The Study of Spatial-Temporal Characteristics for Chlorophyll Concentration derived from Remote Sensing Image in Xinfengjiang Reservoir

By investigating the law of radiative transfer and the process of scattering and absorption from suspended sediment，chlorophyll and oxygen\|consuming organics，this paper builds the model，it formulate the functional relationship between the reflection and the concentration of this three kinds of water quality parameters，therefore retrieve the concentration.With this model，the chlorophyll concentration in Xinfengjiang Reservoir can be inversed，then using the measured data to verify the inversion result，the correlation coefficient between them equals 0.94，and the average relative error equals 66.67%.By analyzing the characteristics of the chlorophyll spatial structure and its time distribution based on the result，we find out that the lowest concentration of the chlorophyll is always existing in the center area during the whole year，and the area near Xinfengjiang River and Zhongxinshui River has the highest concentration，associated with cage culture.Multiple factors has been considered in the model building in this paper，and hence multi\|spectral remote sensing data were successfully applied to improve the calculation accuracy.     

Soil Heavy Metals Estimation based on Hyperspectral in Urban Residential

To explore the possibility of using soil spectral reflectance to estimate soil heavy metal content in urban residential area，this study chooses 30 soil samples of Cu，Pb and Zn in Minhang Residential area，Shanghai Province.Through the spectral factor transform to highlight its eigenvalues，constructed Multiple Linear Stepwise Regression(MLSR) model and Partial Least Squares Regression(PLSR) model based on spectral reflectance of soil heavy metals.The results show that the reciprocal first-order and the logarithmic first-order differential transformation can effectively enhance the heavy metal soil spectral characteristics.The best characteristic bands of Cu，Pb and Zn are 1 042.7 nm、706.84 nm and 1 404.8 nm.In terms of model stability and accuracy，PLSR model is better than MLSR model.The RMSE of Cu and Zn were only about 10% of the mean value of heavy metals in the study area，and the accuracy of the model was high.Compared with Cu and Zn，the R2 of Pb is between 0.64~0.88 which with higher model stability.By preprocessing the spectral data，the partial least-squares regression can effectively improve the accuracy of estimating the heavy metal content in urban residential areas. 〖WTHZ〗Key words:〖WT〗 Urban residential area;Soil heavy metals;Hyperspectral;Multivariate Linear Stepwise Regression(MLSR) model;Partial Least Squares Regression(PLSR) model 〖HT〗〖ST〗〖HJ〗〖WT〗〖JP〗〖LM〗     

基于偏最小二乘的土壤重金属铜含量高光谱估算

为探究高光谱数据估算土壤重金属铜含量的可行性，以石家庄市水源保护区褐土为研究对象，对不同光谱变换数据与重金属铜含量做了相关分析，建立了土壤重金属铜的单光谱变换指标偏最小二乘模型和多光谱变换指标偏最小二乘模型。结果表明：光谱反射率（R）经倒数一阶微分（RTFD）变换后与铜含量的相关性有所提高；光谱敏感波段为418、427、435、446、490、673、1 909、1 920和2 221 nm，基本位于土壤氧化铁、粘土矿物的特征吸收区域；对土壤重金属铜含量估算效果最好的单光谱变换指标偏最小二乘模型为RTFD模型，其模型决定系数（R²）为0.649，均方根误差（RMSE）为1.477；多光谱变换指标偏最小二乘模型R²和RMSE分别为0.751和1.162，建模效果优于单光谱变换指标模型。研究结果可为北方地区褐土类型土壤重金属铜的高光谱估算提供借鉴。     

