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1.
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.  相似文献   

2.
In this study, a MDC3A algorithm (Multi-Data Crossing Algorithm for Accuracy Accessing) was developed for accessing the accuracy of chl-a (chlorophyll-a) retrieval model in case of no sufficient available in situ measurements. Three simple estimation algorithms of chl-a concentration, i.e., two-band algorithm, three-band algorithm and four-band algorithm, were used as input dataset of MDC3A algorithm to illuminate its performance. These three simple algorithms were calibrated and validated by calibration and validation dataset collected on October 27–28, 2003. According to model calibration and validation results, it was found that the four-band algorithm (R 2?=?0.8676) had a superior performance to the two-band (R 2?=?0.5061) and three-band (R 2?=?0.5142) algorithm. The uncertainties in modeling prediction of these three simple algorithms were underestimated as 0.07 %, 0.04 % and 8.07 % for calibration dataset and 8.38 %, 9.33 % and 9.37 % for validation dataset by MDC3A algorithm through comparison with in situ measurements. Because the MDC3A algorithm was able to detect the random errors from measured values, but had an inadequate ability to detect systematical errors and gross errors from measured values. The uncertainty estimated by MDC3A algorithm was usually lower than that estimated by in situ measurements.  相似文献   

3.
The complex composition and distribution of colour producing agents (CPAs) in turbid aquatic environments such as the Western Basin of Lake Erie (WBLE) presents a challenge to the application of remote sensing data for differentiating among in-water constituents and estimating their concentrations independently. In this study, multivariate procedures are applied to lab-based spectrophotometer data to estimate the concentration of chlorophyll-a and suspended matters in the WBLE. Principal Component Analysis of first-derivative transformed hyper-spectral data from the spectrophotometer extracted three significant spectral components for each cruise, explaining up to 88% of the spectral variability. Spectral matching using reference spectra indicated that two of the extracted patterns represent signatures of in-water constituents that govern the optical properties of the WBLE, namely, cyanobacteria and diatoms associated with green algae. The spectrophotometer data clearly revealed known spectral features associated with phytoplankton, such as the absorption minima near 550 and 700 nm, which can be attributed to the minimum of absorption and fluorescence of chlorophyll-a, respectively. The method also extracted the absorption peaks due to chlorophyll-a, near 670 nm, and due to phycocyanin, near 620 nm. Principal component regression of chlorophyll-a on the PC scores indicated that 63.4% of variation of chlorophyll-a in the WBLE can be explained by two components. Factors 2 and 3 explain 60% of the joint spatiotemporal variability of suspended matters in the WBLE. The results illustrate the potential of multivariate technique applied to remote sensing data in isolating the patterns that represent constituents in turbid Case 2 waters.  相似文献   

4.
Accurate assessment of phytoplankton chlorophyll-a (Chla) concentration in turbid waters by means of remote sensing was challenging due to the optical complexity of turbid waters. Recently, a conceptual model containing reflectance in three spectral bands in the red and near-infrared range of the spectrum was suggested for retrieving Chla concentrations in turbid productive waters. The objective of this paper was to evaluate the performance of this three-band model to estimate Chla concentration in the Pearl River Estuary (PRE), China. Reflectance spectra of surface water and water samples were collected concurrently. The samples contained variable Chla (4.80-92.60 mg/m3) and total suspended solids (0.4-55.2 mg/L dry wt). Colored dissolved organic matter (CDOM) absorption at 400 nm was 0.40-1.41 m−1; turbidity ranged from 4 to 25 NTU (Nephelometric Turbidity Units). The three-band model was spectrally calibrated by iterative and least-square linear regression methods to select the optimal spectral bands for the most accurate Chla estimation. Strong linear relationships (R2=0.81, RMSE=1.4 mg/m3, N=32) were established between measured Chla and the levels obtained from the calibrated three-band model [R−1(684)-R−1(690)]×R(718), where R(λ) was the reflectance at wavelength λ. The calibrated three-band model was independently validated (R2=0.9521, RMSE=6.44 mg/m3, N=16) and applied to retrieve Chla concentrations from the calibrated EO-1 Hyperion reflectance data in the PRE on December 21, 2006. The EO-1 Hyperion-derived Chla concentrations were further validated using synchronous in situ data collected on the same day (R2=0.64, RMSE=2 mg/m3, N=9). The spatial tendency of Chla distribution mapping by Hyperion showed gradually increased concentrations of Chla farther from the river mouths (although decreasing from east to west), which were disturbed by the combination of river outlets and tidal current in Lingding Bay of the PRE. This observation conformed to previous observations and studies, and could reasonably be explained by geographical changes. Also, results indicated that the slope of the three-band regression line decreased as the Chla concentration increased, resulting in the first sensitive band of the three-band model to move towards short wavelengths. These findings validated the rationale behind the conceptual model and demonstrated the robustness of this algorithm for Chla retrieval from in situ data and the Hyperion satellite sensor in turbid estuarine waters of the PRE, China.  相似文献   

