Understanding the Spatial Variability of Chlorophyll a and Total Suspended Matter Distribution Along the Southwest Bay of Bengal Using In-Situ and OCM-2 & MODIS-Aqua Measurements

Spatial and temporal distribution of chlorophyll a (chl a) and Total Suspended Matter (TSM) and inter comparison of Ocean Color Monitor-2 (OCM-2) and Moderate Resolution Imaging Spectro-radiometer (MODIS-Aqua) derived chlorophyll a and TSM was made along the southwest Bay of Bengal (BoB). The in-situ chl a and TSM concentration measured during different seasons were ranged from 0.09 to 10.63 μgl^?1 and 11.04–43.75 mgl^?1 respectively. OCM-2 and MODIS derived chl a showed the maximum (6–8 μgl^?1) at nearshore waters and the minimum (0–1 μgl^?1) along the offshore waters. OCM-2 derived TSM imageries showed the maximum (50–60 mgl^?1) along the nearshore waters of Palk Strait and the moderate concentration (2–5 mgl^?1) was observed in the offshore waters. MODIS derived minimum TSM concentration (13.244 mgl^?1) was recorded along the offshore waters, while the maximum concentration of 15.78 mgl^?1 was found along the Kodiakarai region. The inter-comparison of OCM-2 and MODIS chl a data (R ² ?=?0.549, n?=?49, p?<?0.001, SEE?=?±0.117) indicate that MODIS data overestimates chl a concentration in the nearshore waters of the southern BoB compared to the OCM-2. The correlation between OCM-2 and MODIS-Aqua TSM data (R ² ?=?0.508, N?=?53, P?<?0.001 and SEE?=?±0.024) confirms that variation in the range of values measured by OCM-2 (2–60 mgl^?1) and the MODIS (13–16 mgl^?1) derived TSM values. Despite problems in range of measurements, persistent cloud cover etc., the launch of satellites like OCM-2 with relatively high spatial resolutions makes job easier and possible to monitor chl a distribution and sediment discharges on day to day basis in the southwest BoB.     

Remote Sensing of suspended sediments along the Tamil Nadu coastal waters

Indian Remote Sensing satellite (IRS) 1A & 1B digital data in combination with field measurement were used to map distribution and concentration of suspended sediments along the Tamil Nadu coastal waters for monsoon and non-monsoon periods. Qualitative suspended sediment mapping was done for entire Tamil Nadu coast while quantitative studies were taken at two selected sites (eg. Tuticorin and Ennore). For qualitative mapping both monsoon (17-12-90) and non-monsoon (18-4-90) season data were analysed by level slicing technique and a qualitative scale was assigned to different sediment classes based on tonal variations. The suspended sediment concentration (SSC) samples were collected on April 15, 1992 and March 10, 1992 around Ennore and Tuticorin coastal waters respectively, synchronous to IRS-1A satellite overpass. This data was used for quantitative estimation of SSC using digital chromaticity technique. The study shows that the plumes of high suspended sediment concentration are contributed from the nearshore wetlands and river mouths and were finally dispersing towards Jaffna coast. Different classes of high to low SSC values ranging from less than 5 mg/L in offshore areas to 21 mg/L in nearshore of Tuticorin were also delineated. The dispersal pattern of the sediments on different is discussed.     

基于神经网络的二类水体大气修正

大气修正是海洋水色遥感中的关键技术之一。近海二类水体大气修正面临两个挑战：浑浊水体造成NIR大气修正波段的离水辐射明显大于零;近海上空存在较强吸收性的气溶胶。本文针对HY-1A CZI,在辐射传输模拟的基础上建立了基于神经网络技术的二类水体大气修正算法,可以由波段1-4的TOA反射率和三个角度反演得到离水反射率、气溶胶光学厚度等参数。利用模拟数据进行了算法的性能评估,并开展了卫星数据处理试验。结果表明,除了在非常浑浊的水体,反演结果基本合理。     

