基于最佳波段判别的湿地植物叶片全氮反演研究

利用高光谱遥感技术定量估测湿地植被叶片全氮含量,对于监测和诊断湿地植被的生理状况及生长趋势具有重要意义。但叶片氮素遥感诊断研究多存在反演模型过拟合、入选波段与生化参量间因果关系不明确和入选变量间"多重共线性"等局限。以芦苇(Phragmites australis)和香蒲(Typha angustifolia)叶片全氮含量作为研究对象,通过谱带分区,分区最佳波段选取和偏最小二乘回归相结合的方法构建芦苇和香蒲叶片全氮含量反演模型,并利用交叉验证决定系数(R2cv)和均方根误差(RMSEcv)对模型精度进行检验,尝试克服传统反演方法中的不足。结果表明,不同湿地植物类型相比,利用芦苇反射光谱建立的预测模型精度都高于香蒲。不同回归模型相比,一阶导数光谱-偏最小二乘回归模型(FDS-PLSR)精度远高于原始光谱-偏最小二乘回归模型(OS-PLSR)。芦苇最佳模型交叉验证决定系数(R2cv)达到了0.84,方根误差(RMSEcv)为0.10,香蒲最佳模型交叉验证的决定系数(R2cv)达到了0.66,方根误差(RMSEcv)为0.13,是构建湿地植物芦苇和香蒲光谱与叶片全氮含量关系的最佳模型。在不降低湿地植物叶片氮含量反演精度的基础上,有效地避免了传统地物高光谱模型反演中的局限性,是无损害遥感探测方面的有益尝试。     

基于挺水植物高光谱信息的再生水总氮含量估测——以北京市门城湖湿地公园为例

高光谱信息是探测植物体内氮素含量状况的重要手段,而植物体中的氮素与水体含氮量息息相关.本研究区为以再生水为主要补给水水源的北京门城湖湿地公园,通过获取区内典型的再生水氮净化挺水植物芦苇和香蒲叶片的高光谱数据,并在室内测定对应样点的水体总氮含量指标, 探讨基于典型湿地挺水植物高光谱数据对水体总氮进行遥感探测的可行性.采用4种高光谱参数(光谱指数、归一化差值指数、“三边”参数及吸收特征参数)分别建立一元线性模型、逐步多元回归模型和偏最小二乘模型,根据决定系数(R²)和均方根误差(RMSE)进行模型精度检验.结果表明: 逐步多元回归和偏最小二乘模型的预测精度高于一元线性模型. 3种模型对芦苇的拟合效果均优于香蒲.偏最小二乘模型对芦苇的拟合效果最优(R²=0.854,RMSE=0.647).500～700 nm是反映水氮含量的最佳波段范围,绿峰与红谷反射率的比值与水体总氮含量具有较强的相关性,尤其是吸收特征参数能够较好地预测水体总氮含量.     

湿地土壤全氮和全磷含量高光谱模型研究

氮磷是湿地生态系统土壤中的重要营养元素,其对湿地植被生长、湿地生态系统生产力、区域富营养化变化、湿地环境生态净化功能等具有重要的影响作用。研究氮磷营养物质在湿地土壤中的分布变化特征,对湿地生态系统评估、恢复和管理具有重要的意义。以中国高纬度地区面积最大的滨海芦苇湿地——盘锦湿地为研究区,采用不同建模方法(再抽样多元逐步回归模型bootstrap SMLR和再抽样偏最小二乘回归模型bootstrap PLSR)和光谱变换技术(包络线去除CR、光谱一阶微分FD和光谱倒数的对数LR),分别建立了湿地土壤全氮和全磷含量的估算模型。基于湿地土壤实测光谱,模拟高光谱Hyperion数据和多光谱TM数据,在此基础上进行湿地土壤营养元素含量估算。对比所建反演模型的估算精度,探讨高光谱遥感技术对湿地土壤营养元素组分的估算能力和适用性。研究结果表明:bootstrap PLSR相比于bootstrap SMLR建模方法,其对研究区湿地土壤全氮和全磷含量的估算获得了较高精度;对盘锦湿地土壤全氮含量的估算,最高估算精度产生于CR光谱变换技术结合bootstrap PLSR建模;对湿地土壤全磷含量的估算,最高估算精度产生于原光谱数据结合bootstrap PLSR建模;模拟高光谱数据Hyperion对湿地土壤全氮和全磷含量的估算精度均高于模拟多光谱数据TM,模拟Hyperion的估算精度更接近于实测光谱的估算精度。     