5.
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.  相似文献   

6.
Particulate organic carbon (POC) plays an important role in the carbon cycle in water due to its biological pump process. In the open ocean, algorithms can accurately estimate the surface POC concentration. However, no suitable POC-estimation algorithm based on MERIS bands is available for inland turbid eutrophic water. A total of 228 field samples were collected from Lake Taihu in different seasons between 2013 and 2015. At each site, the optical parameters and water quality were analyzed. Using in situ data, it was found that POC-estimation algorithms developed for the open ocean and coastal waters using remote sensing reflectance were not suitable for inland turbid eutrophic water. The organic suspended matter (OSM) concentration was found to be the best indicator of the POC concentration, and POC has an exponential relationship with the OSM concentration. Through an analysis of the POC concentration and optical parameters, it was found that the absorption peak of total suspended matter (TSM) at 665 nm was the optimum parameter to estimate POC. As a result, MERIS band 7, MERIS band 10 and MERIS band 12 were used to derive the absorption coefficient of TSM at 665 nm, and then, a semi-analytical algorithm was used to estimate the POC concentration for inland turbid eutrophic water. An accuracy assessment showed that the developed semi-analytical algorithm could be successfully applied with a MAPE of 31.82% and RMSE of 2.68 mg/L. The developed algorithm was successfully applied to a MERIS image, and two full-resolution MERIS images, acquired on August 13, 2010, and December 7, 2010, were used to map the POC spatial distribution in Lake Taihu in summer and winter.  相似文献   

7.
To understand the scale effects on chlorophyll-a (chl-a) concentration retrieved from satellite images, the two-band algorithm (TA) and three-band algorithm (TBA) were constructed for estimating chl-a from satellite images. Two synchronous images of Advanced Wide-Field Sensor (AWiFS) and Linear Imaging Self-Scanner (LISS) of Indian remote sensing satellite were used to assess and validate the scale errors of these two algorithms. They were collected at local time 02:55:46:471 and 02:58:25:053 on October 8, 2005 in Yellow River Estuary, and their spatial resolutions are 24 m and 56 m, respectively. From the results of this study, it was found that: (1) the relative scale error (RSE) of TA and TBA, caused by scale changing from LISS to AWiFS, varied from 0% to 100%; (2) the RSE was correlated with the spatial non-homogeneous degree of chl-a distribution; and (3) using TBA to estimate chl-a concentration in Yellow River Estuary decreased 2.55% of model uncertainty, but increased 4.97% of scale errors, in comparison with TA. Additionally, the study indicated that the performance of algorithms for chl-a estimation was greatly affected by the scale error. If the scale effects of chl-a retrieval algorithm were taken into consideration, TA had a superior performance to the TBA in this study.  相似文献   

8.
Ocean color analysis and aerosol retrieval in coastal regions are made difficult by water turbidity. An algorithm has been proposed which uses the data at a blue wavelength instead of those in near-infrared wavelengths for the aerosol retrieval. The quasi-homogeneous effects are assumed for the correction of water leaving radiance with soil particles at 0.412 μm. The proposed algorithm is examined using SeaWiFS data on December 24, 2000 around India. Over the coastal waters, extremely large values of optical thickness are extracted from the operational SeaWiFS algorithm, whereas our proposed algorithm produces a smooth transition in values of optical thickness from the turbid waters to the surrounding regions.  相似文献   

9.
内陆水体叶绿素a浓度反演的区域化三波段模型研究   总被引：1，自引：0，他引：1  
李方  徐京萍  马荣华  段洪涛  张柏 《遥感学报》2011,15(6):1163-1179
以太湖和石头口门水库为例,建立了一种可直接计算水体叶绿素a浓度的区域化三波段模型。该模型通过对研究水体的光学特性分析,明确三波段组合与叶绿素a浓度间的函数关系参数,不仅可较好指示研究水体叶绿素a浓度水平,而且大大减小了回归算法所带来的模型不确定性。利用高精度、长时间序列的水体光学特性观测数据,建立针对不同研究水体的区域化三波段模型可为实现内陆水体叶绿素a浓度遥感监测业务化运行提供方法借鉴。  相似文献   

