基于HJ-1A CCD数据的湖泊叶绿素a浓度反演——以贵阳市百花湖为例

为及时、快速地获取百花湖叶绿素a浓度情况,形成具有可操作性的水质遥感监测技术,结合HJ-1A卫星数据与2012年4月实测的光谱数据,建立百花湖叶绿素a的遥感反演模型。结果表明:①第1波段和第2波段比值(B2/B1)与叶绿素a浓度的相关性最好,相关系数(R~2)为0.84。②利用波段比值构建的回归模型具有不错的反演效果,模型决定系数(R~2)为0.87,平均绝对误差(MAPE)为13%,均方根误差(RMSE)为4.32 mg/m~3;用12月份实测的数据对模型进行验证,效果也比较理想,说明该模型适用于百花湖冬、春季叶绿素a浓度的反演,在一定时间范围内具有一定的普适性。③百花湖湖边叶绿素a浓度高于湖心,分布趋势自北向南逐渐增加;④营养状态指数空间分布主要呈富营养化状态,富营养状态区域占全湖的85%,中营养状态区域仅占全湖的15%。叶绿素a反演及富营养化评价结果与实际分析情况相符,表明HJ-1A CCD数据可用于百花湖水质参数的遥感监测。     

长荡湖叶绿素a浓度卫星遥感反演研究

以江苏典型湖泊长荡湖为研究区,结合20个站点实测光谱数据和叶绿素a浓度数据,建立了长荡湖叶绿素a浓度卫星遥感反演模型,并对长荡湖叶绿素a浓度开展监测.结果表明遥感技术能够快速实现长荡湖叶绿素a浓度的监测,监测结果能够反映湖泊叶绿素a浓度的分布状况,是水环境监测的一种先进的技术手段.     

河口水体泥沙浓度的水面光谱统计模式分析

现场测量长江口Ⅱ类水体的反射高光谱,并同步获取水样、测量流速,在实验室中对所获水样的泥沙浓度进行测定。通过对试验数据的分析发现,水体反射光谱随泥沙浓度不同而发生变化,在黄绿光波段(560～720nm)和近红外波段(810nm)出现两个明显的反射峰。波长大于650nm光谱反射率和表层泥沙浓度的相关性较好,特别在690～900nm波段两者的相关系数大于075,对泥沙浓度变化较为敏感。基于最小二乘法,建立了单波段反射率与泥沙浓度关系以及波段反射率比值与泥沙浓度关系的回归方程。结果表明,670nm和715nm处单波段反射率的指数方程相关系数较高,而基于810/690波段反射率比值的二次多项式拟合方程对泥沙浓度的预测精度好于其它比值组合形式的模型。     

南四湖水体叶绿素a浓度实用化高光谱反演模型

根据2014年7月21-23日在南四湖实测的高光谱数据和同步水质采样分析数据分别构建了反演南四湖水体叶绿素a浓度的单波段模型、一阶微分模型、波段比值模型、三波段模型以及四波段模型,并进行验证,同时尝试用连续统去除和反连续统去除法构建叶绿素a浓度反演模型。结果表明:R*728模型、R'705模型、R*728/R*617波段比值模型、R734/R463波段比值模型、[R-1rs(671)-R-1rs(730)]·Rrs(763)三波段模型以及[R-1rs(682)-R-1rs(720)]·[R-1rs(761)-R-1rs(733)]-1四波段模型均可以较好的估测南四湖水体叶绿素a浓度,均方根误差RMSE小于7μg/L,ARE在15%以内。其中各模型中线性模型估测精度最高,更适合南四湖水体叶绿素a浓度的高光谱反演;连续统去除和反连续统去除法无法建模。     

基于GF-1/WFV的钱塘江叶绿素a和总悬浮物浓度遥感估算

为了探究高分一号(GF-1)卫星对河流水体水质参数遥感反演的效果,使用GF-1卫星数据的16 m分辨率的GF-1/WFV传感器数据和地面实测数据,基于地面实测光谱反射率数据模拟WFV波段组合,构建水体叶绿素a和总悬浮物浓度遥感模型,从而对钱塘江流域杭州段水体水质参数进行估算。研究结果表明:基于B1-B3差值的二次多项式模型可用于叶绿素a浓度估算(R²=0.83,RMSE=0.74 μg/L),基于B3波段的二次多项式模型可用于总悬浮物浓度的估算(R²=0.92,RMSE=1 mg/L);通过模型应用于准同步的GF-1/WFV数据,较好反映了低潮位钱塘江杭州段水体叶绿素a和总悬浮物浓度的空间分布,为高分一号卫星数据遥感监测钱塘江水色参数做出了有益的探索性工作。研究方法及结果对其他流域河流水色遥感研究具有参考价值。     