再生水补给河道内芦苇的光谱特征及其对水体氮和磷含量的响应

再生水是城市景观河湖的重要补给水源, 然而再生水中含量较高的氮和磷营养盐会引起水体富营养化, 破坏水生态平衡。以再生水补给的潮白河为研究区, 运用高光谱技术分析了挺水植物芦苇(Phragmites australis)叶片的光谱特征, 并结合水质数据, 通过拟合模型, 探究了芦苇对再生水中氮和磷的响应关系。结果表明, 各采样点水体的总氮(TN)和总磷(TP)含量分别介于1.85-18.16 mg·L^-1及0.01-0.36 mg·L^-1之间, 叶绿素a (Chl a)和溶解氧(DO)含量的范围分别为0.60-47.45 μg·L^-1与4.24-11.4 mg·L^-1。水体富营养化较为严重, 但仍处于富氧环境。多重方差分析表明, 不同采样点之间水体的TN、TP和Chl a含量差异显著(P<0.05)。由光谱反射率及反射率一阶导数曲线可知, 水体TN含量越高, 叶片光谱在可见光区的反射率越小, 红边位置也越向波长长的方向移动(即红移)。相关分析表明, 水体TN和TP含量与吸光度值log(1/R)在可见光区的相关性较强, 且TN与log(1/R)的相关系数高于TP。芦苇叶片光谱可在一定程度上区分水体TN含量差异, 但TP对光谱特征的影响模式不明显。光谱指数与水体TN含量之间的拟合模型中, 基于光化学指数(PRI)、修正叶绿素吸收指数(MCARI)和导数叶绿素指数(DCI)的模型能够解释水体TN含量变化的62.4%-70.9% (P<0.05), 可用于再生水氮含量的定量监测。该研究证明了植物光谱技术在水体富营养化监测上的可行性, 为保障再生水修复河道水质和生态安全提供了科学依据。     

Spectral Characteristics of Phragmites australis and Its Response to Riverine Nitrogen and Phosphorus Contents in River Reaches Restored by Reclaimed Water

再生水是城市景观河湖的重要补给水源, 然而再生水中含量较高的氮和磷营养盐会引起水体富营养化, 破坏水生态平衡。以再生水补给的潮白河为研究区, 运用高光谱技术分析了挺水植物芦苇(Phragmites australis)叶片的光谱特征, 并结合水质数据, 通过拟合模型, 探究了芦苇对再生水中氮和磷的响应关系。结果表明, 各采样点水体的总氮(TN)和总磷(TP)含量分别介于1.85-18.16 mg·L^-1及0.01-0.36 mg·L^-1之间, 叶绿素a (Chl a)和溶解氧(DO)含量的范围分别为0.60-47.45 μg·L^-1与4.24-11.4 mg·L^-1。水体富营养化较为严重, 但仍处于富氧环境。多重方差分析表明, 不同采样点之间水体的TN、TP和Chl a含量差异显著(P<0.05)。由光谱反射率及反射率一阶导数曲线可知, 水体TN含量越高, 叶片光谱在可见光区的反射率越小, 红边位置也越向波长长的方向移动(即红移)。相关分析表明, 水体TN和TP含量与吸光度值log(1/R)在可见光区的相关性较强, 且TN与log(1/R)的相关系数高于TP。芦苇叶片光谱可在一定程度上区分水体TN含量差异, 但TP对光谱特征的影响模式不明显。光谱指数与水体TN含量之间的拟合模型中, 基于光化学指数(PRI)、修正叶绿素吸收指数(MCARI)和导数叶绿素指数(DCI)的模型能够解释水体TN含量变化的62.4%-70.9% (P<0.05), 可用于再生水氮含量的定量监测。该研究证明了植物光谱技术在水体富营养化监测上的可行性, 为保障再生水修复河道水质和生态安全提供了科学依据。     