10.
Accurately estimating phytoplankton Chlorophyll-a(Chla) concentration from remotely sensed data is particularly challenging in turbid, productive waters. In this study, a weighted Chla concentration algorithm (WCA) are constructed to smooth the performance of three-bands semi-analytical algorithm(TSA) and four-bands semi-analytical algorithm(FSA). The performance of WCA, TSA and FSA algorithms are calibrated and validated by three independently datasets collected from Chesapeake Bay, USA, Yellow River Estuary, China, and Taihu Lake, China. Results of this study indicated that: (1) The accuracy and stability of TSA, FSA and WCA in Chesapeake Bay have a superior performance than it in Taihu Lake and Yellow River Estuary; (2) In Taihu Lake and Yellow River Estuary, the TSA and FSA algorithms are not stable for estimating Chla concentration, especially in Taihu Lake, the accuracy and stability of TSA, FSA and WCA algorithms are quite bad; (3) The WCA can greatly improve the accuracy and stability of TSA and FSA algorithms, but it is greatly depended on the performance of TSA and FSA algorithms; and (4) Although the TSA, FSA and WCA algorithms are semi-analytical algorithm, however, the optimal bands, accuracy and stability of these algorithms are very timely and located dependence.  相似文献   

11.
In this study chlorophyll measurements were made during March 2012 in the estuarine waters of Off Kakinada and Yanam coast, Bay of Bengal onboard a coastal vessel. In-situ water samples and optical data was collected at 21 stations (surface to 150 m depth) using Underwater radiometer (Hyperpro-II). In-vivo chlorophyll profiles were collected using wet labs fluorometer integrated with underwater Hyperspectral radiometer. Chlorophyll-a concentrations were estimated using HPLC by collecting the water samples at each sampling location. And also chlorophyll-a concentrations were retrieved from the OCM-2 data of OCEANSAT-2 satellite, processed using SeaDAS v.6.2 with the available global ocean colour algorithms namely, OC2 and OC4V4. A total of 33 samples used covering all the stations for chlorophyll-a estimation, and surface water samples of all the stations only being used for direct comparison among chlorophyll concentrations of HPLC, in-situ (fluorometrically integrated to Hyperpro-II) and retrieved from OCM-2. A good correlation found between the Fluorometer derived and HPLC measured chlorophyll-a concentration with an R2 value of 0.78. The relation between Chlorophyll-a concentration measured from HPLC and retrieved from OCM-2 (OC2 and OC4V4 algorithms) using SeaDASv.6.2 for 10 samples has been compared for validation and obtained an R2 value of 0.6. Also comparisons done with the in-situ measured (fluorometer) Chlorophyll-a concentration with OCM-2 chlorophyll data (OC4-V4 and OC2 algorithms) and validation with 10 concurrent in-situ surface measurements showed a significant overestimation by OCM-2 at low chlorophyll-a concentrations and underestimation at high chlorophyll-a concentrations.  相似文献   

12.
以黄海及东海海域为对象,研究用MOD IS数据提取我国海域悬浮泥沙时空分布的定量遥感方法,建立了基于MOD IS数据的悬浮泥沙定量遥感实用模式。研究表明,用250 m和1 000 m分辨率的MOD IS数据进行悬浮泥沙浓度的定量遥感,可以达到实际应用的精度要求。这说明,MOD IS数据是研究近岸水体中悬浮物输运变化规律的一种经济实用数据源。  相似文献   

13.
Dissolved Organic Carbon (DOC) is an important component in the global carbon cycle. It also plays an important role in influencing the coastal ocean biogeochemical (BGC) cycles and light environment. Studies focussing on DOC dynamics in coastal waters are data constrained due to the high costs associated with in situ water sampling campaigns. Satellite optical remote sensing has the potential to provide continuous, cost-effective DOC estimates. In this study we used a bio-optics dataset collected in turbid coastal waters of Moreton Bay (MB), Australia, during 2011 to develop a remote sensing algorithm to estimate DOC. This dataset includes data from flood and non-flood conditions. In MB, DOC concentration varied over a wide range (20–520 μM C) and had a good correlation (R2 = 0.78) with absorption due to coloured dissolved organic matter (CDOM) and remote sensing reflectance. Using this data set we developed an empirical algorithm to derive DOC concentrations from the ratio of Rrs(412)/Rrs(488) and tested it with independent datasets. In this study, we demonstrate the ability to estimate DOC using remotely sensed optical observations in turbid coastal waters.  相似文献   

