三峡坝区水体吸收系数的特征研究

利用2007年11月在三峡坝区现场实测的水色要素吸收系数数据,对总颗粒物、浮游植物、CDOM的吸收系数特征进行了分析和研究。结果表明,对于三峡坝区区域的水体:(1)总颗粒物吸收光谱分布与非藻类的吸收光谱相似;(2)非藻类颗粒物的吸收系数随波长的变化分布接近指数衰减规律,且不同波段的吸收系数之间存在一定的关系;(3)多项式关系能较好的表达浮游植物吸收系数与叶绿素a浓度之间的关系;(4)分段函数能很好的表达CDOM的吸收系数特性,对500nm以下光谱的吸收呈现负指数衰减的规律,不同采样点拟合精度R2接近1;501—700nm波段范围的光谱曲线采用多项式能进行很好的拟和,且拟合精度R2达到95%以上。     

HJ-1A/B卫星CCD影像的武汉市东湖水色三要素遥感研究

以武汉市东湖为研究区域,利用同步的MODIS-Terra气溶胶光学厚度数据为输入参数,采用FLAASH模型对2010年3月11日HJ-1A/B卫星CCD影像进行大气校正处理,并利用多年实测数据建立叶绿素a浓度、悬浮泥沙浓度、黄色物质吸收系数三要素神经网络反演模型,对水色三要素进行反演。通过对反演结果与实测数据的对比分析可知,悬浮泥沙浓度、黄色物质吸收系数和叶绿素a浓度的平均相对误差分别为28.052%、17.628%和35.621%,表明HJ-1A/B卫星CCD传感器基本能满足II类水体水色要素的遥感监测需求。     

黄色物质光学特性及遥感研究进展

黄色物质是海洋水色三组分之一。本文回顾了黄色物质定义的演变历史及其来源研究，描述了表征黄色物质光学特性的两个参数（吸收系数和比例系数S），概括了吸收系数研究的两种数学模型，即190-250nm区间的高斯模型和250-650nm区间的指数模型。高斯模型为化学方法研究黄色物质的分子结构提供了有力帮助，指数模型为光学特性和遥感应用提供了便利条件。本文提供了S值的三种数学模拟方法，结果表明带有背景参数的非线性回归方法确定S值可使平均值增加13％，相应的标准偏差降低72％。而且黄色物质的吸收系数同荧光线性关系很强。吸收系数不仅是黄色物质光学特性的表征，而且还是黄色物质遥感的基础。根据遥感器的不同特点总结了CZCS、SeaWiFS、MERIS、MODIS、GLI等遥感器的黄色物质反演模型，展望了黄色物质遥感的未来。     

太湖秋季光学活性物质空间分布及其遥感估算模型研究

基于2004年秋季在太湖进行的一次大范围水体吸收系数、散射系数、辐照度比等生物光学特性及光学活性物质浓度的测定和计算,分析了秋季太湖光学活性物质浓度的空间分布特征以及水体生物光学特性,并在此基础上发展了内陆浅水湖泊非色素颗粒物、浮游植物色素和有色可溶性有机物(chromophoric dissolved organic matter,CDOM)的半分析模型.     

水体铜离子吸收系数光谱(400-900 nm)测量

金属溶解物的吸收光谱测量是水体重金属遥感反演的关键。本文使用水体透射光测量装置,利用ASD光谱仪测量相同厚度不同浓度铜离子溶液的透射光辐亮度,运用比值法计算水体铜离子消光系数和吸收系数,最终得到400—900 nm波长范围内的水体铜离子单位浓度吸收系数光谱。该方法可以较好地消除实验装置和水中悬浮物的影响。结果表明,水体铜离子在蓝、绿光波段吸收作用极小,红光至红外波段的吸收系数快速增大,与铜离子溶液颜色相吻合;吸收峰位于810 nm。多次独立实验测量所得结果的标准差很小,说明测量结果稳定。与Jancsò测量结果的对比分析表明,本文结果与国际上著名测量结果接近,且部分波段的测量值更为合理。     

一种高斯过程回归的水体吸收系数反演模型

水体吸收系数是评价水体环境质量和衡量海洋对全球气候影响的重要因子.水色遥感作为目前对大范围海洋进行长时间连续监测的唯一手段,可以借助于合适的反演模型从影像上获取水体吸收系数.然而现有模型多为经验模型,反演精度和水体适应性都较差.基于自建的全球水体光学原位测量数据集SeaBASS2020,通过选用412、443、490、...     