盐城滨海湿地优势植物碳氮磷生态化学计量高光谱反演

滨海湿地是海陆交界的生态过渡带,是自然界生物多样性最丰富的生态系统之一。湿地植物作为湿地生态系统重要的组成部分,研究其碳、氮、磷生态化学计量特征是了解植物生长状况与适应策略的有效途径。以江苏盐城滨海湿地为研究区,采集互花米草(Spartina alterifora)、芦苇(Phragmites australis)、白茅(Imperata cylindrica)、柽柳(Tamarix chinensis)、盐地碱蓬(Suaeda salsa)共5种优势湿地植物样本及冠层高光谱数据,对植物的碳、氮、磷生态化学计量特征进行高光谱反演研究。结果表示白茅、柽柳与芦苇的最佳反演模型为随机森林(RF)模型,对互花米草反演效果最好的是偏最小二乘(PLSR)模型,而对盐地碱蓬反演精度最高的是BP神经网络(BPNN)模型。研究表明利用高光谱数据可以实现湿地植物碳、氮、磷生态化学计量特征的准确反演,不同模型对于不同湿地植物的反演存在差异,RF模型的反演稳定性最强,是反演湿地植物生态化学计量特征的较优模型。     

不同水氮梯度下典型挺水植物叶绿素荧光的响应特性

叶绿素荧光测量分析可以揭示植物叶片光化学效率的变化,已越来越多地应用于植物生态监测。以再生水为主要补给水源的北京门城湖湿地公园为研究区,选取典型湿地挺水植物芦苇(Phragmites australis)、香蒲(Typha angustifolia)和茭白(Zizania latifolia)为研究对象,通过野外测量叶片尺度的叶绿素荧光参数和室内测定对应样点的水体总氮含量指标,研究了再生水补给条件下,不同水氮梯度植物叶绿素荧光的响应特性。结果表明,3种典型挺水植物的初始荧光(Fo)与最大荧光(Fm)随着水体总氮含量的增加呈现上升的趋势;PSII的量子效率(F_v/F_m)与实际量子效率(ΦPSII)受水氮含量的影响先升高,达到15–20 mg·L~(–1)区间时,则与之持平;光化学淬灭(qP)参数则呈现先升高后降低的变化趋势,而非光化学淬灭(NPQ)参数的变化没有明显的规律。当水氮含量为15–20 mg·L~(–1)时,光化学反应减弱,光合作用出现抑制。不同类型植物的荧光参数也有所不同,处于生长期(6月)植物的光合作用显著强于生长成熟期(9月)。     

乌梁素海湿地芦苇最大羧化速率的高光谱遥感

湿地植被生产力和固碳潜力的研究是全球碳循环和全球变化的热点研究问题。湿地植被的光合能力能够指示其生长的健康状态。最大羧化速率是重要的植被光合参数之一,对精确模拟湿地植被光合作用和气体交换模型中的固碳过程具有重要的作用。以内蒙古乌梁素海湖泊湿地为研究区,进行了芦苇叶片光合参数和光谱的测量。芦苇叶片最大羧化速率(V_(cmax))数值是基于Farquhar光合作用模型,从光合测量获取的A-C_i曲线计算并校正到25℃得到的。分别基于bootstrap PLSR模型、单波段和高光谱植被指数(包括简单比值指数SR和归一化差值指数ND),构建湿地芦苇叶片最大羧化速率(V_(cmax))估算模型。基于高光谱遥感图像HJ-1A HSI,采用ND高光谱指数中具有较高V_(cmax)估算精度的入选波段702和756 nm,获取研究区湿地芦苇最大羧化速率空间分布图。研究结果表明,湿地植被光谱特征和高光谱植被指数,可用于估算湿地芦苇V_(cmax),其中最高精度产生于基于bootstrap PLSR模型的建模方法(R~2=0.87,RMSECV=3.90,RPD=2.72),ND高光谱指数的V_(cmax)估算精度高于SR高光谱指数的估算精度;从获取的V_(cmax)空间分布图上提取估算值,其与测量值对比,存在较好的相关性(R~2=0.80,RMSE=4.74)。     

