Study on detection of coastal water environment of China by ocean color remote sensing

Coastal water environment is essentially enhanced by ocean color which is basically decided by substances concentration in water such as chlorophyll, suspended material and yellow substance. It is very difficult, even not possible, to detect water color by expensive ship routing, because of its temporal and spatial variety of feature and scales in the very complicated dynamical system of coastal water. With the development of satellite technique in the last 20 a, space sensors can be applied to detect ocean color by measuring the spectra of water leaving radiance.It is proven that ocean color remote sensing is a powerful tool for understanding the process of oceanic biology and physics. Since the 1980s, great attention has been paid to the advanced remote sensing technique in China, especially to development of satellite programs for the coastal water environment. On 7 September 1988, China launched her first polar orbit satellite FY-1A for meteorological and oceanographic application (water color and temperature) and the second satellite FY-1B two years later. In May 1999, China launched her second generation environment satellite FY-1C with higher sensitivies, more channels and stable operation. The special ocean color satellite HY-1 is planned to be in the orbit in 2001, whose main purpose is to detect the coastal water environment of China seas. China is also developing a very advantageous sensor termed as Chinese moderate imaging spectra radiometer (CMODIS) with 91 channels, which will be a good candidate of the third generation satellite FY-3 in 2003. The technical system of ocean color remote sensing was developed by the Second Institute of Oceanography (SIO), State Oceanic Administration (SOA) in 1997. The system included data receiving, processing, distribution, calibration, validation and application units. The Hangzhou Station of SIO, SOA has the capability to receive FY-1 and AVHRR data since 1989. It was also a SeaWiFS scientific research station authorized by NASA,USA to free receive SeaWiFS data from 16 September 1997. In the recent years, the local algorithms of atmospheric correction and inversion of ocean color have been developed for FY-1C and SeaWiFS, to improve the accuracy of the measurement from satellites efficiently. The satellite data are being applied to monitor coastal water environment, such as the spatial distribution of chlorophyll, suspended material and yellow substance, red tide detection and coastal current study. The results show that the ocean color remote sensing has latent capacity in the detection of coastal water environment.In consideration of the update technique progress of ocean color remote sensing and its more important role in the detection of coastal water in the 2000s, some suggestions are set forth, which would be beneficial to the design of a cheaper but practical coastal water detection system for marine environment preservation.

The application of hyperspectral remote sensing to coast environment investigation

Requirements for monitoring the coastal zone environment are first summarized.Then the application of hyperspectral remote sensing to coast environment investigation is introduced,such as the classification of coast beaches and bottom matter,target recognition,mine detection,oil spill identification and ocean color remote sensing.Finally,what is needed to follow on in application of hyperspectral remote sensing to coast environment is recommended.

Atmospheric correction of ocean color imagery over turbid coastal waters using active and passive remote sensing

This paper demonstrates an atmospheric correction method to process MODIS/Aqua (Moderate-resolution Imaging Spectroradiometer) ocean color imagery over turbid coastal waters with the aid of concurrent CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization) aerosol data, assuming that there exists "nonturbid" water in the study area where MODIS aerosol optical properties can be retrieved accurately. Aerosol properties from CALIOP measurements were obtained and related to those from MODIS. This relationship, combined with CALIOP aerosol data, was extended to turbid water to derive MODIS aerosol properties, where atmospheric correction using MODIS data alone often fails. By combining MODIS and CALIOP data, aerosol signals were separated from the total signals at the satellite level, and water-leaving radiances in turbid waters were subsequently derived. This method was tested on several MODIS/Aqua ocean color images over South China turbid waters. Comparison with field data shows that this method was effective in reducing the errors in the retrieved water-leaving radiance values to some extent. In the Zhujiang (Pearl) River Estuary, this method did not overestimate the aerosol effects as severely, and provided far fewer negative water-leaving radiance values than the NASA (National Aeronautics and Space Administration) default methods that used MODIS data alone.