基于遗传算法的二类水体水色遥感反演

提出一种基于遗传算法的二类水体水色遥感反演算法。该算法以三成分 (叶绿素、悬浮泥沙与黄色物质 )海水光学模型作为前向模型 ,以实数编码遗传算法作为优化方法 ,并采用一对波段比来构造目标函数。模拟反演的结果表明 ,该算法可以有效克服已有二类水体水色遥感优化反演方法在搜索策略方面存在的困难 ,是一种有较高计算效率、可靠与稳健的反演算法     

水合铁离子及铁络合物吸收系数光谱(400-900 nm)测量

测量铁化合物溶解物的吸收光谱曲线是水中铁离子含量遥感反演的关键。采用自主设计的水体透射光测量装置,利用ASD光谱仪测量相同厚度不同浓度铁离子溶液的透射光辐亮度,然后运用比值法计算出水中3种铁化合物(硫酸铁、氯化铁和铁氰化钾)的消光系数和吸收系数,最终得到400—900 nm波长范围内3种铁离子吸收系数光谱。该方法可以较好地消除实验装置和水中悬浮物的影响。结果表明,水中3种铁离子均在紫蓝光波段吸收作用较大,绿光次之,逐渐减少至红光波段后,吸收系数变化很小呈平缓直线。测量结果可作为水体铁离子浓度遥感反演模型所需的基础参数。     

HY-1C卫星COCTS近海水体遥感反射率产品真实性检验

中国HY-1C卫星水色水温扫描仪(COCTS)从2018年9月发射至今已积累了大量的全球观测数据,本文利用AERONET-OC实测数据集对COCTS近海水体遥感反射率(Rrs)产品进行了真实性检验。本文对实测光谱数据集进行归一化处理,按光谱特征分为A (清洁)、B (比较清洁)、C (轻微浑浊)、D (比较浑浊)这4种光学水体类型,对COCTS Rrs产品在这4类水体的精度进行评价。结果表明:COCTS反演Rrs在A、B两种水体类型中存在轻微高估(平均绝对百分比误差APD (Average absolute Percent Difference)分别为38.79%、44.44%),在C类水体轻微低估(APD=40.85%),而在D类水体显著低估(APD=47.14%)。COCTS不同波段Rrs产品在4类水体的精度亦存在差异,其中412 nm、443 nm波段在A类水体中和实测数据一致性相对较好(APD均小于30%);520 nm、565 nm波段在C、D两类水体中和实测数据一致性相对较好(APD均小于30%);670 nm波段在4种水体均呈现显著低估。由于AERONET-OC波段和CO...     

大气环境卫星污染气体和大气颗粒物协同观测综述

空气污染作为一种重要的环境问题,直接影响人们的日常生活和身体健康。随着污染气体和颗粒物观测技术的逐步成熟,基于卫星平台的近地层大气污染物监测得到了快速的发展。本文概括性描述了大气环境关注的污染气体和大气颗粒物的主流遥感方法,对各方法的适用场景及优缺点进行了评述。尽管差分吸收光谱方法对污染气体的监测十分有效,但最优估计算法可进一步从多光谱信息中提取部分污染气体（例如：臭氧O3、一氧化碳CO等）的分层信息,有助于更细致地刻画污染气体在整层大气中的垂直分布。对于大气颗粒物遥感方法,采用不同的技术手段进行地气解耦是算法的核心问题,增加光谱、角度、偏振以及时间序列信息都可有效增加算法的地气解耦能力。基于对污染气体和大气颗粒物反演算法的总结,从污染气体和颗粒物协同观测的角度对卫星平台及传感器的发展历程进行了梳理,论述了紫外、红外以及可见光波段的传感器协同观测的优势,展望了未来静止卫星星座的高时空分辨率大气污染监测能力以及中国卫星的贡献。还探讨了以近地面大气污染物监测卫星探测技术及遥感算法亟待解决的问题以及未来的可能发展方向。     

Gelbstoff — the interfering yellow substance in the cholorophyll remote sensing

The development of remote sensing technology in the recent past and the consequent synoptic coverage of earth elements have made it possible to attempt to understand large scale ocean processes. The mapping of chlorophyll distribution and infering.at the resourcefulness of coastal waters are among the new areas of the beginning. But, a biogenic yellow substance in the coastal waters, which has some overlapping optical properties with phytoplankton chlorophyll, interferes in the process of developing and applying the algorithms to remote sensed data while estimating the concentration of the latter. This paper makes an overview of the properties of yellow substance while indicating the importance of its study in Indian waters.     