Empirical Estimation of Nearshore Waves From a Global Deep-Water Wave Model

Global wind-wave models such as the National Oceanic and Atmospheric Administration WaveWatch 3 (NWW3) play an important role in monitoring the world's oceans. However, untransformed data at grid points in deep water provide a poor estimate of swell characteristics at nearshore locations, which are often of significant scientific, engineering, and public interest. Explicit wave modeling, such as the Simulating Waves Nearshore (SWAN), is one method for resolving the complex wave transformations affected by bathymetry, winds, and other local factors. However, obtaining accurate bathymetry and determining parameters for such models is often difficult. When target data is available (i.e., from in situ buoys or human observers), empirical alternatives such as artificial neural networks (ANNs) and linear regression may be considered for inferring nearshore conditions from offshore model output. Using a sixfold cross-validation scheme, significant wave height H_s and period were estimated at one onshore and two nearshore locations. In estimating H_s at the shoreline, the validation performance of the best ANN was r=0.91, as compared to those of linear regression (0.82), SWAN (0.78), and the NWW3 H_s baseline (0.54)     

联合大地水准面、海面地形和潮波运动数值模拟的长江口陆海垂直基准转换关系

长江口水域地形地貌研究对河道治理建设、水上交通运输等人类社会经济活动具有重要意义,而建立高精度的无缝深度基准面及其与其他垂直基准间转换模型将直接影响到水陆交界区高精度地形地貌数据的获取及统一综合管理与分析。为此着重研究了基于三维潮波运动数值模拟、海面地形和大地水准面3种手段联合的河口水域无缝深度基准面构建及其与其他垂直基准间转换模型,并在长江口南支这一典型河口水域进行了建模实验和模型精度评估分析。结果显示,垂直基准转换模型中误差为12.4 cm,与现场长期潮位站实际观测结果比对分析得垂直基准转换模型误差绝对值均值为24.2 cm,尽管大于模型中误差估值,但仍满足国际水道测量规范对测深中垂向最大不确定度的要求。     

海洋激光雷达反演水体光学参数

研制了一套船载海洋激光雷达,用于探测海水光学参数垂直廓线。2017年8月,该系统在黄海海域进行了实验测量。在准单次散射模型中引入原位测量的光学参数,实现了理想激光雷达回波信号的模拟,并将该理想信号与系统响应函数卷积后精确复现了实验的激光雷达信号。采用Fernald后向迭代积分法(简称Fernald法),比较了不同水体悬浮物激光雷达比下反演的激光雷达衰减系数α与原位漫射衰减系数Kd的差别。基于停航时标定的水体悬浮物激光雷达比,采用Fernald法获得了走航时的激光雷达衰减系数。进一步地,提出一种基于米散射激光雷达数据和原位测量的后向散射数据的融合算法,模拟了高光谱分辨率激光雷达(HSRL)反演α的过程,并将其与Fernald法进行了比较。实验结果表明,自研的海洋激光雷达能够有效探测海水光学参数,基于合适的水体悬浮物激光雷达比的Fernald法可以有效应用于米散射激光雷达的反演,未来无需假设的HSRL在海水光学参数探测领域具有更大的优势。     

Optical classification of waters in the eastern arabian sea

The optical properties in a non-spectral mode covering Photosynthetically Active Radiation (PAR) was estimated in the Arabian Sea in the west coast of India. The attenuation coefficients, light transmittance and K/c ratio were found useful for classification of water bodies in the coastal and offshore region. High values of turbidity and Chlorophyll-a in coastal waters associated with comparatively higher values of diffusive attenuation coefficients for upwelling and downwelling irradiances. On the basis of attenuation coefficients and K/c ratio derived from upwelling and downwelling irradiances, the water bodies were classified as defincd by Jerlov (1976). The coastal waters are classified under Jerlov water types of 3 to 9, whereas those of offshore are falling under the categories Ia, Ib and II.     

