海星号卫星

海星号卫星潘德炉国家海洋局第二海洋研究所）卫星海洋水色遥感是指利用卫星资料测量影响海洋水色有关物质的浓度，水下光穿透深度以及海面大气气溶胶的分布。在海洋遥感学中，它是海洋可见光遥感的代名词。由卫星水色遥感得到的海面叶绿素分布专题图是估计海洋初级生产率...     

新一代海洋遥感水色传感器展望

一、水色遥感机理和遥感水色传感器的现状浮游植物生长引起的水色变化,是研究渔业和海洋生态的重要依据。海洋表层叶绿素α的浓度是海洋初级生产力的重要指数,是海洋食物链中的重要一环。几十年来海洋生物学家采用常规调查船方法进行水色调查和研究。由于遥感技术的发展,近十几年来科学家开始应用空间遥感手段获得全球性大洋水色几何分布图和随时间变化的分布图,从而发现浮游植物的     

渤海叶绿素a时空分布特征分析

叶绿素a是海洋初级生产力估算中的一个重要基础参数。本文以HY—1／COCTS为数据源，运用海洋叶绿素a的算法，计算出我国渤海的叶绿素a的分布。整个海域的叶绿素浓度的分布具有明显的分区和季节变化特征。基本规律是由于渤海的地理特征，叶绿素浓度从近岸向渤海中央方向递减；随着季节变化温度升高，近海叶绿素浓度增高，而渤海中央区域叶绿素浓度降低。渤海叶绿素a的分布与河口径流、季节等因素有关。从而为海洋初级生产力估算服务。     

浮游植物初级生产力的遥感研究综述

针对当前浮游植物初级生产力遥感研究存在的系统化、层次化总结不够的问题,综述了浮游植物初级生产力的遥感研究进展,并对其发展进行了展望。详细论述了浮游植物初级生产力的研究从基于现场观测的单点计算到逐步引入遥感手段的大尺度长时间序列估算的发展历程,并指出了生物-光学模式及新一代水色遥感传感器对浮游植物初级生产力估算的革命性意义。通过结合初级生产力遥感估算模型及相关文献计量的方法,重点探讨了垂向归纳模型(vertically generalized productivity model,VGPM)在进行浮游植物初级生产力估算领域的成就及其挑战。综述发现,利用黑白瓶等传统的手段已逐渐不适应初级生产力大尺度长时间序列估算的需要,未来通过提高遥感输入数据精度、修正和优化初级生产力遥感估算模型,有望实现浮游植物初级生产力大尺度和长时间序列的精确估算。     

我国获得美国Seastar卫星资料免费接收权

美国曾于1978年发射了专用于海洋水色监测的“雨云—7”号卫星,携带有沿岸带水色扫描仪(CZCS),该星一直工作到1986年。它成功地获取了全球性海洋水色资料,首次提供了全球性初级生产力估计的可能性,开创了卫星海洋水色遥感实际应用的新阶段。1994年初,美国将发射第二颗专用于海洋水色遥感的卫星“海星”号(Seastar),星上安装有更先进的水色扫描仪——宽视场水色扫描仪(Seawifs)。     

应用叶绿素荧光估算植被总初级生产力研究进展

日光诱导叶绿素荧光作为光能在叶片上光合作用的伴生产物，包含丰富的光合信息，被认为是可以表征植物光合作用的快速、无损“指示器”。叶绿素荧光在研究植物胁迫、病虫害监测、估算植被总初级生产力（Gross Primary Production， GPP）等方面发挥着独特的作用。陆地植被GPP是研究全球气候、碳循环变化、全球生态系统等的重要内容。准确、及时地掌握GPP的时空分布特征，有利于深入理解生物圈与大气圈之间的相互作用，可为开展减缓全球气候变化的生态过程管理提出相应建议和对策。相比于植被指数，叶绿素荧光对植被光合作用的敏感程度更高，已被证实可以更直接有效地监测GPP，显著优于传统的GPP估算方法。深入探讨了叶绿素荧光在遥感估算GPP领域的基本原理、方法、不确定性以及最新进展，并对其面临的挑战和未来趋势进行了分析。     

基于支持向量机的一类水域叶绿素a浓度反演研究

指出了用叶绿素a的浓度估计海洋初级生产力的重要作用;分析了目前采用的浓度反演方法的不足;尝试将基于统计学习理论的最小二乘支持向量机用于浓度反演, SeaBAM的数据实验结果表明该方法可以获得更高的反演精度;可以有效避免过学习的情况出现;不像神经网络那样需要确定网络结构。     