14.
Remote sensing has been extensively used for water delineation and has played an important role in water quality evaluation and environmental management strategies. Suspended sediments are important determinants of water quality in coastal zones. Remote sensing enables the effective monitoring of total suspended sediments (TSS) and the detection of areas with critical water quality issues. This study aims to develop and implement regression models for estimating and mapping TSS concentrations from Advanced Land Observation Satellite (ALOS) images over the coastal waters of Langkawi Island, Malaysia. The algorithm was developed based on the water reflectance model, which is a function of the inherent optical properties of water. Such properties can then be linked to TSS concentration. In this study, an ALOS Advanced Visible and Near Infrared Radiometer type 2 device was used as the imaging sensor system. Concurrent complementary in-situ water samples were collected within the area coverage of the sensor, and digital numbers (DN) for each band corresponding to the sea-truth locations were determined. The extracted DN values were converted into reflectance values and then regressed with their respective sea-truth data. An algorithm was proposed to obtain the regression coefficient. This algorithm can estimate TSS concentrations with a high correlation coefficient (R2?=?0.96) and low root-mean-square error (RMSE?=?1.98 mg/l). Finally, a map of the TSS concentration was generated by using the proposed algorithm. This study found that TSS mapping can be conducted by using ALOS data over the coastal waters of Langkawi Island, Malaysia.  相似文献   

15.
Phytoplankton blooms, particularly in the Southern Ocean, can have significant impact on global biogeochemistry cycling. To investigate the accuracy of chlorophyll-a distribution, and to better understand the spatial and temporal dynamics of phytoplankton biomass, we examine chlorophyll-a estimates (October–March from 2002 to 2012) derived from Moderate Resolution Imaging Spectrometer (MODIS) data following the ocean chlorophyll-a 3 model (OC3M) algorithm. Noticeable seasonality occurs in the temporal distribution of chlorophyll-a concentrations, which shows the highest value in December and January and an increasing tendency during the 2002–2012 period. The spatial distribution of chlorophyll-a varies greatly with latitude, as higher latitudes experience more phytoplankton blooms (chlorophyll-a concentration larger than 1 mg/m3) and marginal seas (Ross Sea and Amundsen Sea) show different bloom anomalies caused by two dominant algae species. Areas at higher latitudes and shallow water (<500 m) experience the shorter ice-free periods with greater seasonality. A noticeable bathymetry gradient exists at 2500-m isobaths, while water at the 500–2500-m depth experiences quite long ice-free periods with a stable water environment. Blooms generally occur near topographic features where currents have strong interactions when the water depth is more than 2500 m. Based on these findings, we can classify the Southern Ocean into two bloom subregions, 0–500 m as an enhanced bloom zone (EBZ), and 500–2500 m as a moderate bloom zone (MBZ). The EBZ has a quite high-bloom probability of about 30%, while the MBZ has only 10%.  相似文献   

16.
In this paper we report chlorophyll measurements made during an ocean colour validation cruise in April 2011 of the research vessel, Sagar Paschimi in the coastal waters of Northern Bay of Bengal. The chlorophyll-a concentration in these waters range from 0.2 to 4.0 mg/m3. Chlorophyll-a concentration from OCM-2 was estimated using the global ocean colour algorithms namely, OC2, OC3, OC4 and Chl-a algorithms respectively. OCM data was processed using the global SeaWiFS Data Analysis System (SeaDAS) in which all the above mentioned algorithms are embedded for estimating the chlorophyll-a concentration. A comparative study was made between and in-situ and satellite derived chlorophyll-a concentration. Although the matchups between in-situ and satellite data from OCM-2 were sparse, it indicates that direct application of the standard SeaWiFS algorithm-the OC4-V4 algorithm—in the coastal waters of the Bay of Bengal will underestimate chlorophyll-a by up to 30%. The results show a good correlation with an R value of 0.61 using OC2 algorithm. However, all the other global algorithms over estimate the chlorophyll-a concentration even in low chlorophyll concentration range. The comparison between in-situ and all the existing chlorophyll algorithms shows the efficiency of these algorithms for quantification of chlorophyll in coastal waters and hence the need to develop regional algorithms and fluorescence based algorithms for better quantification.  相似文献   