基于高光谱分析的长荡湖水质监测技术研究

以江苏省长荡湖为例,对15项常规水质参数进行实地采样试验,并同步测定采样点的水体高光谱信息。为研究高光谱信息在该湖泊水质反演中的适用性,对水质参数和对应光谱特征进行定量分析,筛选高光谱对水质指标的敏感波段。分别选用波段差值、波段比值和单波段建立半经验数学模型,并根据实测值验证各模型反演精度。结果表明,利用波段组合反射率建立的模型对TP、浊度、悬浮物SS、水温和透明度具有较好的拟合效果。     

悬浮泥沙反射光谱特性和泥沙量估算试验研究

通过实验室含沙水体的配比试验，对不同浓度含沙水体进行了光学特性测量，建立了不同悬沙含量遥感反演模型，结果表明：1）确立的水体光谱反射率和悬沙浓度之间的数值关系，为用卫星遥感技术探测表层悬沙浓度做了基础性的研究，取得了令人满意的效果；2）悬沙水样的敏感波段位于700nm～720nm，730～750nm和800～850nm；3）利用主成分分析方法结合多元线性回归可较为精确地估算悬沙含量，其模型反演能力明显优于敏感波段线性模型。对于浓度范围为0．1905g／L～3．6991g/L的悬沙水体，主成分回归模型反演精度更高，反演值和实测值的平均相对误差仅为5％左右；4）用实验室含沙水体配比方法进行的悬沙浓度与光谱关系的研究，其数据采集的同步性好，精度可靠。     

基于实测数据的鄱阳湖悬浮泥沙粒度遥感反演模式分析

水体悬浮泥沙粒度是重要的水质参数之一,影响着水体的遥感反射率。研究两者之间的关系对于内陆湖泊水环境遥感监测具有重要意义。基于鄱阳湖实测数据,采用相关分析方法,用不同数学模型进行鄱阳湖悬浮泥沙粒度反演研究。研究结果表明:(1)浑浊区适合采用体积百分比众数粒径建立反演模型,清水区适合采用数量百分比中值粒径建立反演模型;(2)浑浊区悬沙粒度的敏感单波段是环境卫星Ⅳ波段,在清水区悬沙粒度的敏感单波段有环境卫星Ⅱ和Ⅲ波段,而环境卫星Ⅱ,Ⅲ波段比组合是整个研究区水域的敏感波段;(3)单波段反演模型中,幂函数适用于鄱阳湖粒度遥感反演;波段比反演模型中,多项式模型适于鄱阳湖粒度遥感反演。     

基于国产卫星多光谱影像的河流水体浊度遥感联合反演研究

基于集合建模思想,在水体光谱特征分析与敏感波段选择基础上,集成多种遥感反演模型优势,构建了河流水体浊度多光谱遥感联合反演模型(Combined Model-BP,CM-BP)。选择汉江中下游典型河段为研究区,利用2012—2013年原位观测数据,以具有较高时间分辨率和空间分辨率的国产卫星数据作为多光谱遥感数据源,测试评估了CM-BP浊度遥感反演模型适用性,并与传统波段组合模型进行精度比较,基于反演结果分析了研究区浊度时空分布特征。结果表明:基于集合建模思想构建的CM-BP模型的反演精度、适应性及稳定性均高于波段组合模型;从光谱分辨率、时空分辨率等角度考虑,环境与灾害监测预报小卫星星座系统、高分一号卫星、资源三号等国产卫星多光谱遥感数据是河流水体水质反演优选数据源;国产卫星遥感数据可以满足河流水体水质高精度、实时性与大尺度等遥感反演需要,为河流水环境监测研究提供数据基础。     

基于Sentinel-2影像的横山水库叶绿素a反演算法研究

针对横山水库叶绿素a参数仅采用固定站点监测,而无本地化的遥感反演算法的现状,基于Sentinel-2遥感影像和自动站点监测数据,运用相关分析法选取最佳反演波段,以此建立经验模型、BP神经网络模型和随机森林模型3种反演方法。结果表明：不同波段组合中,B8、B5/B4、(B5-B4)/(B5+B4)与自动站点监测的叶绿素a浓度值相关系数最大;构建的随机森林模型平均绝对误差1.09、均方根误差1.335、决定系数0.94,均优于另外两种模型,更加适合基于Sentinel-2影像的横山水库叶绿素a浓度反演。     

Spectral Reflectance Measurements of a Microcystis Bloom in Upper Klamath Lake,Oregon