基于可见光波段包络线去除的湿地植物叶片叶绿素估算

研究采用芦苇和香蒲叶片光谱及实测叶绿素含量数据,选取波段谱带范围为可见光波段400—760nm(为了避免近红外波段受叶片水分含量的影响,降低构建模型的稳定性),利用相关分析与逐步回归分析的统计学分析方法,建立叶面尺度下不同包络线去除衍生转换光谱:BD(band depth)、CRDR(continuum-removed derivative reflectance)、BDR(band depth ratio)、NBDI(normalized band depth index)与叶绿素含量估算模型。通过对入选波段的统计表明在550—750nm,特别是700—750nm(红边)波段范围内产生了较多的有效波段,是今后进行生物参量反演的重点波段范围。舍一交叉验证结果表明芦苇、香蒲和混合样本绿素含量估测的最佳模型分别为BD、CRDR和NBDI模型,其交叉验证决定系数依次为0.87、0.83和0.81,交叉验证均方根误差RMSE依次为0.16、0.15和0.33。并在此基础上利用独立样本非参数检验和多因子方差分析,探讨相关因素对于叶绿素含量估算模型精度的影响。结果表明物种差异、数据类型差异对于叶绿素回归模型的影响较大,而光谱类型差异及光谱数据与数据类型交互作用对于回归模型精度的影响较小。     

乌梁素海湿地富营养化研究进展

本文回顾了乌梁素海湿地近20年来富营养化的研究成果。乌梁素海湿地富营养化主要状况表现为:(1)水体氮、磷平均含量已超国家地表水环境质量标准Ⅴ类要求;空间分布上,总体特征为北高南低,西高东低,局部特征则与植物分布有关;时间分布上,总体受河套地区退水和气温变化影响,局部受植物生长影响。(2)沉积物氮、磷显著富集,氮含量在水平方向上北高南低,西高东低,垂直方向上随深度增加而递减,磷含量则无一致规律。(3)藻类时空分布与氮、磷表现出较为一致的规律。近年来,藻类的过量繁殖常导致"黄苔"暴发。(4)水体有机质显著富集,与氮含量空间分布特征一致。(5)沉积物有机质主要来源于陆源输入和水生生物,与氮具有显著的同源性且空间分布特征一致;沉积物有机质显著富集,成为重要内源污染源。今后应加强乌梁素海湿地富营养化机理研究,为乌梁素海湿地恢复提供科学依据和技术支撑。     

Estimation of Potentially Toxic Elements Contamination in Anthropogenic Soils on a Brown Coal Mining Dumpsite by Reflectance Spectroscopy: A Case Study

In order to monitor Potentially Toxic Elements (PTEs) in anthropogenic soils on brown coal mining dumpsites, a large number of samples and cumbersome, time-consuming laboratory measurements are required. Due to its rapidity, convenience and accuracy, reflectance spectroscopy within the Visible-Near Infrared (Vis-NIR) region has been used to predict soil constituents. This study evaluated the suitability of Vis-NIR (350–2500 nm) reflectance spectroscopy for predicting PTEs concentration, using samples collected on large brown coal mining dumpsites in the Czech Republic. Partial Least Square Regression (PLSR) and Support Vector Machine Regression (SVMR) with cross-validation were used to relate PTEs data to the reflectance spectral data by applying different preprocessing strategies. According to the criteria of minimal Root Mean Square Error of Prediction of Cross Validation (RMSEP_cv) and maximal coefficient of determination (R²_cv) and Residual Prediction Deviation (RPD), the SVMR models with the first derivative pretreatment provided the most accurate prediction for As (R²_cv) = 0.89, RMSEP_cv = 1.89, RPD = 2.63). Less accurate, but acceptable prediction for screening purposes for Cd and Cu (0.66 ˂ R²_cv) ˂ 0.81, RMSEP_cv = 0.0.8 and 4.08 respectively, 2.0 ˂ RPD ˂ 2.5) were obtained. The PLSR model for predicting Mn (R²_cv) = 0.44, RMSEP_cv = 116.43, RPD = 1.45) presented an inadequate model. Overall, SVMR models for the Vis-NIR spectra could be used indirectly for an accurate assessment of PTEs’ concentrations.     