Remote Sensing Inversion of Soil Zinc Pollution in Gejiu Mining Area of Yunnan

As a product of the development of modern industry and mining industry,heavy metal Zn pollution has gradually invaded the daily production and life of human beings,which is harmful to our physical and mental health.In dealing with large-scale soil environmental monitoring.The traditional heavy metal monitoring method is time-consuming and laborious.Due to its characteristics of high speed,high speed and high efficiency,remote sensing technology has become an important tool for environmental monitoring in the new era.This study takes Yunnan Gejiu mining area as a typical area,collecting sample in field soil and measurement of soil sample spectra and Zn content.Then the band transform method based on the multiplicative transformation was proposed to enhance product conversion relationship between Zn elements and spectral sensitive bands,using the established prediction model and optimal Zn content based on ASTER images to carry out pollution mapping.Research shows that：①the maximum correlation band of Zn elements is the B515 band,close to the absorption peak of sphalerite and smithsonite zinc containing minerals,is an important band of zinc element inversion of soil;②the spectral multiplicative transformation can highlight the sensitive bands of Zn elements,and retain the most sensitive information of the original soil;③in the hypersecretion inversion model of soil zinc content in the study area,the precision of the model established by partial least squares(R=0.90)is the highest(R=0.70);④The inversion results based on ASTER images show that there is a significant correlation between soil Zn pollution and mining activities(Verification accuracy of map R=0.694).The results of this study can provide the basis and technical support for remote sensing quantitative inversion of heavy metal content and large-scale environmental pollution monitoring.     

A spectral-based method for reconstructing spatial distributions of soil surface temperature during simulated fire events

Heterogeneous heat was applied to a homogenous soil surface to simulate a natural fire event. Subsequently cooled soil samples were evaluated spectrally and a spectral-spatial cube was generated corresponding to the burned area. Heat-induced spectral changes associated with thermal effects on soil minerals were observed across the entire spectrum, including: soil color changes (iron-oxide transformation); shifting absorption bands (iron-oxide transformation and illite/calcite ratio); changes in spectral shape (illite/montmorillonite ratio); disappearing absorption features (unknown); and changes in the overall brightness (soot). A model was developed using Partial Least Squares (PLS) to predict maximum soil surface temperatures, measured using thermocouples, from soil spectral reflectance. Thus, this proof-of-concept study demonstrates that soil spectroscopy reveals important information about soil temperature history and as such, represents a promising tool for viewing fire events retrospectively.     

吐鲁番盆地葡萄园土壤重金属铅含量高光谱估算

土壤重金属铅污染作为现代工矿业发展的产物,已逐渐入侵到农业生产和农产品中。高光谱技术由于具有宏观、快速、高效的特点已成为土壤重金属监测的重要手段。以新疆吐鲁番盆地葡萄园土壤Pb元素为研究对象,分析土壤原始光谱在内的15种光谱变换下的土壤光谱反射率数据与土壤Pb含量的关系,构建土壤Pb含量偏最小二乘回归（PLSR）模型和地理加权重回归（GWR）模型,对比分析并探讨运用土壤高光谱估算葡萄园土壤Pb含量的可行性。结果表明：土壤原始光谱反射率通过光谱变换能有效增强葡萄园土壤Pb元素的光谱特征及模型估算精度,其中,平方根二阶微分（SRSD）变换的PLSR模型和GWR模型估算能力最优。采用GWR模型比PLSR模型更好的解释葡萄园土壤重金属Pb含量高光谱估算。从模型稳定性和精确性来看,在平方根二阶微分变换中GWR模型R²从PLSR模型的0.262提高至0.866, 平方根误差减少了1.009。采用GWR模型可有效提高估算葡萄园土壤Pb含量的精度,为中国葡萄园基地土壤重金属污染以及土壤环境安全研究提供有益借鉴。     

An O2-A Band Atmospheric Correction Algorithm for Tower-based Platform based on Look-up Table

