基于SVM模型的妫水河叶绿素a浓度的遥感反演

以北京市妫水河为研究区,基于2011年9月25日和2012年9月30日的两期叶绿素a浓度实测数据和准同步的环境一号卫星(HJ-1A)多光谱数据,分别构建一元线性和多元支持向量机模型(SVMM),通过决定系数R²和平均相对误差对模型的精度进行检验,用模型进行水体叶绿素a浓度的反演,并分析其时空分布特征。研究表明:在样本数较少的情况下,SVM具有很强的非线性映射能力,能够取得较好的预测结果,更适用于反演叶绿素a浓度。时间分布上,研究区叶绿素a浓度呈增加趋势,均值上升了6.86 μg/L;空间分布上,深水区叶绿素a浓度值低于浅水区,上游高于下游。国产HJ-1A CCD2多光谱数据以其4 d的时间分辨率,在水质动态变化监测方面具有优势。     

基于CHRIS/PROBA数据和地面实测光谱的三峡库区水体叶绿素a浓度反演研究

使用欧空局2001年发射的小卫星PROBA所获取的CHRIS数据,结合卫星过境时的准实时地面试验数据分析,提出了一种新的半经验模型用于反演三峡库区的叶绿素a.反演的最大误差为33%,最小误差8%,平均误差22%,均在预计的范围内.考虑到实验数据与卫星过境具有6-7天的时延,可基本认为反演结果与实测值符合,并反映了叶绿素a的全局分布,反演精度满足实用要求.     

An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing

Satellite remote sensing of ocean colour is the only method currently available for synoptically measuring wide-area properties of ocean ecosystems, such as phytoplankton chlorophyll biomass. Recently, a variety of bio-optical and ecological methods have been established that use satellite data to identify and differentiate between either phytoplankton functional types (PFTs) or phytoplankton size classes (PSCs). In this study, several of these techniques were evaluated against in situ observations to determine their ability to detect dominant phytoplankton size classes (micro-, nano- and picoplankton). The techniques are applied to a 10-year ocean-colour data series from the SeaWiFS satellite sensor and compared with in situ data (6504 samples) from a variety of locations in the global ocean. Results show that spectral-response, ecological and abundance-based approaches can all perform with similar accuracy. Detection of microplankton and picoplankton were generally better than detection of nanoplankton. Abundance-based approaches were shown to provide better spatial retrieval of PSCs. Individual model performance varied according to PSC, input satellite data sources and in situ validation data types. Uncertainty in the comparison procedure and data sources was considered. Improved availability of in situ observations would aid ongoing research in this field.     

EOS/MODIS 遥感资料探测海洋赤潮信息方法

近几年来, 我国沿海赤潮的发生越来越频繁, 已经成为一种常见海洋灾害。它的发生给沿海经济、居民生活和生态系统造成了很大影响。通过分析赤潮水体及其周边水体的光谱特性, 以及赤潮发生期间海水叶绿素a 浓度的变化特点, 提出了利用EOS/ MODIS 通道4 与通道3 的反射率比和通道11 与通道9 的离水辐射率比再结合相关的悬浮泥沙信息提取海水中赤潮信息的方法。利用此方法, 对2002 年6 月15 日和2004 年5 月31 日发生在我国渤海的赤潮进行了信息提取。结果表明此方法可以有效地提取海水中的赤潮信息。     

Seasonal changes of arsenic speciation in lake waters in relation to eutrophication

In this study, the influence of eutrophication on arsenic speciation in lake waters was investigated. Surface water samples (n = 1-10) were collected from 18 lakes in Japan during July 2007 and February 2008. The lakes were classified into mesotrophic (7 lakes) and eutrophic (11 lakes) based on the total phosphate (T-P) and chlorophyll-a (Chl-a) concentrations in water column. Inorganic, methylated and ultraviolet-labile fractions of arsenic species were determined by combining hydride generation atomic absorption spectrometry with ultraviolet irradiation. Organoarsenicals (mainly methylated and ultraviolet-labile fractions) comprised 30-60% of the total arsenic in most lakes during summer. On the other hand, inorganic arsenic species (As(III + V)) dominates (about 60-85%) during winter. The occurrence of ultraviolet-labile fractions of arsenic was higher in eutrophic lakes than those in mesotrophic lakes in both seasons. The concentration of dimethyl arsenic (DMAA) was high in eutrophic lakes during winter; and in mesotrophic lakes during summer. The results suggest that the conversion of As(III + V) to more complicated organoarsenicals occurred frequently in eutrophic lakes compared to that in mesotrophic lakes, which is thought to be the influence of biological activity in the water column. The distribution of arsenic species were well correlated with phosphate concentrations than those of Chl-a. This might be due to the competitive uptake of As(V) and phosphate by phytoplankton. The organoarsenicals (OrgAs)/As(V) ratio was higher at low phosphate concentration indicating that conversion of As(V) to OrgAs species was more active in phosphate-exhausted lakes with high phytoplankton density.     