Estimating photosynthetic traits from reflectance spectra: A synthesis of spectral indices,numerical inversion,and partial least square regression

The lack of efficient means to accurately infer photosynthetic traits constrains understanding global land carbon fluxes and improving photosynthetic pathways to increase crop yield. Here, we investigated whether a hyperspectral imaging camera mounted on a mobile platform could provide the capability to help resolve these challenges, focusing on three main approaches, that is, reflectance spectra-, spectral indices-, and numerical model inversions-based partial least square regression (PLSR) to estimate photosynthetic traits from canopy hyperspectral reflectance for 11 tobacco cultivars. Results showed that PLSR with inputs of reflectance spectra or spectral indices yielded an R² of ~0.8 for predicting V _cmax and J _max, higher than an R² of ~0.6 provided by PLSR of numerical inversions. Compared with PLSR of reflectance spectra, PLSR with spectral indices exhibited a better performance for predicting V _cmax (R² = 0.84 ± 0.02, RMSE = 33.8 ± 2.2 μmol m⁻² s⁻¹) while a similar performance for J _max (R² = 0.80 ± 0.03, RMSE = 22.6 ± 1.6 μmol m⁻² s⁻¹). Further analysis on spectral resampling revealed that V _cmax and J _max could be predicted with ~10 spectral bands at a spectral resolution of less than 14.7 nm. These results have important implications for improving photosynthetic pathways and mapping of photosynthesis across scales.     

The role of plants in the removal of nutrients at a constructed wetland treating agricultural (dairy) wastewater,Ontario, Canada

The South Nation River Watershed, in eastern Ontario, Canada, is an agricultural watershed impacted by excess nutrient loading primarily from agricultural activities. A constructed wetland for the treatment of agricultural wastewater from a 150-cow dairy operation in this watershed was monitored in its eighth operating season to evaluate the proportion of total nitrogen (TN) (approximated by total Kjeldahl nitrogen (TKN) due to low NO₃⁻) and total phosphorus (TP) removal that could be attributed to storage in Typha latifolia L. and Typha angustifolia L., which dominate this system. Nutrient loading rates were high, with 16.2 kg ha⁻¹ d⁻¹ N and 3.4 kg ha⁻¹ d⁻¹ P entering the wetland and loading the first wetland cell. Plant uptake accounted for 0.7% of TKN removal when the vegetated free water surface cells were considered together. However, separately, in the second wetland cell with lower N and P loading rates, plants accounted for 9% of TKN, 21% of NH₄⁺ and 5% of TP removal. Plant uptake was significant to overall removal given wetland age and nutrient loading. Nutrient storage during the growing season at this constructed wetland helped reduce the nutrient load entering the watershed, already stressed by intensive local agriculture.     

