for MODIS observations are examined, and the effects of ancillary data for corrections are discussed. A nonlinear (NLSST) model using high-temporal-resolution climatological SSTs as the first guess shows high accuracy and availability. The addition of a temperature-proportional term to the NLSST model effectively improves the estimate.