Evolution of a coastal upwelling event during summer 2004 in the southern Taiwan Strait

A coastal upwelling event in the southern Taiwan Strait (STWS) was investigated using intensive cruise surveys (four repeated transects in a month) and satellite data in July and early August 2004.The extensive upwelling-associated surface cold water was first observed in early July (～2.0×10 4 km 2) along the STWS coast.Then,the cold surface water reduced in size by ～50% with decreased chlorophyll concentrations after 15 days,indicating the weakening of the upwelling event.At the end of July,the cold surface water disappeared.The temporal variations of the surface cold water and the 3-D hydrography around Dongshan Island are thought to be mainly attributed to the weakened upwelling-favorable southwestern wind,the asymmetric spatial structure of the wind field and the intrusion of warm water from the northern South China Sea.

我国海岸带海岛礁遥感研究进展及建议

为厘清我国海岸带海岛礁遥感近年来发展取得的成就以及存在的问题,本文摘选近十年来若干典型性研究,按照“近海陆域–潮间带–近海水域–海岛礁”的空间顺序进行综述和探讨。总体而言,海岸带的土地覆盖、海岸线等仍是当前遥感应用研究的热点;同时,随着我国经济的快速发展和城镇化出现的环境问题,地面沉降、海水入侵、潮间带生态监测、海水养殖、赤潮、岛礁证据等新兴遥感应用方向也取得大幅进展,有效支撑了国家海洋战略。但同时也发现使用的遥感数据自主性不强、遥感信息更新频率低、学科孤立发展难以满足实际需求等问题。建议加强国产多源数据协同、多学科交叉以及大数据云平台支持下的大范围与局部高精度自动化、常态化监测等。

DOC遥感研究进展——基于全球大河DOC与CDOM保守性特征

目前,溶解有机碳(DOC)遥感反演研究主要集中在河口及陆源影响较大的边缘海区,大多数是利用DOC与有色溶解有机物(CDOM)或DOC与盐度的经验关系获取。为了较好的理解DOC的遥感反演机理,收集了全球主要大河(流量排名前25中16条)及边缘海DOC与CDOM浓度与保守性分布状况,发现大多数河口CDOM呈现保守性分布,DOC呈现非保守性分布。基于DOC与CDOM保守性行为的主要影响因素分析以及研究海区的生物地球化学特征,论述了DOC遥感反演算法的研究进展,提出了DOC遥感反演需要考虑DOC受不同主要控制因素(如保守混合与生物作用等)的影响,并对这些控制因素进行量化。

海岸带高光谱影像分类技术研究

以海岸带地物分类研究为重要对象,针对传统海岸带区域地物及海水等目标分类技术的局限性,通过分析海岸带地物的光谱特征以及在高光谱数据中的表征,研究高光谱成像技术在海岸带遥感应用中的有效性。实验结果表明相对传统的遥感影像分类技术,高光谱海岸带分类显得更为精细,也展示了高光谱技术在海洋遥感中的巨大应用前景。

海洋卫星北极多区域遥感成像任务规划及应用评估

北极区域海冰是影响北极船舶航行安全的重要因素,由于该区域现场观测站点少,卫星遥感成为监测北极海冰变化的主要手段。为满足北极海域重点区块遥感观测的需求,结合海洋卫星轨道预测技术和海岸带成像仪的载荷特点,本文提出了一种多区域成像的卫星探测任务规划算法。简化的轨道预报模型和规划算法均为自主设计、独立编程,脱离商用软件的约束,自动化程度高,经过海洋一号C卫星的应用实践,验证了该算法满足近实时的观测需求,改变了以往无差别接收任务规划的不合理局面,有效提高了卫星资源的应用效能,为北极航运提供更好的支撑服务。