Tower-based spectral observation is an important connecting bridge between flux sites and satellite remote sensing data，and the effect of atmospheric absorption and scattering between horizontal surface and tower-based platform on the atmospheric absorption band such as O2-A is difficult to ignore.Firstly，the influence of atmospheric radiation transfer on the up-welling radiance and down-welling irradiance of the tower-based platform is analyzed，and the atmospheric correction method of based on upward and downward transmittance is established，that is，the influence of the upwelling radiance and down-welling irradiance is corrected by the direct transmittance and the total transmittance.Secondly，using the simulation data of MODTRAN model，the influence of AOD550 and radiative transfer path length on atmospheric transmittance is quantitatively analyzed，and the LUT of AOD550 is established based on the ratio of down-welling irradiance of near-infrared and red bands and solar zenith angle，as well as the upward and downward atmospheric transmittance LUT based on the AOD550 and the radiative transfer path length.Finally，using the canopy spectral data of different growth stages observed by the tower-based platform，the difference of the apparent reflectance between the inside and outside of the O₂-A band absorption line before and after atmospheric correction was analyzed.The results show that the atmospheric correction method based on LUT of AOD550 and radiative transfer path length proposed in this paper can better correct the influence of upwelling radiance and down-welling on the O₂-A absorption band of the tower-based platform，and provides important method support for applications such as SIF observation on the tower platform.     

A Breakpoints based Spatio-temporal Analysis of Tibetan Plateau Vegetation

Due to the fragile ecosystem and unique geographical environment on the TP，the vegetation strongly responds to climatic shifts.Therefore，it is of great significance to discuss the spatiotemporal trend shift of vegetation，to evaluate the climate change of the plateau and to predict regional ecological development.Using the GIMMS NDVI3g dataset from 1982 to 2012 to extract the NDVI information of the TP，as well as establishing seasonal trend model to classify research through the seasonal trend analysis and breakpoints detection method，reveals the spatiotemporal pattern of the trend shifts of plateau vegetation at both ends of the breakpoints combining the classification of land cover.The results shows that conclusions.(1) The seasonal trend model can effectively identify the breakpoints of vegetation time series，moreover the time span of the breakpoints were large and the spatial heterogeneity were strong.(2) The trend of vegetation degeneration in the western part of the Tibetan Plateau was small，vegetation degeneration in the south and northeast regions was obvious，and vegetation in the central and eastern regions has improved.58.93% of the vegetation status tends to be stable.The area where the vegetation status changes significantly accounts for about 32.3% of the entire plateau.(3) In the area where the vegetation status is generally or significantly changed，the vegetation improvement of monotonous trend and interruption trend were more than that of degradation，and the degenerative situation in the reverse trend were more than the improvement.Monotonous trend changed in 3.14% of the regions，58.36% of the regions occurred interruption trend changes，and 38.50% of regions occurred reverse trends.The time distribution of the monotonous trend and the interruption trend were more concentrated，while the reverse trend covered the entire time series.(4) The vegetation improvement and degradation in different land cover types were various conditions.The type with the highest rate of improvement was desert(53.30%)，and the type with the highest rate of degradation was sparse vegetation(60.14%).Overall，the vegetation in Tibetan plateau tends to be greening，but the spatial heterogeneity remains significant.     

Reduction of high-order discrete-time systems

A combination of bilinear transformation, the Routh stability criterion and the integral squared error (ISE) criterion is proposed for the linear model reduction of high-order discrete-time systems. The approach consists of a four-step computational scheme. In the first three steps, by the use of the bilinear transformation and Routh approximation methods, the denominator of the reduced model is obtained. In the fourth step, a recursive algorithm is used to minimize the variance of the spectral density between the original and the reduced model to obtain optimal coefficients for the numerator of the reduced model.     

基于模拟退火算法的植被参数遥感反演

提出了基于模拟退火( SA, Simulated Annealing ) 算法的植被参数( 叶面积指数和叶绿素含量) 反演方案。该方案以冠层反射率模型( SAIL, Scat tering by Arbit rarily Inclined Leav es) 作为正向模型, 分别以Bo ltzman 模拟退火( BSA , Bolt zman Simulated Annealing) 、快速模拟退火( FSA,Fast Simulated Annealing ) 、极快速模拟再退火( VFSA, Very Fast Simulated Anneal ing ) 算法为优化方法, 并采用模型输出的光谱反射率和观测的光谱反射率的残差平方和作为目标函数。模拟反演结果表明: ①模拟退火算法能够跳出局部最优, 得到全局最优解; ②极快速模拟再退火算法在时间效率和反演精度上都优于Bo ltzman 模拟退火和快速模拟退火;③ 在给定的光谱数据没有误差的情况下, 利用模拟退火算法反演SAIL 模型, 能够得到高精度的叶面积指数和叶绿素含量。     