海洋水色遥感器发展趋势初探

海洋水色遥感技术是近年兴起的海洋探测技术。它通过各种遥感平台上的探测器对海洋表面的水色进行探测,反演出海洋水体中的叶绿素浓度、泥沙含量及黄色物质浓度,进而得到关于海洋的各种信息。本文介绍了未来几年的星载海洋水色遥感器,并将其与第二代海洋水色遥感器进行了初步对比,对其未来的发展趋势进行了展望。     

兴趣区域高分辨率叶绿素荧光遥感数据集重建框架

太阳诱导叶绿素荧光数据是反映全球植被总初级生产力的关键指标,对于监测全球或地区性的植被生产力变化和气候变化的影响具有重大意义.然而,目前为止仍没有高分辨率和全球覆盖的可用原始数据集.虽然存在一些全球性的重建数据集,但一般存在区域特异性不够明显等问题,从而一定程度上限制了该数据在特定的兴趣区域上的可用性.为了探索重建基于兴趣区域的叶绿素荧光数据的方法,本研究以华北平原为例,综合遥感数据处理技术,机器学习方法和生态学原理,对原始轨道碳观测者二号卫星所提供的叶绿素荧光数据集和MODIS地表反照率数据建模.重建数据集基于兴趣区域内原始数据的时空特征而建,具有连续的空间覆盖和更高的空间分辨率,经过验证,该框架可以为特定区域提供有效的有针对性的的叶绿素荧光数据,可为兴趣区域的与叶绿素荧光数据有关的研究提供数据支持.     

用于环境遥感的光学成像仪器的通道选择

1 着眼于二十一世纪的空间遥感人们已越来越感觉到人类赖以生存的地球环境正面临着全球的恶化,影响着社会和经济的发展。如全球气候变暖引起海平面上升,多发性气候异常,平流层臭氧层破坏,大气污染与酸雨,海洋初级生产力的重大变化,森林破坏和沙漠的扩大。所有这些都涉及全球尺度上的大气、海洋、冰雪、陆地地表与生物圈之间复杂的相互作用。早在1978年,世界气象组织(WMO)就提出全球大气研究计划(GARP),第一期全球试验     

Effect of May 2003 tropical cyclone on physical and biological processes in the Bay of Bengal

Satellite observations are beginning to show the remarkable effects of tropical cyclones on upper ocean temperature and chlorophyll concentration. We use weekly, 4 km resolution chlorophyll‐a and sea surface temperature (SST) from TERRA Moderate Resolution Imaging Spectroradiometer, weekly averaged SST at 0.25° resolution from Tropical Rainfall Measuring Mission Microwave Imager, modeled primary productivity (PP) from Goddard Space Flight Center and mixed layer depth generated by US Navy's Fleet Numerical Meteorology and Oceanography Center to study the response of upper ocean physics and biology to the passage of a tropical cyclone in the southern Bay of Bengal. Decrease in SST up to 5°C, associated with the deepening of mixed layer by about 12 m, was observed. Directly under the cyclone track, PP increased from its pre‐storm value by up to 3800 mg C m^?2 day^?1, and chlorophyll‐a concentration also increased. The increase in chlorophyll‐a and productivity were not confined to the region under the cyclone track, but covered a much broader area, possibly due to forced coastal upwelling south of Sri Lanka. After the passage of the cyclone the SST slowly increased, and the chlorophyll decreased.     

Bottom influence on the estimation of chlorophyll concentration in water from remotely sensed data

Remote sensing algorithms that provide for the computation of chlorophyll concentration in surface waters are an important tool for the synoptic mapping of ocean optics and primary productivity. The remote sensing of chlorophyll concentration in Case 1 coastal waters ( waters whose optics are primarily controlled by biologic content) could present a problem due to the presence of the bottom itself and the possible contribution of bottom reflected light to the upwelling light stream ultimately ‘ seen’ by a remote sensor. The present work analyzes the impact on the estimation of chlorophyll concentration when a bottom is present. Multiple plots are used to exhibit and quantify the effects the presence of a bottom and bottom reflected light have on chlorophyll computation algorithms. Further, a new water type definition is proposed and threshold optical depths are calculated that provide values at which the presence of a benthic interface and bottom reflected light no longer contribute to the remotely observed upwelling light stream.     