Landsat-8的舟山近岸海域总悬浮物遥感反演与时空变异研究

总悬浮物(TSM)是海洋水质和水环境评价的主要参数之一。舟山海域位于杭州湾边缘,泥沙含量多,总悬浮物长期处于高浓度状态,其分布与动态变化对近岸水质、水循环以及该区域的渔业、旅游业都有较大影响。Landsat-8卫星影像作为一种应用广泛、空间分辨率高、便于获取的光学信息,可以为舟山海域的TSM观测提供有力的技术手段。利用舟山近岸海域实测TSM吸收系数ap(440)和水面光谱,开发了基于Landsat-8反演TSM的最优模型,发现基于近红外和蓝色波段比B5/B2的S-函数和线性函数模型反演精度较好,相对于线性模型,S-函数具有更强的鲁棒性,该模型形式为ap=3.72/(0.009+e-5.249B5/B2),克服了常用函数模型(如线性、对数、指数函数)应用于实际卫星影像时出现光谱幅度范围受限的困难。海岸带内陆复杂水体水色遥感的另一难点是大气校正,以往的研究往往只采用某种大气校正模型,但该模型不一定适合研究水域,从而使得校正结果并不一定是最优的。在本研究中,验证比较了FLAASH,6S和ACOLITE三种大气校正方法面向Landsat-8水色反演的校正结果,发现ACOLITE方法获取的光谱形状最准确,误差最小,特别在蓝色波段,明显好于FLAASH和6S方法。将最优模型应用于舟山近岸海域2013到2018年的10幅Landsat-8图像。实测数据和反演结果显示:舟山近岸海域的TSM吸收系数ap(440)的变化范围在1.64~417.04 m^-1,均值118.47 m^-1,TSM吸收占水体总吸收的90%以上,该海域实测的水面光谱形状呈现典型的河口海岸带复杂浑浊水体的光谱特征,很多光谱曲线具有双峰特征,遥感反射率幅值较大,特别是红色、近红外波段,由于受河口高浓度TSM的影响,遥感反射率高于远海较清洁的海水;衢山、洋山、宁波等近岸区域的TSM浓度明显高于东极、嵊泗等远海区域,随河口羽化区呈现由高到低的梯度变化,在近岸区域分布复杂,外海区域分布较为均匀。在时间分布上具有冬季浓度远高于夏季的特点,其中12月最高,最大值为413.32 m^-1,8月最低,最小值为3.69 m^-1,5月、10月期间也有TSM的局部峰值。这些TSM时空变异特征表明舟山海域悬浮物的分布和变化一方面受地形、海流、潮汐、季风、台风等自然环境因素的影响,另一方面也受如海运、港口建设、海岛旅游等人类活动的较大影响。

Estimation of chlorophyll-a concentration in the Zhujiang Estuary from SeaWiFS data

The chlorophyll-a concentration is generally overestimated for the southem China coastal waters if the default algorithm of the SeaDAS is employed. An algorithm is developed for retrieval of chlorophyll-a concentration in the Zhujiang Estuary, Guangdong Province, China, by using simulated reflectance data. The simulated reflectance is calculated corresponding to the SeaWiFS wavelength bands, via a general model by inputting measured water components, I.e., the suspended sediment,chlorophyll-a, and yellow substance (DOC) concentration data of 130 samples. Empirical relationships of the chlorophyll-a concentration to 240 different band combinations are investigated based on the simulated reflectance data, and the band combination, R5R6/R3R4, is found to be the optimum one for the development of an algorithm valid for the Zhujiang Estuary. This algorithm is then employed to determine the chlorophyll-a concentration from SeaWiFS data. The estimated concentrations have a better accuracy than those obtained from the SeaDAS default algorithm when comnpared with sea truth data. The new algorithm is demonstrated to work well and is used to derive a series of image maps of the chlorophyll-a concentration distribution for the Zhujiang Estuary and adjacent coastal areas.