Remote determination of chromophoric dissolved organic matter in lakes,China

Chromophoric dissolved organic matter (CDOM) strongly influences the water-leaving radiance from aquatic ecosystems. In most inland waters, the remote determination of CDOM absorption presents a central challenge due to their complex optical conditions. However, identifying the temporal and spatial variability of CDOM is fundamental to the understanding of aquatic biogeochemical dynamics. In the present study, semi-analytical and empirical modeling approaches were used to examine CDOM absorption in four, shallow, inland water bodies using the spectral bands and sensitivities of major satellite observational systems. Of the models examined, an empirical multiband model was found to provide the highest correlation with measured CDOM absorption. The spectral characteristics of the MERIS sensors yielded the best results with respect to the other available satellite sensors. High detrital load was observed to be a major impediment to estimating CDOM absorption, while lakes with elevated phytoplankton biomass did not present similar problems.     

Chlorophyll — A Concentration Along West Coast of India Using IRS-P3 MOS-B Data

Remote sensing of ocean colour yields information on the constituents of sea water, such as the concentration of phytoplankton pigments, suspended sediments and yellow substances. It is well understood that the study of ocean colour is significantly related with the primary production and zonation of potential fishing sites in coastal and oceanic waters. The major pigment constituent is predominated by chlorophyll-a (ocean colour pigment of phytoplankton). The chlorophyll mapping on regular basis plays a major role in assessing water quality and classifying different water types. IRS P-3 MOS-B satellite data for three consecutive passes of path 94, during the period of January-February 1997 have been used to derive chlorophyll-a concentration. The present study emphasizes on the chlorophyll mapping using IRS-P3 MOS-B data for the coastal and offshore water of Maharashtra coast, India.     

Hyperspectral radiometric observation of the northeast Arabians Sea during April 2006

Parameters were retrieved from the hyperspectral radiometer like upwelling and downwelling radiance (Lu and Ed) upwelling and downwelling attenuation (K-Lu and K-Ed) for 9 stations in the northeast Arabian Sea between 16–26 April 2006. Data was analyzed for 5 offshore and 4 coastal stations of the cruise SS-244, on board FORV “Sagar Sampada” between latitude 9-22oN and longitude 68–74°E. The peak for all parameters was observed to be different respectively for depths 1, 5, 10, 20, 30, 40, 50 meters in coastal and offshore stations. Each peak in the respective wavelength is due to a particular composition; phytoplankton pigments have spectral peaks at 443, 490, 555, 670 nm, suspended matter, sediments have peaks at 630 and 670 nm. Detailed analysis with High Performance Liquid Chromatography (HPLC) data and comparison with the water composition of our hyperspectral radiometer results show that the marine cyanophyte, Trichodesmium bloom produces high pigment concentrations of chlorophyll-a, zeaxanthin, β-carotene and pheophytin and their absorptions are interpreted at wavelengths 443, 490, 515 and 536 nanometers, respectively. A dip around 515 nm was seen in the Ed and Lu profiles in our study.     

基于TM影像数据的五日生化需氧量浓度估计

湖泊的水体污染往往伴随着富营养化现象,水体中叶绿素a、透明度、全磷、全氮、化学需氧量及五日生化需氧量等水质参数的相关性很强.前人的研究成果表明,由于存在事实上的强相关性,可以直接建立全磷、全氮的遥感反演模型.基于这样的技术思想,洪泽湖水体内的五日生化需氧量与全磷、全氮有较强的相关性,本研究应用TM遥感影像数据直接建立了五日生化需氧量的半经验估算模型.该模型简便易用,是建立水质参数反演模型的成功尝试.     