A study of the stationary and the anomalous in the ocean surface chlorophyll distribution by satellite data

Variability of chlorophyll concentration in the ocean is one of the most important components of the primary production process on the planet. To preserve the biosphere and to make appropriate use of it, it is imperative to have a deep insight into the long-term dynamics of the primary production on the planet. To investigate the dynamics of chlorophyll concentration based on satellite data, the Institute of Biophysics (Russian Academy of Sciences, Siberian Branch) has developed a geoinformation system. It was used to detect the areas in the global ocean that are quasistationary in relation to seasonal dynamics of chlorophyll concentration. Areas such as these, found in the Indian Ocean, are described in this work. These areas form the basis for the analysis of long-term dynamics of chlorophyll concentration. In these quasistationary zones systematic monitoring of phytopigment concentration is conducted by space-borne and marine craft. The work presents long-term satellite-based data on the space distribution of anomalous deviations of chlorophyll concentration in the ocean. An anomaly criterion is proposed and maps of Pacific Ocean areas with a high probability of anomalies are presented.     

Remote sensing of sea surface Sun-induced chlorophyll fluorescence: consequences of natural variations in the optical characteristics of phytoplankton and the quantum yield of chlorophyll a fluorescence

The rate of Sun-induced chlorophyll a fluorescence (SICF) observed at sea surface is determined by chlorophyll a concentration, incident irradiance, and optical and fluorescence properties of the phytoplanktonic population. In this study, the impact of natural variations in the two latter on the use of remotely sensed SICF to determine ocean surface chlorophyll a concentration, is assessed using a simple parameterization of phytoplankton optical properties and a model describing the variations in the quantum yield of chlorophyll a fluorescence as a function of environmental factors, such as excess irradiance and nutrient limitations. It is shown that (1) variations in the optical properties of phytoplankton are the main cause of non-linearity in the relationship between SICF and chlorophyll a concentration, (2) the extent of spatial variations in the rate of fluorescence per unit chlorophyll a concentration and irradiance, at the level of a typical sensor scene, prevents the use of a linear relationship between SICF and chlorophyll a concentration even at local scales and (3) the optical properties of the ocean surface layer play an important role in modifying the SICF signal. Nevertheless, the parameterizations presented in this paper may represent a reasonably sound approach for a meaningful use of SICF in view of detecting the chlorophyll a concentration within the upper layer of the ocean. Interestingly, it is also shown that the detection threshold of SICF could be significantly lower than the one currently expected.     

The colour of the Mediterranean Sea: Global versus regional bio-optical algorithms evaluation and implication for satellite chlorophyll estimates

In this paper, uncertainties in the retrieval of satellite surface chlorophyll concentrations in the Mediterranean Sea have been evaluated using both regional and global ocean colour algorithms. The rationale for this effort was to define the most suitable ocean colour algorithm for the reprocessing of the entire SeaWiFS archive over the Mediterranean region where standard algorithms were demonstrated to be inappropriate. Using a large dataset of coincident in situ chlorophyll and optical measurements, covering most of the trophic regimes of the basin, we validated two existing regional algorithms [Bricaud, A., E. Bosc, and D. Antoine, 2002. Algal biomass and sea surface temperature in the Mediterranean Basin — Intercomparison of data from various satellite sensors, and implications for primary production estimates. Remote Sensing of Environment, 81(2-3), 163-178.; D'Ortenzio, F., S. Marullo, M. Ragni, M. R. d'Alcala and R. Santoleri, 2002. Validation of empirical SeaWiFS algorithms for chlorophyll-alpha retrieval in the Mediterranean Sea — A case study for oligotrophic seas. Remote Sensing of Environment, 82(1), 79-94.] and the global algorithm OC4v4 used for standard NASA SeaWiFS products. The results of our analysis confirmed that the OC4v4 performs worse than the two existing regional algorithms. Nonetheless, these two regional algorithms do show uncertainties dependent on chlorophyll values. Then, we introduced a better tuned algorithm, the MedOC4. Using an independent set of in situ chlorophyll data, we quantified the uncertainties in SeaWiFS chlorophyll estimates using the existing and new regional algorithms. The results confirmed that MedOC4 is the best algorithm matching the requirement of unbiased satellite chlorophyll estimates and improving the percentage of the satellite uncertainty, and that the NASA standard chlorophyll products are affected by an uncertainty of the order of 100%. Moreover, the analysis suggests that the poor quality of the SeaWiFS chlorophyll in the Mediterranean is not due to the atmospheric correction term but to peculiarities in the optical properties of the water column. Finally the observed discrepancy between the global and the regional bio-optical algorithms has been discussed analysing the differences between the two in situ datasets used for tuning the algorithms (SeaBASS versus ours). The main results are that methodological differences in the two datasets cannot play a major role and the inherent bio-optical properties of the basin can explain the observed discrepancy. In particular the oligotrophic water of the Mediterranean Sea is less blue (30%) and greener (15%) than the global ocean.     