胶州湾及青岛近海水中颗粒物散射特性及其分类

胶州湾位于山东半岛南部,是黄海西部的一个半封闭海湾,是北温带海湾生态系统的重要代表。由于水体交换能力不足,容纳的污染物总量较大,胶州湾及青岛近海水体富营养化问题突出,对其水质进行实时有效监测意义重大。2014年8月和2015年10月在胶州湾及青岛近海进行了两次海洋光学现场实验,测量海水固有光学性质。利用高光谱吸收衰减仪ac-s测量了海水吸收系数和衰减系数光谱剖面,并计算了海水散射系数光谱剖面;利用后向散射仪BB9(2014年航次)和HS6(2015年航次)测量了海水后向散射系数光谱剖面,并计算了水中颗粒物的后向散射比。利用现场测量数据,建立了悬浮粒子散射系数和后向散射系数光谱模型,以及532 nm处后向散射系数与散射系数的关系模型。利用后向散射比提供的粒子折射率信息分析了胶州湾及青岛近海海域的粒子组成及其空间分布情况。最后分析了悬浮粒子散射特性与浓度SPM的关系。研究结果表明:胶州湾内的散射系数b p和后向散射系数b bp值普遍高于青岛近海,并且胶州湾内越靠近岸边的站位,其值越大,胶州湾内站位的散射系数b p光谱斜率(m=0.56)较青岛近海站位大(m=0.44);胶州湾及青岛近海海域的粒子后向散射系数和散射系数之间存在幂指数回归关系;研究海域的粒子折射率在1.097~1.197之间,粒子组成以无机矿物粒子为主,两次现场实验的结果表明湾口站位(JZ1,QD1和QD7)的折射率变化不大。选取从湾内经湾口到青岛近海的站位组成断面,分析这些站位粒子折射率n p的分布发现,湾内从近岸(JZ9)到湾口(JZ1),粒子折射率逐渐增大,湾内粒子无机成分更多;青岛近海离岸越远(QD7—QD5),粒子折射率逐渐减小,有机粒子的成分增加。JZ6站位为靠近胶州湾大桥的站位点,粒子折射率明显小于大桥两边的站位。后向散射系数与SPM浓度之间存在线性回归和幂指数回归关系,但幂指数回归结果优于线性回归结果。

面向海岸带陆海相互作用研究的e-CoastalScience平台研发与设计

总结了海岸带区域的特殊性以及海岸带陆海相互作用研究的特点和所面临的挑战,分析了海岸带陆海相互作用研究对e-Coastal Science平台研发的需求,设计了由3个技术层面、5个研究单元和4个技术单元所组成的e-Coastal Science平台整体框架,并明确了平台研发与设计的任务重点以及关键的支撑技术,进而对e-Coastal Science的发展前景进行了展望。

Atmospheric correction of HJ-1A/B CCD images over Chinese coastal waters using MODIS-Terra aerosol data

This paper demonstrates an atmospheric correction method to process HJ-1A/B CCD images over Chinese coastal waters with the aid of MODIS-Terra aerosol information.Based on the assumption of zero water-leaving radiance at the two near-infrared (NIR)bands or the shortwave infrared(SWIR)bands,the atmospheric aerosol optical depth(AOD)is firstly retrieved from MODIS-Terra with a simple extension of the NIR-SWIR combined atmospheric correction approach embedded in SeaDAS (SeaWiFS data analysis system).Then the"turbid"and"non-turbid"waters are separated by the turbid water index.Maximum probability of AOD at 551 nm band is derived based on the NIR information over"non-turbid"waters and FLAASH model is selected to do the atmospheric correction of the HJ-1A/B CCD imagery using the AOD values of highest probabilities as input.Similarly,according to the histogram of the AOD distribution at 551 nm band,the studied turbid water area is divided into several blocks and HJ-1A/B CCD imagery is corrected with the corresponding AOD values displayed with the highest frequency in each block.This method has been applied to several HJ-1A/B images over Chinese coastal waters and validated by synchronous in-situ data.The results have shown that this method is effective in the atmospheric correction process of HJ-1A/B CCD images for ocean color remote sensing study and application in the coastal waters.

面向海岛海岸带区域的高分遥感影像智能化色彩增强方法

原始高空间分辨率海岛海岸带遥感影像往往存在影像灰暗、偏色、地物信息较难辨识的现象。为及时获取清晰、信息丰富、反差适中、亮度均匀的海岛礁遥感影像,满足日益强烈的海岛海岸带地理信息保障需求,针对海岛海岸带高空间分辨率遥感影像,该文提出一种深度学习结合改进直方图匹配的智能化调色方法。首先,进行数据重采样与自适应分块获取抽稀影像;其次,应用MBLLEN网络对抽稀影像进行真彩色增强;最后,采用改进直方图匹配的方法对原始影像进行色彩映射,最终得到符合人眼视觉、色彩一致、细节丰富的遥感影像。采用主客观相结合的方式综合评价调色效果,结果表明:相较于Retinex,HE和MASK等常用调色方法,该文算法结果更符合人眼视觉、色彩一致、细节丰富,可有效改善海岛海岸带高空间分辨率遥感影像视觉效果,较好地保留原始地物的细节信息,大幅提升调色效率。