利用经优化的边界条件开展黄海海州湾潮汐场模拟

受海底地形、开边界驱动水位及底摩擦系数等边界条件的共同影响,当前中国沿岸和近海潮汐场模拟的精度仍显不足。利用精度和分辨率较海图高一级别的水深数据、包含长周期天文气象分潮Sa的由12个主分潮组成的开边界驱动水位及顾及水深空间变化的底摩擦系数等经优化的边界条件,运行二维潮汐数值模式2D-MIKE21,开展黄海海州湾潮汐场模拟。结果表明,天文潮模拟值与海州湾周边6个验潮站1年潮汐表相比,12个主分潮综合预报误差为5.52 cm;与中国海域现有潮汐模型CST1中24个随机点位相比,12个主分潮综合预报误差为7.10 cm。天文潮模拟值和CST1预报值二者与海州湾周边2个验潮站近1个月实测值相比,前者中误差要小于后者。这为在沿岸及近海开展面向海洋测绘应用的潮汐场模拟提供了新思路,同时也表明通过数值模拟的方式构建天文气象分潮Sa是可行的。     

利用卫星测高技术确定浙江海域大地水准面

利用多颗卫星的测高数据,经共线平均及交叉点平差,建立浙江深海海域2.5′×2.5′格网分辨率的平均海面高模型,在扣除海面地形影响后得到海域的大地水准面起伏,并与EGM2008所得计算结果进行对比;利用移去-恢复技术及SVR方法,联合验潮站GPS/水准数据与EGM2008大地水准面模型,计算浙江近岸海域大地水准面起伏;最终建立浙江海域2.5′×2.5′格网分辨率的大地水准面模型。     

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.     

中国区域COSMIC数据掩星反射信号特征分析

掩星信号在传播过程中能够在地球表面发生反射,其反射信号中的低层大气信息在改进天气预报精准度和气候监测等方面存在很大的应用价值.基于COSMIC(constellation observing system for meteorology,ionosphere and climate)掩星廓线资料,提取了 2011-20...     

A three-band semi-analytical model for deriving total suspended sediment concentration from HJ-1A/CCD data in turbid coastal waters

The accurate assessment of total suspended sediment (TSM) concentration in coastal waters by means of remote sensing is quite challenging, due to the optical complexity and significant variability of these waters. In this study, three-band semi-analytical TSM retrieval (TSTM) model with HJ-1A/CCD spectral bands was developed for the retrieval of TSM concentration from turbid coastal waters. This model was calibrated and validated by means of one calibration dataset and three independent validation datasets obtained from three different turbid waters. It was found that the TSTM model may be used to retrieve accurate TSM concentration data from highly turbid waters without the spectral slope of the model requiring further optimization. Finally, the TSM concentration data were quantified from the HJ-1A/CCD images after atmospheric correction using the dark-object subtraction technique. Upon comparing the model-derived and field-measured TSM concentration data, it was observed that the TSTM model produced <29% uncertainty in deriving TSM concentration from the HJ-1A/CCD data. These findings imply that the TSTM model may be used for the quantitative monitoring of TSM concentration in coastal waters, provided that the atmospheric correction scheme for the HJ-1A/CCD imagery is available.     

An improved atmospheric correction algorithm for applying MERIS data to very turbid inland waters

Atmospheric correction (AC) is a necessary process when quantitatively monitoring water quality parameters from satellite data. However, it is still a major challenge to carry out AC for turbid coastal and inland waters. In this study, we propose an improved AC algorithm named N-GWI (new standard Gordon and Wang’s algorithms with an iterative process and a bio-optical model) for applying MERIS data to very turbid inland waters (i.e., waters with a water-leaving reflectance at 864.8 nm between 0.001 and 0.01). The N-GWI algorithm incorporates three improvements to avoid certain invalid assumptions that limit the applicability of the existing algorithms in very turbid inland waters. First, the N-GWI uses a fixed aerosol type (coastal aerosol) but permits aerosol concentration to vary at each pixel; this improvement omits a complicated requirement for aerosol model selection based only on satellite data. Second, it shifts the reference band from 670 nm to 754 nm to validate the assumption that the total absorption coefficient at the reference band can be replaced by that of pure water, and thus can avoid the uncorrected estimation of the total absorption coefficient at the reference band in very turbid waters. Third, the N-GWI generates a semi-analytical relationship instead of an empirical one for estimation of the spectral slope of particle backscattering. Our analysis showed that the N-GWI improved the accuracy of atmospheric correction in two very turbid Asian lakes (Lake Kasumigaura, Japan and Lake Dianchi, China), with a normalized mean absolute error (NMAE) of less than 22% for wavelengths longer than 620 nm. However, the N-GWI exhibited poor performance in moderately turbid waters (the NMAE values were larger than 83.6% in the four American coastal waters). The applicability of the N-GWI, which includes both advantages and limitations, was discussed.     

