太湖水体叶绿素浓度与反射光谱特征关系的研究

根据2004年10月在太湖实测的水体反射光谱及实验室分析得到的叶绿素浓度数据,对太湖水体反射光谱特征与叶绿素浓度之间的关系进行探讨与分析。研究结果表明:水体叶绿素浓度与各波长处的反射光谱相关性不大,但是反射光谱经过比值法和微分处理后,两者具有很好的相关性,而且叶绿素浓度与反射光谱700nm附近波峰几何形态特征(波峰位置、面积、净高度)相关性很好,建立太湖水体叶绿素浓度估算模型。     

水稻叶绿素浓度与光谱反射率关系研究

结合田间小区实验,获取了水稻生育期9组叶片叶绿素浓度和相应的光谱反射率数据,进行了相关分析研究,结果表明:水稻叶片叶绿素浓度与其光谱反射率之间具有相关性,在450～686nm和750～770 nm光谱区内相关性较好,且在686 nm处两者达到最高的相关性;水稻叶片的“红边”拐点波长位置与其叶绿素浓度之间具有很强的相关性,复相关系数为0.88,并由此进一步讨论了高光谱遥感定量探测水稻叶绿素浓度的可行性。
     

太湖水体时间序列叶绿素浓度与反射光谱特征分析

对2008年5月到2009年5月采集的太湖水体反射光谱数据进行了异常数据检测、归一化等预处理后,计算了常用于叶绿素浓度反演的特征参量,包括荧光峰高度、荧光面积、特征波段比值、反射率微分;并分析建立了这些特征参量与对应叶绿素浓度的相关模型。研究表明：荧光面积、特征波段比值等与实测叶绿素浓度具有较好的相关性,而蓝绿光波段反射率比值对内陆水体叶绿素浓度反映不明显。湖泊水体的光学特征能够较好反映蓝藻的不同生长状态,太湖蓝藻随时间变化的规律大致可分为5月～11月,12月～4月两个阶段。本研究结果可为湖泊水体富营养化高光谱遥感监测的波段选择提供参考。     

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。     

秋季太湖叶绿素a浓度荧光反演研究

基于2007年11~12月太湖全湖实测水质参数和光谱数据,首先利用高斯方程对遥感反射率进行过滤分解,找出叶绿素a(chl\|a)吸收峰675 nm以后的荧光反射峰(Fluorescence Peak:FP),再以662 nm处的反射率为基准,采用归一化荧光高度法进行叶绿素a浓度(C chl-a)反演,得到chl-a反演模型。基于高斯分解获取的chl-a的荧光反射峰值R(FP)与662 nm处的反射率R (662)比值［R(FP)/R(662)］与C chl-a之间存在显著的相关性,该模型为秋季太湖水体C chl-a的最佳反演模型。在高悬浮泥沙条件下,该模型能够较好地表示出叶绿素荧光高度与叶绿素浓度之间的关系,为C chl-a反演提供新的方法和依据,并为传感器敏感波段的选取和设置提供参考。     

松毛虫危害的光谱特征与虫害早期探测模式

根据生态学特征，本文将松毛虫危害的针叶样品分为５个等级，对其反射光谱和叶绿素含量进行了测量分析。结果表明，随受害程度加重，叶绿素含量降低，５５０ｎｍ处的反射率、近红外肩反射率与红光最低反射率之差及红界一阶导数谱最大值均呈下降趋势，６３０ｎｍ处反射率呈上升趋势，红界光谱蓝移、叶绿素反射峰红移明显。应用逐步判别分析法对比分析证实了细分光谱特征参量比绿、红、近红外三波段反射率参量有更强的判别分类能力，这     

褐潮土的光谱特性及用土壤反射率估算有机质含量的研究

本文通过ASDFR便携式光谱仪对132个风干土壤样品的光谱反射率进行了实验室测定。根据土样光谱反射率变化,获得了褐潮土土壤剖面的不同诊断层反射光谱特征。结果表明,在400～1200nm范围之间,土壤有机质含量与土壤光谱反射率有较好的相关性。利用导数光谱方法建立了预测土壤有机质含量的方程,提出了预测北京地区褐潮土有机质光谱的最佳波段。在波长447nm处采用反射率和A值(反射率倒数的对数)所建立的预测方程的预测精度较高。采用反射率的一阶微分建立的预测方程的最佳波段在516nm处。而A值一阶微分光谱在615nm处相关性最好。作为一项参考指标用光谱分析法评价土壤中有机质含量,以期对精准农业中土壤养分或肥力的预测具有一定的指导作用。     