The objective of this study was to measure the in situ spectral reflectance of lake water that contains a bloom of Microcystis, a species of cyanobacteria. Reflectance spectra (350–2,500 nm) of lake water near a boat dock in Upper Klamath Lake, Oregon, were collected with a portable spectroradiometer on a cloud-free day with sunlight as a source of illumination between 0845 to 0915 hours, Pacific Daylight Time (PDT) on 17 August 2004, at a near-normal angle of observation. The averaged spectrum of the lake water containing the Microcystis bloom exhibits reflectance maxima from 550-590 nm and near 710 nm wavelengths and reflectance minima near 630 nm and 675 nm wavelengths. The reflectance gradually decreases from 810–1,000 nm and has very low reflectance in the 1,000–2,500 nm wavelength region. Our results show that the spectral reflectance of Microcystis at this stage of its bloom remains low for wavelengths longer than 1,000 nm in the near-infrared region of the spectrum. These spectral results have implications in selecting the spectral ratios and refining the algorithms that will be used to estimate phycocyanin content using satellite models. Microcystis is the predominant species of cyanobacteria blooms in Lake Erie, which makes these spectral data as important to the Great Lakes as it is to Upper Klamath Lake. Satellite algorithms have been published that have mapped phycocyanin, a pigment more uniquely associated with cyanobacteria than is chlorophyll a, in Lake Erie with data from LANDSAT TM bands 1, 3, 4, 5, and 7, and the reflectance spectra reported here are the first that cover the entire spectral range of all those LANDSAT TM spectral bands for a Microcystis bloom.     

基于高光谱数据的鄱阳湖湿地典型植被识别分析

利用高光谱数据对湿地植被进行分类历来是植被遥感研究的重点和难点之一。以鄱阳湖为研究区,测取了5种典型湿地植被的高光谱数据,利用光谱微分法对原始光谱数据进行处理,分析不同植被原始光谱、一阶微分和二阶微分光谱曲线图;使用欧式距离法选择差异较大的波段以鉴别不同植被;最后利用马氏距离法检验所选择波段识别不同植被的效果。结果表明:3种光谱曲线所提取的差异性较大,波段虽有所差异,但多位于近红外波段,马氏距离在这些波段上能有效对不同典型湿地植被进行识别。研究结果可为湿地植被分类识别奠定基础,同时可为湖泊湿地植被以及湖泊生态环境的保护决策提供科学依据。     

基于MODIS数据的鄱阳湖总悬浮物浓度监测分析

为了利用遥感卫星影像资料对湖泊水质进行连续、大范围的监测,以鄱阳湖为研究对象,通过对水体实测高光谱的特征分析,采用分期统计回归的方法建立总悬浮物(TSS)浓度反演模型,利用MODIS影像反演鄱阳湖TSS浓度的空间分布,并分析其时空分布特征.研究结果表明:红光和近红外波段是反演水质参数TSS的敏感波段,在同一环境下分析,...     

An analysis of MODIS-derived algal and mineral turbidity in Lake Erie

Satellite-derived estimates of chlorophyll concentrations based on colour ratio algorithms traditionally fail in turbid waters such as those found in Lake Erie, resulting in chlorophyll concentrations often orders of magnitude in error and spatial distributions mirroring that of known suspended sediment distributions. Methods are presented here that were used to simultaneously extract algal and mineral suspended particulate matter for Lake Erie from the red and near-infrared bands of NASA's MODIS-Aqua sensor. Results produced spatially and temporally distinct seasonal cycles in agreement with bio-geo-physical processes on the lake. Derived imagery was used to monitor seasonal cycles of both algal and mineral particulate matter on the lake and determine areas of persistently elevated concentrations that may highlight regions of potential water quality concern.     

基于文献计量学的中国地下水微生物研究现状分析

为了揭示我国地下水微生物研究现状与重点,为后续污染修复提供参考,利用Excel、CNKI可视化分析模块和CiteSpace软件对国内该领域397篇期刊论文和199篇硕博论文进行文献计量学分析。结果显示：中国地下水微生物研究主要围绕地下水污染开展,一方面使用多种修复技术对地下水污染环境进行生物修复,为地下水污染修复提供技术支持,另一方面利用分子生物学技术对地下水污染环境进行监测,为地下水污染修复提供理论支撑。张胜研究员、林学钰院士、刘菲教授、王焰新教授和席北斗研究员是该领域不同研究阶段的重要学者,吉林大学、中国地质大学（北京）和中国地质科学院水文地质环境地质研究所在该领域具有较强学术影响力。在生态文明建设的迫切需求下,充分发挥微生物群落在地下水污染修复中的作用潜力仍是当下研究的重点。     

Identification of processes regulating the colour and colour change in an oligotrophic,hardwater, groundwater‐fed lake,Blue Lake,Mount Gambier,South Australia

Blue Lake, located in Mount Gambier, South Australia, is the only known global example of a lake that annually changes colour in the blue end of the spectrum. A series of experiments, including Secchi depth readings, in situ spectroradiometric analysis and spectrophotometric analysis of water samples, were designed to identify the factors affecting the colour of Blue Lake and the processes that regulate these factors. Based on the results of these experiments, the processes controlling the colour and colour change in Blue Lake are described and quantified. Blue Lake colour was observed to change between AS 2700 Aqua during winter (April through to October) and Blue Bell during summer (December through to February). The colour change in Blue Lake is measurable and reflects primarily the regulation of the concentration of humic substances in the upper part of the lake by calcite precipitation. The calcite precipitation is driven by degassing of carbon dioxide from the epilimnion of the stratified lake in summer. The humic substances co‐precipitate with the calcite. Photodegradation of the humic substances may also occur.     