17.
A simple method to determine the slope of spectral variations of combined absorption of the colored dissolved organic matter and detritus (CDM) is presented. This method uses the slope of total absorption spectrum excluding contribution of waters in lieu of slope for the CDM. The errors in slopes using the new method decreased with increase in contributions of CDM to the total absorption. The relative errors were less than 10% when CDM contributions were above 60% and even at very low contributions of CDM of 25%, errors in the slopes were less than 40%. For estuarine and coastal waters rich in CDM, the errors in the slopes for CDM were less than 10% using this simple method. Absorption of CDM derived using the slope with the new method in a semi-analytical algorithm QAAV6 showed improved performance with RMSE of 0.07, 0.0119 and 0.0027 at 405, 555 and 665 nm respectively and with R2 > 0.95 at all spectral range. The method provided values of spectral absorption due to CDM with fewer errors when validated with the satellite derived data from MODIS and SeaWiFS. This method to determine the slope of CDM could be easily implemented in any model, as it was very generic in nature, simple, did not involve any mathematical model and avoids empirical methods. Since the method is also independent of any specific bands, it can be used for most ocean color satellites. Considering the performance of this new method and applicability for most water types, it was considered as a better option to derive the slope of CDM than using a constant value or deriving the slope with empirical method.  相似文献   

18.
针对我国近岸高浑浊水体区域MODIS短波红外波段大气校正产品中存在的信号饱和及条带问题,利用神经网络模型,采用准同步的HJ-1A/B卫星CCD影像及实测遥感反射率数据对MODIS/Terra水色遥感大气校正产品进行了质量改进。改进后结果与MODIS/Terra遥感反射率产品相比,平均相对误差为13.3%,信号饱和区域修复结果与实测数据各波段平均相对误差为28.2%。结果表明,该方法在保证结果精度的情况下,能有效地修复MODIS/Terra水色波段因为信号饱和而产生的数据空白区域,同时也能较好地解决MODIS/Terra大气校正产品中的条带问题。  相似文献   

19.
Total suspended sediment (TSS) data concentrations are retrieved from two sets of satellite ocean color data (the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua and the Korean Geostationary Ocean Color Imager (GOCI)) using an existing regional model to characterize spatial and temporal variation of TSS in the Yellow and East China Seas. MODIS-derived TSS maps show that TSS concentrations are, in general, high along the Korean and Chinese coasts including the Bohai Sea and the Yangtz River estuary, and lower in the middle of the Yellow Sea and the southeastern area of the East China Sea. The monthly average of 10-year MODIS data reveals that TSS values are highest during winter (January to February) and lowest in summer (July to August). Short-term TSS concentrations retrieved from GOCI data showed the dominant influence of semi-diurnal tidal changes on sediment dynamics through temporal (hourly) and spatial distribution in coastal zones of the Yellow sea. The results presented here demonstrate that the satellite-derived TSS products can be utilized as an application tool for future studies on long- and short-term sediment dynamics of turbid coastal waters. In particular, GOCI observations provide unique important capabilities to characterize and quantify the water properties at high temporal (hourly) and spatial (0.5 km) resolutions in the turbid coastal waters of the Yellow Sea and its vicinities.  相似文献   

20.
Soft-classification-based methods for estimating chlorophyll-a concentration (Cchla) by satellite remote sensing have shown great potential in turbid coastal and inland waters. However, one of the most important water color sensors, the MEdium Resolution Imaging Spectrometer (MERIS), has not been applied to the study of turbid or eutrophic lakes. In this study, we developed a new soft-classification-based Cchla estimation method using MERIS data for the highly turbid and eutrophic Taihu Lake. We first developed a decision tree to classify Taihu Lake into three optical water types (OWTs) using MERIS reflectance data, which were quasi-synchronous (±3 h) with in situ measured Cchla data from 91 sample stations. Secondly, we used MERIS reflectance and in situ measured Cchla data in each OWT to calibrate the optimal Cchla estimation model for each OWT. We then developed a soft-classification-based Cchla estimation method, which blends the Cchla estimation results in each OWT by a weighted average, where the weight for each MERIS spectra in each OWT is the reciprocal value of the spectral angle distance between the MERIS spectra and the centroid spectra of the OWT. Finally, the soft-classification based Cchla estimation algorithm was validated and compared with no-classification and hard-classification-based methods by the leave-one-out cross-validation (LOOCV) method. The soft-classification-based method exhibited the best performance, with a correlation coefficient (R2), average relative error (ARE), and root-mean-square error (RMSE) of 0.81, 33.8%, and 7.0 μg/L, respectively. Furthermore, the soft-classification-based method displayed smooth values at the edges of OWT boundaries, which resolved the main problem with the hard-classification-based method. The seasonal and annual variations of Cchla were computed in Taihu Lake from 2003 to 2011, and agreed with the results of previous studies, further indicating the stability of the algorithm. We therefore propose that the soft-classification-based method can be effectively used in Taihu Lake, and that it has the potential for use in other optically-similar turbid and eutrophic lakes, and using spectrally-similar satellite sensors.  相似文献   

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