HY-1C/D卫星CZI数据监测湖泊藻华的适用性评价与方法选择

随着湖泊富营养化加剧,蓝藻水华频发暴发,藻华的卫星遥感监测面临着中高空间分辨率卫星过境时间长、中低空间分辨率卫星数据在小型湖泊监测能力不足的问题。海洋水色业务卫星海洋一号C星和D星(HY-1C/D)搭载的海岸带成像仪CZI(Coastal Zone Imager)具有50 m空间分辨率,3 d重访周期,是内陆中小型湖泊藻华遥感监测的重要数据源。本文构建了以CZI数据的绿光(560 nm)—近红外波段(825 nm)连线作为基线,红光波段(650 nm)到该基线的垂直距离作为藻华识别指数AFAH(Adjusted Floating Algae Height),并将其应用在4个典型的富营养化湖泊(太湖、巢湖、滇池、星云湖),评价了其在湖泊藻华遥感监测方面的适用性和不确定性。结果表明:(1)在无云的理想条件下4种藻华识别指数的藻华识别精度高于0.93;在非理性条件下的藻华识别方面,AFAH优于NDVI(Normalized Difference Vegetation Index)、DVI(Difference Vegetation Index)和VB-FAH(Virtual baseline floating macro Algae Height),对太阳耀斑、云、气溶胶厚度敏感性较低;(2)采用最大梯度法确定了单景影像的AFAH的藻华提取阈值,太湖、巢湖、滇池、星云湖有藻华的数据共180景,AFAH藻华提取阈值的统计均值为0.041,标准差为0.013;(3)2019年7月到2021年7月期间4个湖泊的藻华发生频率空间分布结果与已有研究一致,藻华暴发频率大于5%的面积分别为609.05 km^(2)、134.43 km^(2)、20.91 km^(2)、14.50 km^(2),主要集中在太湖竺山湾、梅梁湾、太湖西部,巢湖西部,滇池和星云湖分散状全湖分布。研究表明,AFAH可以应用于仅包含一个近红外波段的中高空间分辨率卫星,可拓展到多源卫星数据的藻华业务化监测,以提高观测频次。

星载激光雷达气溶胶数据辅助的近岸浑浊水体大气校正研究

提出了一种星载激光雷达CALIOP气溶胶数据辅助的MODIS/Aqua水色数据大气校正方法,并在长江口及其邻近浑浊水体区域进行了实验。通过与实测光谱数据的对比分析说明,本文方法能在一定程度上避免如近红外波段离水辐亮度为零的假设的不合理性,摆脱对实测数据的依赖,有效地反演离水辐亮度,修复SeaDAS软件中短波红外-近红外联合大气校正算法中短波红外波段引起的产品的条带问题。

高光谱海岸带区域分割的活动轮廓模型

近年来,高光谱遥感图像的分割作为地物识别和异常目标探测等应用的基础工作而受到重视,而高光谱遥感图像的海量数据和复杂结构使其分割技术成为一项挑战性的工作。在对海岸带高光谱遥感图像的光谱特性进行分析的基础上,提出一种基于光谱特性的海岸带水、陆区域分割的偏微分方程活动轮廓模型:首先以高光谱海岸带图像的海域像元光谱信息为参照点,构建海岸带高光谱图像的能量偏差矩阵;在此基础上建立适应该能量偏差矩阵的水、陆区域分割的活动轮廓模型。模型通过引入基于梯度的边缘引导函数,提升了对水、陆区域边缘的捕捉能力和抗噪声干扰能力。实验结果表明,与传统活动轮廓模型相比,本文模型不仅能够保证水、陆区域分割的精度,而且具有更快的计算速度。