Variability of chlorophyll concentration in the Arabian Sea and Bay of Bengal as observed from SeaWiFS data from 1997–2000 and its interrelationship with Sea Surface Temperature (SST) derived from NOAA AVHRR

Variability of chlorophyll concentration in the Arabian Sea and Bay of Bengal has been studied using SeaWiFS eight‐day average, 9 km processed data for the period 1997–2000. The interrelationship with sea surface temperature (SST) was studied with the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) derived, best SST product. The chlorophyll pattern shows in general high concentrations during February to March in the Arabian Sea and November to December in the Bay of Bengal. Year‐to‐year variations in temperature show an inverse relation with chlorophyll, at different locations, even on a monthly basis. However, the intraannual variability in chlorophyll at different locations shows differences in the relationship with SST. The Arabian Sea showed an inverse relationship at most of the locations, while a positive relationship was observed in the northwest region during October to December and an inverse relationship during January to April. The Bay of Bengal showed positive relationships at northeast locations, whereas no definite assessment could be made for other locations due to the narrow range of chlorophyll concentration.A longer time series (～10 years) will be required to establish a more concrete relationship but definitely consistent patterns are emerging from this study. The results form an additional dimension to the criteria for partitioning the ocean, required for global productivity or biophysical coupled modelling.     

Internal solitary waves in the China seas observed using satellite remote-sensing techniques: a review and perspectives

Internal solitary waves (ISWs) occur ubiquitously in China’s waters: the South China Sea (SCS), the East China Sea (ECS), the Yellow Sea (YS), and the Bohai Sea (BS). ISWs have long attracted much research interest because of their important role in ocean acoustics, offshore engineering, ocean mixing, primary productivity, and submarine navigation. ISWs have sea surface signatures that can be detected by satellite synthetic aperture radar (SAR) and optical sensors. Satellite remote-sensing images provide excellent two-dimensional views of the ISW field. Our understanding of ISWs in the China Seas has been greatly improved using satellite remote-sensing techniques. The primary objectives of this paper are to review the development of remote-sensing techniques in the study of ISWs and to summarize ISW characteristics in the China seas, mainly demonstrated by remote-sensing techniques. In addition, several issues with remote-sensing techniques and interesting research topics are discussed.     

Variations of ocean colour parameters with nonuniform vertical profiles of chlorophyll concentration

Based on radiative transfer simulations, the effects of nonuniform chlorophyll profiles in case 1 waters on the penetration depth, the above‐surface spectral remote‐sensing reflectance, and the optically weighted chlorophyll concentration are investigated. The simulations for nonuniform chlorophyll profiles are compared with those for homogeneous ocean whose chlorophyll concentrations are identical to the surface chlorophyll concentrations in the inhomogeneous ocean. Due to influence of the nonuniformity of chlorophyll profile, the maximum relative error for the penetration depth at 445 nm is more than 60%, the spectral remote‐sensing reflectance is about 40% and the optically weighted chlorophyll concentration is about 40% within the range of our simulations. However, the simulation shows that there is always a spectral band where the value of above‐surface remote‐sensing reflectance is not influenced by the nonuniformity. Depending on this band, a new model for retrieving sea surface chlorophyll concentration is designed by adding a compensation term into the variable in SeaWiFS OC2V4 algorithm. By using an iterative method with this new model, sea surface chlorophyll concentration can be well retrieved even in an area where the vertical chlorophyll distribution is unknown.     

A class-based approach to characterizing and mapping the uncertainty of the MODIS ocean chlorophyll product

Global chlorophyll products derived from NASA's ocean color satellite programs have a nominal uncertainty of ± 35%. This metric has been hard to assess, in part because the data sets for evaluating performance do not reflect the true distribution of chlorophyll in the global ocean. A new technique is introduced that characterizes the chlorophyll uncertainty associated with distinct optical water types, and shows that for much of the open ocean the relative error is under 35%. This technique is based on a fuzzy classification of remote sensing reflectance into eight optical water types for which error statistics have been calculated. The error statistics are based on a data set of coincident MODIS Aqua satellite radiances and in situ chlorophyll measurements. The chlorophyll uncertainty is then mapped dynamically based on fuzzy memberships to the optical water types. The uncertainty maps are thus a separate, companion product to the standard MODIS chlorophyll product.