Ocean color reveals phase shift between marine plants and yellow substance

Daily high-resolution Sea-viewing Wide Field-of-view Sensor (SeaWiFS) images of the central North Atlantic Ocean (1998-2003) show that temporal changes in the absorption coefficient of colored dissolved organic matter (CDOM) or "yellow substance" follow changes in phytoplankton pigment absorption coefficient in time. CDOM peaks (between January and March) and troughs (late summer and fall) followed pigment peaks and troughs by approximately two and four weeks, respectively. This phase shift is additional strong evidence that CDOM in the marine environment is derived from phytoplankton degradation. The common assumption of linear covariation between chlorophyll and CDOM is a simplification even in this ocean gyre. Due to the temporal changes in CDOM, chlorophyll concentration estimated based on traditional remote sensing band-ratio algorithms may be overestimated by about 10% during the spring bloom and underestimated by a similar 10% during the fall. These observations are only possible through use of synoptic, precise, accurate, and frequent measurements afforded by space-based sensors because in situ technologies cannot provide the required sensitivity or synoptic coverage to observe these natural phenomena.     

Re-parameterization of a quasi-analytical algorithm for colored dissolved organic matter dominant inland waters

Quasi-Analytical Algorithms (QAAs) are based on radiative transfer equations and have been used to derive inherent optical properties (IOPs) from the above surface remote sensing reflectance (R_rs) in aquatic systems in which phytoplankton is the dominant optically active constituents (OACs). However, Colored Dissolved Organic Matter (CDOM) and Non Algal Particles (NAP) can also be dominant OACs in water bodies and till now a QAA has not been parametrized for these aquatic systems. In this study, we compared the performance of three widely used QAAs in two CDOM dominated aquatic systems which were unsuccessful in retrieving the spectral shape of IOPS and produced minimum errors of 350% for the total absorption coefficient (a), 39% for colored dissolved matter absorption coefficient (a_CDM) and 7566.33% for phytoplankton absorption coefficient (a_phy). We re-parameterized a QAA for CDOM dominated (hereafter QAA_CDOM) waters which was able to not only achieve the spectral shape of the OACs absorption coefficients but also brought the error magnitude to a reasonable level. The average errors found for the 400–750 nm range were 30.71 and 14.51 for a, 14.89 and 8.95 for a_CDM and 25.90 and 29.76 for a_phy in Funil and Itumbiara Reservoirs, Brazil respectively. Although QAA_CDOM showed significant promise for retrieving IOPs in CDOM dominated waters, results indicated further tuning is needed in the estimation of a(λ) and a_phy(λ). Successful retrieval of the absorption coefficients by QAA_CDOM would be very useful in monitoring the spatio-temporal variability of IOPS in CDOM dominated waters.     

Retrieval of Brown Carbon based on the aerosol complex refractive indices in the winter of Wuhan

Abstract

The impact of Brown Carbon (BrC) to aerosol light absorption has been paid more attention recently and there are a large number of studies showing that the influence of BrC on radiative forcing should not be ignored. BrC also acts as an important component of haze pollution which is occurring frequently in Wuhan, China. Therefore, it is essential to estimate their optical properties, composition, and mass concentration. Considering most haze pollution happens during the coldest time, we retrieved BrC columnar content during winter in Wuhan for the first time. Our method bases on the fact that BrC showed the strong spectral dependence on UV-light absorption. Using this method, we found that BrC makes up the small proportions of total aerosol volume (less than 10%). In the winter of 2011, we retrieved the daily-averaged columnar-integrated mass concentration of BrC on clear day is 4.353 mg/m² while that of haze day is 12.750 mg/m². According to the sensitivity study, we found that the results highly relied on the assumed aerosol refractive index. To reduce the uncertainty of this approach, we need to gain a better understanding of the temporal variability of the radiation absorbing components of these aerosols in the future.     

南海水色遥感的主因子分析

分析了叶绿素、黄色物质和无机悬浮颗粒等要素对海水光谱反射率的贡献,并由这些要素的光学特性正演光谱反射率,与实测结果符合较好。在此基础上,利用主成分分析方法,通过对光谱反射率数据的特征向量变换和主因子回归,建立了反演南海海水叶绿素和溶解有机碳的遥感算法。与实测结果的比较表明,叶绿素和溶解有机碳的相对误差分别达１７５％和３７４％。