Microalgal fatty acid composition: rapid assessment using near-infrared spectroscopy

The feasibility of assessing microalgal fatty acid composition using near-infrared spectroscopy (NIRS) is described. The chlamydomonad microalga, Rhopalosolen saccatus (previously known as Characium saccatum), was isolated from the Fitzroy River, Central Queensland, Australia. R. saccatus was grown in batch culture with varying phosphorus nutrition and assessed for dry matter, total lipid and fatty acid composition using gas chromatography (GC). Transmission spectra (1100–2500 nm) were acquired of liquid culture, and reflectance spectra were acquired of wet and dry filtrates of cultures and of methyl esters. Partial least square (PLS) regression models were built on biomass, total lipid and a number of fatty acids. All sample presentation models supported PLS regression model with a cross validation correlation coefficient (R _cv) >0.87 for biomass and R _cv >0.68 for total lipid; however, the use of dry filtrates of culture is recommended as the sample presentation mode of choice. Models for fatty acids based on culture transmission spectra, reflectance spectra of wet and dry culture filtrates, or reflectance spectra of methyl esters in solvent were not acceptable. Dry extracts of methyl esters supported adequate models for fatty acids from C8:0 to C22:0, with the exception of capric and behenic acids, with an R _cv of 0.89–0.94; however, in practice, samples processed to this stage can be easily analyzed by GC. Near-infrared spectroscopy can be a potential choice for rapid estimation of biomass (dry matter) and lipid content and composition in microalgae, with further work required to demonstrate oping robustness of the calibration model in prediction of unknown samples.     

Multilevel responses of emergent vegetation to environmental factors in a semiarid floodplain

Wetland emergent vegetation of Tablas de Daimiel National Park (Central Spain), mainly composed by Cladium mariscus, Phragmites australis and Typha domingensis, was studied to test if population responses to environmental factors were invariant to scaling-up conditions from the single plant to the entire wetland. While the significance of the main controlling, abiotic factors (wetland location, sedimentary and water nitrogen and phosphorus, water level, duration of flooding) was that of earlier studies, the importance of them changed along with the level of plant organization. Our study showed that multiple effects occurred in the responses of helophyte populations to abiotic factors, and that these responses appeared to depend upon the level of observation involved, showing positive (Typha biomass and sedimentary phosphorus), negative (Cladium biomass and sedimentary phosphorus, Cladium large patch growth and total phosphorus), delayed (landscape cover of Phragmites and Cladium and water level of the previous year), saturation (Cladium biomass and water level), threshold (small patch growth rate of Cladium and water level of the previous month) and non-linear (landscape cover of Phragmites and Cladium and total phosphorus in water) effects.     

蚯蚓对湿地植物光合特性及净化污水能力的影响

以香蒲、芦苇和美人蕉为研究对象,并以土壤+沙子+有机质混合物为供试基质模拟人工湿地处理污水,采用向基质中加入蚯蚓与未加入蚯蚓2种处理。研究加入蚯蚓后,香蒲、芦苇和美人蕉光合速率、蒸腾速率、SPAD值和水分蒸发、蒸腾量的变化及其对净化污水能力的影响。结果表明:与未加入蚯蚓相比,加入蚯蚓后,香蒲、芦苇和美人蕉的净光合速率、蒸腾速率、SPAD值和水分蒸发、蒸腾量均增加,其中芦苇的净光合速率、蒸腾速率和水分蒸发、蒸腾量增加达到显著水平(P <0.05),而香蒲的水分蒸发、蒸腾量增加也达到显著水平(P <0.05);加入蚯蚓后,香蒲、芦苇和美人蕉对COD_Mn、NH₄⁺-N、NO₃^--N、TN和TP的去除率均增加,且香蒲和芦苇对COD_Mn的去除率显著增加 (P <0.05)。加入蚯蚓后,香蒲、芦苇和美人蕉的SPAD值均增加,说明蚯蚓能提高湿地植物对氮的吸收,增加植株中的氮含量,促进湿地植物的光合速率和蒸腾速率从而提高对污水的净化能力。     

Enhancement of nitrogen removal in towery hybrid constructed wetland to treat domestic wastewater for small rural communities