基于偏最小二乘的土壤重金属铜含量高光谱估算

为探究高光谱数据估算土壤重金属铜含量的可行性,以石家庄市水源保护区褐土为研究对象,对不同光谱变换数据与重金属铜含量做了相关分析,建立了土壤重金属铜的单光谱变换指标偏最小二乘模型和多光谱变换指标偏最小二乘模型。结果表明：光谱反射率（R）经倒数一阶微分（RTFD）变换后与铜含量的相关性有所提高;光谱敏感波段为418、427、435、446、490、673、1 909、1 920和2 221 nm,基本位于土壤氧化铁、粘土矿物的特征吸收区域;对土壤重金属铜含量估算效果最好的单光谱变换指标偏最小二乘模型为RTFD模型,其模型决定系数（R²）为0.649,均方根误差（RMSE）为1.477;多光谱变换指标偏最小二乘模型R²和RMSE分别为0.751和1.162,建模效果优于单光谱变换指标模型。研究结果可为北方地区褐土类型土壤重金属铜的高光谱估算提供借鉴。     

Radarsat-2/SAR和MODIS数据联合反演黄土高原地区植被覆盖下土壤水分研究

以黄土高原半干旱区定西为试验区,利用Radarsat-2/SAR和MODIS数据,将由MODIS NDVI估算的植被含水量(VWC)应用到微波散射Water-Cloud模型中校正植被的影响。采用交叉极化(VV/VH)组合方案对植被覆盖下土壤水分的反演进行初步探讨,结果表明:在植被影响校正前,模型反演土壤水分值出现明显低估现象;校正植被影响后,相关系数R由0.13提高到0.44,且通过α=0.01的显著性检验,标准差SD由5.02降低到4.30,有效提高了模型反演土壤水分的准确度。卫星反演的研究区土壤含水量大部分介于10%~30%之间,与实地考察情况一致,较好地反映出区域土壤湿度分布信息。表明,光学和微波协同遥感反演对于提高农田土壤水分遥感反演精度具有较大的应用潜力。     

在水分胁迫下棉花冠层叶片全氮含量的高光谱遥感估算模型研究

研究利用美国产ASD地物光谱仪,获取新疆北部地区棉花冠层关键生育时期的高光谱数据,采用红边积分面积变量估测棉花冠层叶片的全氮含量,对反射光谱进行一阶微分,应用一阶微分光谱数据,衍生出基于光谱位置变量的分析方法,以红边积分面积(SDr)为自变量,冠层全氮(TN)含量为因变量,做相关分析与处理,构建新陆早6号红边积分面积与冠层叶片TN含量的相关数学模型。研究在不同水处理条件下,对棉花冠层单叶叶绿素含量和单叶全氮含量做相关分析,结果表明:叶绿素含量与TN含量呈显著的正相关(R=0.8723,n=39),叶绿素含量能有效的估计棉花单叶TN含量;红边积分面积变量与冠层TN含量呈显著的相关性,相关系数是0.7394(n=40),利用构建的相关模型可以较为精确地估测棉花两个品种新陆早6号与8号冠层叶片的全氮含量,RMSE分别为0.3859和0.4272。研究认为红边积分面积变量具有预测棉花冠层全氮含量的应用潜力,研究得出利用3边面积变量构造的数学模型对反演作物冠层TN含量有较高应用价值。研究认为,红边位移现象结合红边幅度的变化的研究,用于诊断棉花水分胁迫也是可行的,关键是建立相应合理的诊断指标体系。研究结果证明:①随着棉花的生长发育,叶片的生理生化参数发生变化,冠层的生理生化参数随之发生变化;②.棉花叶片叶绿素含量与叶片的全氮含量相关性显著(R=0.8723,n=38),通过建立数学模型,可以估测叶片中全氮的含量;③由一阶微分光谱衍生出基于光谱“红边”位置变量的分析方法,使我们认识到“红边”的变幅、形状和面积包含了各个波段的信息,这些波段综合产生的变量所构造的模型,为棉花氮素营养参数的估计提供了预测能力;④如果棉花叶绿素含量高,说明水分充足、氮代谢旺盛,植株处于生长旺盛时期,红边向蓝光方向发生了位移。利用红边位移现象结合红边幅度的变化的研究,用于诊断棉花水分胁迫也是可行的,关键是建立相应合理的诊断指标体系。     

