| Currently one of the main scientific issues is to understand and quantify the impact of global climate change on the Earth system.One of the challenges is to understand the role of terrestrial ecosystems and the changes they may undergo.In this respect,the leaf water content is of interest,also in view of the water use efficiency of plants.Leaf water content is an important chemical component of plants and a primary limiting factor for plant transpiration.It is a crucial variable involved in many physiological processes and ecosystem patterns.The spatio-temporal variations of vegetation water content are essential for monitoring plant physiological status.But a first step prior to the estimation of vegetation water content at the leaf level via remotely sensed data is the accurate method for retrieval of leaf water content.Optical remote sensing provides an easy and versatile way to accurately estimate water content information using multi-angular reflectance measurements.Due to the presence of water absorption band in near infrared（NIR）and shortwave infrared（SWIR）wavelength range,electromagnetic spectrum will allow us to correctly measure the leaf water content.In the context of the complete analysis of leaf water content,new index is proposed to estimate the leaf water content.As leaves have varied angle orientations and high spatial resolution data can be gathered for a tiny area of a single leaf,we must consider multi-angular reflection of leaves.Specular reflection from a leaf surface is important in influencing the distribution and magnitude of multi-angular reflectance components,but it is completely irrelevant to the leaf’s biochemical features.In the present study multi angular reflectance factor measurement have been used to investigate the relation between leaf equivalent water thickness（EWT）,gravimetric water content（GWC）and plant water concentration（PWC）as a parameter in 350-2,500 nm reflectance spectral range.From a plant garden of Northeast Normal University,Changchun a total of 256 leaf samples were used in this study of ten different plants as calibration dataset,and 683 leaf samples from wide specie were used for validation which include Leaf Optical Properties Experiment 93（LOPEX93）,ANGERS and multi angular dataset it has 330,275 and 78 leaf samples respectively.According to the literature,numerous researchers utilized a variety of indices based on multi angular spectra.To analyze leaf water content we also have taken multi angular reflection measurement with three different forms of hyperspectral indices were evaluated,including the simple ratio（SR）,normalized ratio wavelength（ND）and double difference（datt type of indices）.Because the majority of these indices are based on two or three particular bands for plant species and easy and not that much time consuming in measurement.In the first step relationship between EWT,PWC and GWC with ten different spectral indices were taken into consideration for this study and the datt type of index（R1-R2）/（R1-R3）based on multi angular reflectance measurement performed good.To analyze the performance of the existing indices,five indices for EWT,PWC and GWC have been chosen to check out their relationship with calibration dataset.Only R1300/R1450,(R850-R2218)/(R850-R1928)and(R850R1788)/(R850-R1928)have shown good correlation with EWT.In the calibration dataset mainly two approaches were applied one is linear regression and the other one is nonlinear regression model and we finalize two indices for each indicator i.e.for EWT（linear）is(R1905-R1840)/(R1905-R1875)and for EWT（nonlinear）is(R1845-R1880)/(R1845-R1910).For PWC（linear）index is(R1410-R1590)/(R1410-R1400)and PWC（nonlinear）is(R1435-R1400)/(R143-R1575)while for GWC the linear and nonlinear index is(R1835-R2130)/(R1835-R1860).In the second step the data were analyzed further to find out a new index for the data taken in this study and we come up with the best calculated three bands（R1-R2/R1-R3）type of index.Basically the method which were applied to find out the best indices for three type of indicators i.e.EWT,PWC and GWC,so for each indicator we selected two indices on the basis of linear regression model and nonlinear regression model.All of the indicators exhibits good result in terms of coefficient of determination for EWT R2>0.94 for PWC R2>0.71 while for GWC R2>0.8.We selected the indices for EWT which are(R1905-R1840)/(R1905-R1875)and(R1845-R1880)/(R184-R1910)for linear and nonlinear respectively,by looking at coefficient of determination and root mean square error values as the other researcher follow the same method,all the leaves was measured by multi angular reflection which ranges from-600 to 600 on the Principle plane.The published spectral indices used in this research have a very weak relationship with our calibration dataset except R1300/R1450,(R850-R2218)/(R850-R1928)and(R85-R1788)/(R850R1928).The two indicators i.e.gravimetric water content（GWC）and plant water concertation（PWC）have showed strong correlation with calibration dataset,however the correlation was not that much good as EWT.Furthermore,when the PWC and GWC indices were validated using the LOPEX,ANGERS and multi angular dataset for reliability and its accuracy,only with multi angular database PWC and GWC shown good result because in multi angular dataset only few plant species were different from calibration dataset.As the proposed indices for three indicators after validation from multi angular dataset,we came to know that the indices for EWT give good result having RMSE=0.0043（g/cm2）while PWC has RMSE=0.0061（g/g）and GWC has RMSE=0.0054（g/g）.So we concluded that the indices for EWT performed very well in all three validation dataset which include LOPEX,ANGERS and multi angular dataset.While the other two indicators i.e.PWC and GWC have shown not considerable result except multiangular dataset in terms of RMSE.The performance of the proposed hyperspectral indices for EWT surpassed the performance of other indices in this study.It has been validated by LOPEX,ANGERS and multiangular dataset.Finally,this study showed that this combination of bands（R1-R2）/（R1-R3）could be used for leaf water content estimation in terms of EWT.This indicates that spectral index that proposed in this study(R1905-R1840)/(R1905-R1875)for linear and(R1845-R1880)/(R1845-R1910)for nonlinear can be used and could be more reliable to predict leaf water content（EWT）.When multi-angular spectral reflection is considered in both linear and nonlinear approaches,this study has proposed a generic spectral indices for reliably measuring equivalent water thickness（EWT）.But future studies will need to include more plant species and field data.The newly suggested indices can be used to estimate EWT using a simple laboratory measurements,making them helpful for agricultural,environmental sciences and ecology related studies.The newly suggested indices has the benefit of being able to eliminate the additional noise created by the leaf surface across a large range of species and also accurately estimate EWT for multi-angular measurements. |