Efforts to protect watercourses, especially sources of drinking water, particularly in rural areas, are now underway in China. Nitrogen present in wastewater, due to its role in eutrophication and potential toxicity to aquatic species, is a focus of primary concern. Constructed wetlands (CWs), a simpler, less costly treatment alternative, have been used to treat domestic wastewater for small communities. Although showing great promise for removing carbonaceous materials from wastewater, wetland systems have not been successful in removing nitrogen mainly due to lack of dissolved oxygen (DO). To enhance nitrogen removal, a novel CW configuration with three stages, towery hybrid constructed wetland (THCW), was designed. The first and third stages were rectangle subsurface horizontal flow CWs, and the second stage was a circular three-layer free-water flow CW. Increased DO by passive aeration of a tower type cascade overflow from the upper layer into the lower layer in the second stage of the wetland enhanced nitrification rates. Denitrification rates were also improved by additional organic matter supplied as a result of bypass influent directly into the second stage. Evergreen tree Pond Cypress (Taxodium ascendens), industrial plants Mat Rush (Schoenoplectus trigueter) and Wild Rice shoots (Zizania aquatica), ornamental floriferous plants Pygmy Waterlily (Nymphaea tetragona) and Narrow-leaved Cattail (Typha angustifolia) were planted in the wetland. The average percentage of removal was 89%, 85%, 83%, 83% and 64% for total suspended solid, chemical oxygen demand, ammonia nitrogen, total nitrogen and total phosphorus, respectively. There was no significant difference (p < 0.05) at low and high hydraulic loads (16 cm/d and 32 cm/d) for performance of THCW. Nitrifying and denitrifying bacteria as well as potential nitrification activity and potential denitrification rates measured have shown that nitrification–denitrification is the main mechanism for nitrogen removal in the wetland. THCW also provided additional aesthetic benefits.     

叶冠尺度野鸭湖湿地植物群落含水量的高光谱估算模型

利用高光谱遥感技术定量估测野鸭湖湿地植被含水量,对于监测和诊断野鸭湖湿地植被的生理状况及生长趋势具有重要意义,也能够为高光谱遥感影像在野鸭湖湿地植被含水量诊断中的实际应用提供理论依据和技术支持.采用Field Spec 3野外高光谱辐射仪,获取了野鸭湖典型湿地植被冠层和叶片的光谱,并测定了对应的含水量.以上述实测数据为基础,首先以芦苇为例初步探明了不同含水量水平下典型湿地植被冠层和叶片光谱反射率的响应模式,然后采用相关性及单变量线性与非线性拟合分析技术,从冠层和叶片两种层次,对不同尺度下的含水量与“三边”参数及高光谱植被指数进行了分析拟合,并采用交叉检验中的3K-CV方法对估算模型进行了测试和检验,确立了不同尺度下野鸭湖湿地植被含水量的定量监测模型.结果表明:(1)随着含水量水平的增加,芦苇冠层与叶片光谱在可见光波段(350-760 nm)和红外波段(760-2500 nm)的反射率均呈逐渐降低趋势.(2)不同尺度含水量与选取的光谱特征参数整体上相关性较强,与“三边”参数基本上都呈极显著相关,相关系数最大达到0.906;与高光谱指数全部呈极显著相关,相关系数最小为0.455,最大达到0.919,并通过选取不同尺度上相关性最佳的光谱特征参数,分别基于“三边”参数和高光谱植被指数构建了不同尺度下的含水量估算模型.其中,冠层尺度下,黄边面积(SDy)与SRWI( Simple Ratio Water Index)的估算效果最好,估算模型分别为y=-9.462x2 -2.671x+0.608和y=0.219e1.010x;叶片尺度下,红边面积(SDr)与WI( Water Index)的估算效果最好,估算模型分别为y=0.562x+0.376和y=2.028x2 -0.476x-1.009.通过3K-CV的交叉验证,不同尺度下的含水量估算模型均取得了较为理想的预测精度,预测精度的最小值为94.92％,最大值为97.06％,表明估测模型具有较高的可靠性与普适性.(3)高光谱植被指数与含水量拟合方程的拟合度相对高于“三边”参数与之建立方程的拟合度,说明多波段组合的光谱特征参数更适合含水量的判别.