扎龙湿地龙泡子水深的高光谱建模研究

以扎龙湿地龙泡子为研究区,用实测高光谱数据和同步测量的水深数据,建立湿地湖泊的水深反演模型。通过分析水体反射率的一阶微分与水深之间的相关性来选取水深反演因子,建立了水深反演单波段模型和多波段模型,以波长832.05、839.87、809.08和774.76 nm建立的多波段线性模型效果较好,相对误差为5.90%,均方根误差为10.869 cm。湿地内影响因素较复杂,要深入研究水中杂质和水体底质的光谱特征才能进一步提高反演模型精度。     

高光谱技术提取不同作物叶片类胡萝卜素信息

以棉花、玉米、大豆、甘薯四种作物为材料，各采集叶片30张(处于不同部位、不同功能期)，分别测定其反射光谱和叶绿素、类胡萝卜素含量。目的在于探讨利用高光谱技术提取类胡萝卜素信息的可行性方法。结果表明，由于叶绿素与类胡萝卜素间存在显的相关性，在叶片水平，利用高光谱反射率估测叶片类胡萝卜素绝对量是可行的。与类胡萝卜素／叶绿素比值或类胡萝卜素含量相比，类胡萝卜素密度(单位叶片面积类胡萝卜素总量，Cardens)与光谱反射率间的相关性更为稳定。类胡萝卜素光谱吸收峰(470nm)附近的反射光谱与Cardens间的相关性较差，基于类胡萝卜素吸收峰附近反射光谱的光谱指数(如PSSRc、PSNDc)与Cardens间也表现出较弱的相关性。叶绿素光谱指数(如SR705、ND705)与Cardens间存在良好的相关性，红边光谱区的微分光谱、包络线归一化吸收深度等高光谱指数与Cardens间也表现出了良好的相关性。     

晋江水体悬浮物浓度的高光谱建模分析

采用适合二类水体的水表面以上光谱测量法,对福建省晋江下游河段进行高光谱采样。通过实测的高光谱反射率及其一阶微分值与晋江水体悬浮物浓度的相关分析,发现利用高光谱数据反演晋江悬浮物浓度的最适合波长位于733±3 nm处。进而采用线性、二次多项式、对数、指数、乘幂等函数对晋江的悬浮物浓度进行模拟,发现二次多项式模型的模拟效果和精度最高,且采用单波段的回归模型要比采用一阶微分值的回归模型更为稳定,因此建立了单波段二次多项式模型用于晋江悬浮物浓度的预测。     

Spectral mixture analysis of inland tropical waters

This letter presents results of experiments conducted to assess the use of linear mixing models to unmix the reflectance spectra of water. The model was tested with 11 reflectance spectra measured at Tucurui reservoir, Brazilian Amazon. The results showed that the fraction of chlorophyll reflectance accounting for the reflectance spectra of the various samples correlate significantly with the chlorophyll concentration in the 600 to 700 nm spectral region.     

长江口及邻近海域悬浮颗粒物对叶绿素a遥感反演算法的影响分析

利用水介质光辐射传输数值模型Hydrolight,结合前人对长江口及邻近海域水体的生物—光学模型研究,模拟不同光学水体的遥感反射率,并分析遥感反射率对悬浮颗粒物(SPM)的敏感性以及SPM对4种叶绿素a(Chla)反演算法(二波段、三波段、荧光基线高度(FLH)和综合叶绿素指数(SCI)算法)的影响。结果表明:由Hydrolight模拟得到的遥感反射率与现场同步实测的遥感反射率的均方根误差小于0.01sr-1,其中可实现遥感反射率在550~725nm波段较精确的模拟。遥感反射率对SPM的敏感性随着Chla浓度的升高而降低。二波段、三波段算法适合低SPM浓度水体的Chla浓度反演,FLH算法反演Chla浓度时易受SPM的影响,而SCI算法在中、高SPM浓度水体中消除SPM的影响进而反演Chla的潜力较好。     

Study on the Inversion of Chlorophyll Content of Spartina Alterniflora Leaf in the Yangtze River Estuary Wetland based on Spectral Analysis#br#