基于Landsat8的地表温度反演算法研究——以滇池流域为例

2013年2月11日Landsat 8在加州范德堡空军基地发射升空,其携带的热红外传感器为反演地表温度提供了一种新的数据,但目前尚没有针对Landsat 8热红外波段反演地表温度的算法。针对Landsat 8第10波段特征,对现有反演地表温度的单窗算法进行了参数修正,得到了用Landsat 8第10波段反演地表温度的单窗算法系数。为了评价修正后算法的精度,用MODTRAN模拟地表温度为20、30和40℃时大气水汽含量分别为1.0、1.5、2.0和2.5g·cm-2传感器高度处的热辐射值,再将模拟数据用修正后的单窗算法反演地表温度,结果表明:地表温度越低、大气水汽含量越低,误差越小;模拟结果的平均误差为0.74℃。说明基于Landsat 8第10波段用修正后的单窗算法反演地表温度是可行的,该方法可为地表温度反演提供一种途径。最后以滇池流域为例,基于2013年4月20日的Landsat 8热红外数据反演了滇池流域的地表温度,并分析了滇池流域地表温度的分布特征。     

Optimizing spectral indices and chemometric analysis of leaf chemical properties using radiative transfer modeling

We used synthetic reflectance spectra generated by a radiative transfer model, PROSPECT-5, to develop statistical relationships between leaf optical and chemical properties, which were applied to experimental data without any readjustment. Four distinct synthetic datasets were tested: two unrealistic, uniform distributions and two normal distributions based on statistical properties drawn from a comprehensive experimental database. Two methods used in remote sensing to retrieve vegetation chemical composition, spectral indices and Partial Least Squares (PLS) regression, were trained both on the synthetic and experimental datasets, and validated against observations. Results are compared to a cross-validation process and model inversion applied to the same observations. They show that synthetic datasets based on normal distributions of actual leaf chemical and structural properties can be used to optimize remotely sensed spectral indices or other retrieval methods for analysis of leaf chemical constituents. This study concludes with the definition of several polynomial relationships to retrieve leaf chlorophyll content, carotenoid content, equivalent water thickness and leaf mass per area using spectral indices, derived from synthetic data and validated on a large variety of leaf types. The straightforward method described here brings the possibility to apply or adapt statistical relationships to any type of leaf.     

Data Assimilation Experiment ofPoor Quality of RemoteSensing Image in Critical Phenology

In the process of data assimilation，influenced by the water vapor and cloud cover in the study area，the qualities of remote sensing images are poor in the key crop phenological phases.This will cause not to get the perfect remote sensing images for a long time.So we try to solve this problem by using an improved EnKF method to assimilate the WOFOST crop growth model and the terrible quality of remote sensing images to forecast the maize’s yield in the Red Star Farm in Heilongjiang province.In order to improve the accuracy of simulated time series curve of the LAI and yield production results，the consideration on quality evaluation of the remote sensing images is introduced by using expansion coefficient and adjustable factor.The results shows based on the improved EnKF method，time series curve of the LAI keeps a normal tendency of LAI rather than negative fluctuations，and it also avoids the serrated fluctuation to a certain extent.In addition，compared with the original EnKF method，in the field level R2 can increased to 0.67 from 0.59，RMSE is reduced to 92.23 kg/hm2 from 240.57 kg/hm2 and in the farm level R2 can increased to 0.61 from 0.52，RMSE is reduced to 122.44 kg/hm2 from 310.94 kg/hm2 between simulated yield and measured yield.     