Deriving and Evaluating Bathymetry Maps and Stage Curves for Shallow Lakes Using Remote Sensing Data

Urmia Lake as a most vital water bodies in Iran, has been shrinking since the late twentieth century and its area has dramatically decreased. To develop and apply any plans to survive the lake, qualitative and quantitative analysis and any modeling, deriving physical information such as volume, area and their changes are very crucial. The objectives of this study were therefore, intended firstly, to study the bathymetry of Urmia Lake with a more satisfactory approach using Landsat- LDCM satellite image and in situ measurement data. The polynomial model was developed to predict the water depth in Urmia Lake area. This model was developed with the input series of reflectance values from blue, green, red and NIR bands in the Landsat- LDCM satellite imagery for Urmia Lake taken on 12 April 2013 of the sampling sites from actual depth measured were taken on the same date. Also, using a large archive of Landsat imagery (TM, ETM+ and LDCM), a counter of equivalent elevation were established for deriving the bathymetry of desiccated areas by mapping the edges of the lake and finally assembled with bathymetry derived from polynomial model. In-situ depth measurements were used to evaluate resultant derived bathymetric map. This comparison shows reasonable agreement between the Landsat-derived depths and those measured in the field with RMSE of 0.27 cm and R² = 0.91. The maximum and mean depths measured were 4.9 and 11 m respectively. The maximum depth measured was located at the upper part of the lake. As well as, developed multi-regression equation used for deriving another bathymetry map using Landsat- LDCM satellite image taken on Sep. 2015 for salt deposition monitoring. Results indicates that about 64 cm salt deposition has occurred during the last two years. Secondly, to make stage curves of lake, multi-temporal changes of water body have been derived from Landsat, MODIS and AVHRR satellite images sets since 1972. In this regard, the area of Urmia Lake at different level was estimated base on object oriented and pixel base classification using 78 satellite images. Finally, stage curve (volume- area- level relations) was derived from bathymetry map.     

Satellite remote sensing reveals impacts from dam‐associated hydrological changes on chlorophyll‐a in the world's largest desert lake

We present an approach that uses satellite products to derive models for predicting lake chlorophyll from environmental variables, and for investigating impacts of changing environmental flows. Lake Turkana, Kenya, is the world's largest desert lake, and environmental flows from the Omo River have been modified since 2015 by the Gibe III dam in Ethiopia. Using satellite remote sensing, we have evaluated the influence of these altered hydrological patterns on large‐scale lake phytoplankton concentrations for the first time. Prior to dam completion, strong seasonal cycles and large spatial gradients in chlorophyll have been observed, related to natural fluctuations in the Omo River's seasonal discharge. During this period, mean lake chlorophyll showed a strong relationship with both river inflows and lake levels. Empirical models were derived which considered multiple hydro‐climatic drivers, but the best model for predicting chlorophyll‐a was a simple model based on Omo River discharge. Application of this model to data for 2015–2016 estimated that during the filling of Gibe III annual mean Lake Turkana chlorophyll declined by 30%. Future water management scenarios based on Gibe III operations predict reduced seasonal chlorophyll‐a variability, while irrigation scenarios showed marked declines in chlorophyll‐a depending on the level of abstraction. These changes demonstrate how infrastructure developments such as dams can significantly alter lake primary production. Our remote sensing approach is easy to adapt to other lakes to understand how their phytoplankton dynamics may be affected by water management scenarios.     

Modeling of sediment and heavy metal transport in Taihu Lake, China

With the current rapid economic growth, heavy metal pollution has become one of the key issues in the Taihu Lake. Although heavy metal pollution levels and distributions of the Taihu Lake have previously been described, an effective model to describe the transport process of heavy metals between the water column and sediment bed for this lake is not available. It is known that heavy metals in the water column can be related to the resuspension of sediment in the lake bed. In this study, we set up a coupled model of relating hydrodynamics, sediment and heavy metals based on Environmental Fluid Dynamics Code (EFDC), and applied it to Taihu Lake, China. For calibration and validation of the model, we employed two series of field sampling data taken all over Taihu Lake during April and July of 2009. The results show that the hydrodynamics simulations of the coupled model agree with the observations reasonably well and the sediment and heavy metal model shows similar variation trends during the simulation. Our results indicate that the model can be used for simulating the sediment and heavy metal transport process in the Taihu Lake and here we provide an effective tool for water quality management at small time scales.