Medium resolution imaging spectrometer data for monitoring tropical coastal waters: a case study of Berau estuary,East Kalimantan,Indonesia

This article investigates the performance of MERIS reduced resolution data to monitor water quality parameters in the Berau estuary waters, Indonesia. Total suspended matter (TSM), Chlorophyll-a (Chl-a) concentration and diffuse attenuation coefficient (K_d ) were derived from MERIS data using three different algorithms for coastal waters: standard global processor (MERIS L2), C2R and FUB. The outcomes were compared to in situ measurements collected in 2007. MERIS data processed with C2R gave the best retrieval of Chl-a, while MERIS L2 performed the best for TSM retrieval, but large deviations from in situ data were observed, pointing at inversion problems over these tropical waters for all standard processors. Nevertheless, MERIS can be of use for monitoring equatorial coastal waters like the Berau estuary and reef system. Applying a K_d (490) local algorithm to the MERIS RR data over the study area showed a sufficient good correlation to the in situ measurements (R ² = 0.77).     

Geomorphic characterization of seafloor using Digital Elevation Model derivatives – a case study around Bombay High,Western Indian offshore

The present study demonstrates the use of gridded bathymetry in the form of a Digital Elevation Model (DEM) in a geographic information system (GIS) in geomorphic characterization of the seafloor in the Western Indian offshore around Bombay High region and presents the salient findings. The variography of bathymetry and its derivatives and their spatial correlation provides a technique to measure the presence of seafloor features and provides an insight into the processes involved. The current study utilizes tools available within a GIS for processing of a DEM and its derivatives involving spatial techniques like spatial correlation and variography studies for geomorphic characterization. A broad regional analysis for the study area comprising the near shore coast to the deep waters is discussed, followed up by a detailed study limiting to the coastal region around Bombay High.     

Detection and monitoring of offshore oil seeps using ERS/ENVISAT SAR/ASAR data and seep-seismic studies in Krishna–Godavari offshore basin,India

An attempt has been made to use synthetic aperture radar (SAR) data for detection and monitoring of offshore oil seeps in the eastern offshore areas of the Krishna–Godavari Basin, which has been supplemented and correlated with collateral free-air gravity and seismic data. Images of the study area obtained from ENVISAT ASAR image mode were processed and analysed in detail. A number of natural oil seepages were identified and distinguished from pollution and biogenic slicks. These were subsequently studied using different parameters to assign various degrees of confidence. The repetitiveness of the identified seepages was studied and a total of five areas of seep repetitions had been recognized in the study area. The seeps that are repeated in images of different dates are more likely to be of natural origin than others. Simulation and modelling of a particular oil slick arising has been attempted over the Krishna–Godavari offshore using MIKE 21 software.     

Removing attitude-related variations in the line-of-sight for kinematic GPS positioning

We are presenting a method for removing attitude-related variations (ATTRVs) in dynamic 1 Hz GPS positioning. The ATTRVs are separated into vertical and horizontal components. These result from the translational and rotational motions of the vehicle, which is a marine research vessel in our case. We have developed new observation equations that use corrected pseudoranges and carrier phases to account for ATTRVs. In the present contribution, we are only focusing on the vertical signals. These modeled ATTRVs are included as corrections in the line-of-sight (LoS) to each GPS satellite in the RINEX data sets using a new software called RNXATTCOR. Precise IGS sp3-orbits are used as inputs together with precise lever arm coordinates of the onboard GPS antennas, observations from the marine inertial navigation system and a priori 3D position of the vessel. The corrected RINEX data sets are then processed using kinematic processing or sequential processing in Precise Point Positioning (PPP) mode. The reduction of the standard deviation from a running mean in the final processed GPS time series is about 95%. The current method is being proposed for marine geodesy science applications such as along-track calibration/validation of altimetry products, and also for applications related to offshore kinematic high precision GPS positioning such as drilling, offshore platforms stability, marine pipeline positioning, earthquake monitoring and tsunami detection.     