A wavelet-based autoregressive fuzzy model for forecasting algal blooms

This paper proposes fuzzy models for forecasting the complex behavior of algal blooms. The models are developed through the integration of autoregressive models, the Takagi-Sugeno fuzzy model, and discrete wavelet transform algorithms. The premise parts of the proposed models are determined using the subtractive clustering technique and the consequent parts are optimized using weighted least squares. To train and validate the proposed fuzzy models, a large number of data sets were collected from Daecheong reservoir in Geum River in the Republic of Korea. The data include both water quality and hydrological variables. Total nitrogen, total phosphorous, dissolved oxygen, chemical oxygen demand, biochemical oxygen demand, pH, air temperature, water temperature and outflow water were evaluated as input signals while chlorophyll-a was used as an output. It is demonstrated from the simulation that the proposed fuzzy models are effective in forecasting algal blooms.     

巢湖叶绿素a与环境因子耦合效应的多元分析

针对巢湖西半湖富营养化情况,利用实测资料,通过相关分析和多元逐步回归统计,分析环境多元耦合效应与水体叶绿素a质量浓度之间的关系,找出显著环境因子,建立多元逐步回归方程,预测叶绿素a质量浓度变化.结果表明,巢湖西半湖叶绿素a质量浓度夏季高冬季低,其变化受多个环境因子共同影响,相关性较显著的为气温、水位、CODMn等.在各...     

新庙泡叶绿素a浓度高光谱定量模型研究

利用吉林省新庙泡的高光谱实测数据和水质采样分析数据,尝试通过单波段、波段比值、一阶微分和峰谷间距法建立叶绿素a反演模型。结果表明:单波段光谱反射率与叶绿素a浓度的相关性较差,不宜用于该区域的叶绿素a浓度估算;680 nm和700 nm波段反射率之比、700 nm处光谱一阶微分值和两波段峰谷间距反演模型都具有较高的决定系数,分别为0.783 4、0.792 7、0.796 9,验证模型的决定系数为0.651 3、0.431 7、0.756 4,均方根误差分别为8.69μg·L-1、14.50μg·L-1、10.04μg·L-1,显著水平P<0.01。这3种方法皆可以用于新庙泡叶绿素a浓度的定量遥感,其中又以峰谷间距法为最优。     

A spectral space partition guided ensemble method for retrieving chlorophyll-a concentration in inland waters from Sentinel-2A satellite imagery

This research proposes an ensemble method for synergistically combining multiple empirical algorithms to better estimate chlorophyll-a (Chl-a) concentration. In previous studies, different empirical algorithms have been employed separately and a single algorithm was often identified as the most suitable predictor for Chl-a retrieval. Our ensemble method combines different individual algorithms to form an ensemble predictor that exploits advantages of each individual algorithm to maximize the overall estimation accuracy. We evaluated two ensemble predictors: the optimally weighted ensemble predictor and the spectral space partition guided ensemble predictor. The ensemble method has been successfully applied to a Sentinel-2A multispectral image acquired over Harsha Lake, Ohio in 2016. Based on in situ water reference data and satellite imagery, we constructed two ensemble predictors that consist of three individual empirical algorithms/estimators, including 2BDA (two-band algorithm), 3BDA (three-band algorithm), and NDCI (Normalized Difference Chlorophyll Index). For the optimally weighted ensemble predictor, the weights for individual algorithms are computed by solving an overdetermined linear system with the pseudoinverse technique. For the spectral space partition guided ensemble predictor, the rules for partitioning spectral space into spectral regions were established as a decision-tree using the CART method. The optimal Chl-a estimate for a pixel is obtained by selectively using the empirical algorithm in the ensemble that has the highest expected accuracy in the spectral region where the pixel is located. Our assessments suggest that the spectral space partition guided ensemble method performs significantly better than three individual empirical algorithms and also better than the optimally weighted ensemble method.     

围隔导流对太湖蓬坑湾藻类富集效能的影响

针对围隔可改变水体流场、影响藻类漂移聚集,通过改变围隔布设角度和长度,探究不同围隔导流方案下藻类的富集效果。选取梅梁湾内的打捞点蓬坑湾作为研究对象,在建立太湖水量水质模型基础上,进一步建立太湖蓬坑湾套网模型,根据角度、长度两个因素,模拟6种布设方案下藻类富集效果,分析得到最佳角度、长度组合布设方案,并进一步考虑蓬坑湾地形和经济效益,提出适宜于蓬坑湾地形的优化方案。结果表明:围隔布设角度与水流方向呈120°时,湾内富集效果最佳;围隔布设长度越长,蓝藻收集区域越大,湾内富集效果越好;综合考虑地形特点和经济效益,最终确定围隔布设最佳方案为在上下湾口处分别布设一段围隔,布设角度与水流方向呈120°,上下湾口处围隔布设长度分别为100、30 m。研究成果对于改善湖泊水环境具有较好的应用前景。