GA-PLS方法提取土壤水盐光谱特征的精度分析

光谱定量遥感已成为土壤盐渍化大尺度调查的有效手段之一,但黄河三角洲地区盐渍化土壤的光谱响应特征尚未明确。以黄河三角洲野外测定土壤体积含水率、电导率为例,应用遗传偏最小二乘法(GA-PLS)在小样本集条件下提取盐渍土壤的水分-盐分的光谱响应特征,利用蒙特卡罗方法随机模拟结果表明:在不同土壤水盐含量条件下,GA-PLS方法所提取的光谱特征具有鲁棒性,含水率模型稳定在23个波段变量,即响应特征为365~425,500~515,720~740,755~765与955~965 nm;土壤电导率模型的特征集数目为20个波段变量,特征为370~385,405~425\,500~535,650~660,755~760与1 030~1 050 nm。实验在不同预处理模型下,GA-PLS算法所建立水盐光谱模型较PLSR模型均显示出更高的精度。其中,包络线预处理方法与GA-PLS算法相结合效果最优,其水分光谱模型测试集拟合精度(R²),预测残差平方和(PRSS)与残差预测方差(RPD)分别为0.88,9.36与15.80;土壤光谱模型测试集精度R²,PRSS与RPD分别为0.71,15.68与13.76。     

改进NSCT和IHS变换相结合的遥感影像融合

目的 目的为了增强多光谱和全色影像融合质量,提出基于脉冲耦合神经网络（PCNN）的非下采样Contoulet变换（NSCT）和IHS变换相结合的融合方法。方法 先对多光谱图像进行IHS变换提取亮度I分量,采用主成分分析增强I分量得到新的I⁺分量;然后通过NSCT变换分别对I⁺分量和全色图像进行分解,并采用边缘梯度信息激励的PCNN得到融合图像的低频和高频分量;最后进行NSCT逆变换、IHS逆变换得到融合图像。结果 利用资源一号02C卫星数据进行实验,结果表明该算法在保留光谱信息的同时提高了图像空间分辨率,获得了较好的融合效果。结论 结合NSCT和IHS变换的融合方法在视觉效果和客观评价指标上都优于常用的图像融合方法。     

New Approach on Robust Delay-Dependent ${H}_infty$ Control for Uncertain T--S Fuzzy Systems With Interval Time-Varying Delay

This paper investigates the robust ${H}_{infty }$ control for Takagi--Sugeno (T--S) fuzzy systems with interval time-varying delay. By employing a new and tighter integral inequality and constructing an appropriate type of Lyapunov functional, delay-dependent stability criteria are derived for the control problem. Because neither any model transformation nor free weighting matrices are employed in our theoretical derivation, the developed stability criteria significantly improve and simplify the existing stability conditions. Also, the maximum allowable upper delay bound and controller feedback gains can be obtained simultaneously from the developed approach by solving a constrained convex optimization problem. Numerical examples are given to demonstrate the effectiveness of the proposed methods.      

The potential for estimating chlorophyll content from a vegetation canopy using the Medium Resolution Imaging Spectrometer (MERIS)

In 2000, the European Space Agency aims to launch the Envisat-1 satellite platform which will carry the Medium Resolution Imaging Spectrometer (MERIS), an advanced optical sensor designed to acquire Earth observation data at regional to global scales. Of particular relevance to terrestrial ecosystems functioning, the MERIS offers the potential to estimate the spectral location of the maximum slope, termed the red edge position (REP), which marks the boundary between chlorophyll absorption in the red wavelengths and the high infrared reflectance due to leaf internal scattering. However, although a first derivative transformation of the reflectance spectra will highlight the maximum slope position, the accurate location of the REP is limited by the spectral sampling resolution of the sensor. A theoretical analysis, using a combined leaf-canopy radiative transfer model, demonstrates that the MERIS, having five coarsely spaced wavebands in the region of the REP, can be utilized for monitoring spectral shifts of the REP, resulting from variation in leaf chlorophyll content or leaf area index.