Comparison of ocean color chlorophyll algorithms for IRS-P4 OCM sensor usingin-situ data

In-situ chlorophyll concentration data and remote sensing reflectance (R_rs) measurements collected in six different ship campaigns in the Arabian Sea were used to evaluate the accuracy, precision, and suitability of different ocean color chlorophyll algorithms for the Arabian Sea. The bio-optical data sets represent the typical range of biooptical conditions expected in this region and are composed of 47 stations encompassing chlorophyll concentration, between 0.072 and 5.90 mg m^-3, with 43 observations in case I water and 4 observations in case II water. Six empirical chlorophyll algorithms [i.e. Aiken-C, POLDER-C, OCTS-C, Morel-3, Ocean Chlorophyll-2 (OC2) and Ocean Chlorophyll-4 (OC4)] were selected for analysis on the Arabian Sea data set. Numerous statistical and graphical criterions were used to evaluate the performance of these algorithms. Among these six chlorophyll algorithms two chlorophyll algorithms (i.e. OC2 and OC4) performed well in the case I waters of the Arabian Sea. The OC2 algorithm, a modified cubic polynomial function which uses ratio of R_rs490 nm and R_rs555 nm (where, R_rs is remote sensing reflectance), performed well with r²=0.85; rms =0.15. The OC4 algorithm, a four-band (443, 490, 510, 555 nm), maximum band ratio formulation was found best on the basis of statistical analysis results with r²=0.85 and rms=0.14. Both OC2 and OC4 algorithms failed to estimate chlorophyll inTrichodesmium dominated waters. The OC2 algorithm was preferred over OC4 algorithm for routine processing of the OCM data to generate chlorophyll-a images, as it uses a band ratio of 490/555 nm and atmospheric correction is more accurate in 490 nm compared to 443 nm band, which is used by OC4 algorithm.     

Validations of suspended sediment concentration (ssc) derived using ocean colour monitor (ocm) data off Chennai coast, India

Indian Remote Sensing Satellite (IRS) — P4 Ocean Colour Monitor (OCM) data were used to estimate Suspended Sediment Concentration (SSC) in the coastal waters off Chennai and to study the distribution along the coast. Surface water samples were collected during May and October 2000 synchronized with satellite overpass, and quantitative estimates of Suspended Sediment Concentration (SSC) were done. OCM — Data Analysis System (DAS) software developed by the Space Applications Centre, Ahmedabad was used for OCM data processing and analysis. The field data and OCM derived SSC showed a correlation of r = 0.85 and r = 0.95 for the months of May and October respectively.     

Comparison of SARAL and Jason-1/2 altimetry-derived geoids for geophysical exploration over the Indian offshore

Satellite with ARgos and ALtika (SARAL) altimeter includes the ALTIKA payload, a 35.75 GHz Ka band radar altimeter. High pulse repetition frequency of SARAL (4 KHz) satellite provides better along-track information. Jason-1/2 data have been extensively utilized as a follow-up of TOPEX/Poseidon altimeter data for its accurate measurements of the sea surface heights, particularly for geodetic mission of Jason-1. In this study, we have compared SARAL and Jason-1/2 altimetry-derived classical and residual geoids over the Indian offshore using Rapp’s, EGM96 and EGM08 gravity model coefficients, which are of interest for better understanding of geological and structural evolution/interpretation. SARAL and Jason-1/2 data have also been used over the two prominent geological features over the Indian offshore, namely the Bombay High in the western offshore and the 85°E Ridge in the Bay of Bengal. The SARAL altimetry-derived geoids could delineate these major geological/structural features with distinct residual geoidal lows.