Sand invasion is intensified by the serious degradation and disappearance of Nitraria bushes

which has a serious effect on the oasis ecological security of deserts.Quantitative analysis of different multiple scattering factors in mixed spectral contribution for the ecological environment on deserts is particularly important.Timely monitoring of spatial and temporal variations in photosynthetic/non-photosynthetic vegetation（PV/NPV） fraction cover provides essential information for guiding management practices on land desertification and research on vegetation recession mechanism.In this paper

taking the typical vegetation of Nitraria bushes in Minqin County of Gansu Province as an example

mixed and endmember spectra

and fraction information were acquired by ground-controlling spectroscopy experiment.Then

the fractional cover of PV(f

pv

) and that of NPV(f

npv

) were estimated by linear and nonlinear spectral mixture models（NSMM）（including Kernel NSMM（KNSMM） and bilinear spectral mixture model（BSMM））

respectively.Fully constrained least square method was adopted to mix the models

and the fraction of every endmember and the accuracy information of all the samples were calculated.The performances of the models were compared based on root mean square error（RMSE） of the unmixing model and accuracy of field validation

and the endmember fraction of field validation is based on the abundance of digital image classification by the neural network classification algorithm.Results show that（1） compared with the traditional three-endmember model（PV

NPV

and bare soil（BS））

the four-endmember model

which incorporates an additional shadow endmember

can effectively improve both the accuracy of spectral mixture model（RMSE decreased from 0.0429 to 0.0052 and improved 16%in accuracy） and the estimation precision of f

pv

and f

npv

（increased by 44%and 83%

respectively）.（2）Moreover

the precision of the unmixing of model could be improved by BSMM considering the multiple scattering between NPV and BS endmembers.However

the improved precision was insignificant.Also

considering the nonlinear parameters

the performance of KNSMM was slightly lower than that of the LSMM model.（3） The validation RMSE of f

pv

was 0.1177（R

2

=0.7049）

and that of f

npv

was0.0835（R

<

sup

>

2=0.4896） with LSMM based on PV/NPV

BS

and shadow endmembers.Process monitoring describes the multiple photon-scattering effect among PV/NPV

BS

and shadows in Nitrariabushes.The selection and application of the types of NSMMs should be confirmed according to specific research object and the required precision.Shadows cannot be ignored in estimating vegetation fractional cover

especially in improving f

npv

accuracy.This finding illustrates that the types and number of endmembers chosen are significant in improving the accuracy of fraction estimation.The conclusion also shows that LSMM is suitable to estimate f

pv

and f

npv

of Nitraria bushes accurately based on PV/NPV

BS

and shadow endmembers.