Spartina alterniflora is one of the most important invasive species in the coastal wetlands in China,which have a profound impact on the local ecological system.The information of chlorophyll content is an important basic data for quantitative research on key ecological function of wetland ecosystem.The Yangtze River in Chongming Dongtan wetland is the study area.Based on the measured leaf spectral reflectance and total chlorophyll content of Spartina alterniflora,in the range of 400~1 000 nm,the ratio of the original form of the spectral reflectance and first derivative spectral reflectance(RVI)and normalized difference vegetation index(NDVI)in the form of combination are established for the correlation with the content of chlorophyll and the construction of the estimation model.The results show that RVI and NDVI vegetation index form model based on the original spectra have the highest accuracy,whose root mean square error(RMSE)are up to respectively 0.24 and 0.25;Because of the nosie in the first derivative spectral reflectance,the estimation model of chlorophyll has poor results;Based on the band selected from the model,the red edge band is particularly important in the estimation of chlorophyll content of Spartina alterniflora.     

Hyperspectral remote sensing of turbidity and chlorophyll a among Nebraska Sand Hills lakes

This study was conducted to establish correlations between reflectance spectra, turbidity and chlorophyll a among 22 fresh to alkaline lakes in Nebraska, U.S.A., sampled in June and July of 1994. Peak reflectance ranged from 2-22 per cent between 500 and 600nm. Turbidity and chlorophyll a ranged from 1-82 NTU and 1-17 1 mu gl-1, respectively, with significant correlation (P<0.001) between the two. Reflectance first-derivatives corresponding to wavelengths 429 and 695nm, were significantly correlated with chlorophyll a (P<0.001), and derivatives at 429, 628 and 695nm were significantly correlated with turbidity (P<0.001) despite a wide range in water quality conditions.     

Remote estimation of chlorophyll content in higher plant leaves

Indices for the non-destructive estimation of chlorophyll content were formulated using various instruments to measure reflectance and absorption spectra in visible and near-infrared ranges, as well as chlorophyll contents from several non-related species from different climatic regions. The proposed new algorithms are simple ratios between percentage reflectance at spectral regions that are highly sensitive (540 to 630nm and around 700nm) and insensitive (nearinfrared) to variations in chlorophyll content: R NIR / R 700 and R NIR / R 550. The developed algorithms predicting leaf chemistry from the leaf optics were validated for nine plant species in the range of chlorophyll content from 0.27 to 62.9mug cm -2. An error of less than 4.2 mugcm -2 in chlorophyll prediction was achieved. The use of green and red (near 700nm) channels increases the sensitivity of NDVI to chlorophyll content by about five-fold.     

Backscattering properties of marine phytoplankton Prorocentrum micans

Backscattering coefficients of Prorocentrum micans were determined in the laboratory using the Hydroscat-6 instrument. Ancillary parameters measured included absorption and scattering coefficients, chlorophyll-a concentration, cell size, and cell concentration. Spectral variability was found in the case of the backscattering coefficients, and the maximum backscattering coefficient was obtained at 488 nm, which deviated from the theory because of pigment absorption. We were unable to detect the effect of chlorophyll fluorescence on the shape of the backscattering coefficient spectra at 700 nm. However, the particulate backscattering coefficient was found to be well correlated with chlorophyll-a concentration at the six chosen wavelengths. At the same time, the backscattering ratio was accurately arranged in the range 0.012 to 0.019 at 442 nm and 0.013 to 0.021 at 620 nm. A positive correlation between particle density and backscattering ratio was established with a nonlinear regression model and the correlation coefficient was as high as 0.96 at 442 nm, this providing a good foundation for improving the accuracy of identifying the red tide alga, P. micans, for water colour remote sensing.     

基于HJ-1卫星CCD数据的厦门海域叶绿素a浓度反演

针对HJ-1A/B卫星CCD数据,建立适合于厦门海域的叶绿素a浓度反演模型,将为持续监测该海域的赤潮提供时间序列的叶绿素a浓度数据。基于2013年7月31日厦门海域水体实测光谱与叶绿素a浓度同步测量数据,及HJ\|1B卫星CCD2光谱响应函数,对各波段遥感反射率与叶绿素a浓度的相关性进行比较,证实蓝、绿波段比值与叶绿素a浓度相关性最高。对OC3模型在内的5种模型的反演结果和实测叶绿素a浓度做相关性分析,发现各模型相关系数均达到0.7以上。利用2013年7月30日实测数据对同期厦门海域HJ-1B卫星CCD2数据叶绿素a浓度反演结果进行精度验证,结果表明本地化的10指数模型在反演叶绿素a浓度动态范围较大的区域具有更高的精度。