Vegetation Properties Retrieval From Multi-frequency And Multi-angular Passive Microwave Data

Monitoring global vegetation dynamics is of great importance for many environmental applications.The vegetation optical depth(VOD),derived from passive microwave observation,is related to the water content in all above ground vegetation and could serve as corresponding information to optical observations for global vegetation monitoring.The Microwave Vegetation Index(MVI),which is originally derived from the zero-order model,is a potential approach to derive VOD and vegetation water content,kg/m2(VWC),however,it has limited application at dense vegetation in the global scale.In this study,we preferred to use a more complex vegetation model,Tor Vergata model,which takes multi scattering effects inside the vegetation and between the vegetation and soil layer into account.Validation with ground-based measurements proved this model is an efficient tool to describe the microwave emissions of corn and wheat.The MVI has been derived through two methods:(i)polarization independent((?)and(ii)time invariant((?),based on model simulation.First,multi-angle MVIs was calculated at L band.MVI computed using two adjacent angles of L band is less influenced by partial penetrating through the canopy and this can improve the MVI results.Results show that the MVI_B~T has a stronger sensitivity to vegetation grow changes than MVI_B~P.In fact,for vegetation with a preferred orientation structure such as corn,the no polarization dependence assumption is not reasonable.MVI_B~T is used to retrieve VOD and VWC,and results were compared to physical VOD and measured VWC.Comparisons indicated that MVI_B~T has a great potential to retrieve VOD and VWC.By using L band time-series information,the performance of MVIs could be enhanced and its application in global scale could be improved while paying attention to vegetation structure and saturation effects.Second,multi-frequency MVIs was calculated at different frequencies(S and L bands as two low frequencies and C and X bands as two high frequencies).MVI_B~P(SL),MVI_B~P(CX),MVI_B~T(SL)and MVI_B~T(CX)were used to calculate vegetation attenuation and results were compared to physical VOD and measured VWC for wheat.Investigation of MVIs protentional in vegetation properties retrieval indicated while lower frequency pair(L and S bands)was used to derive MVI,it has more ability to derive vegetation properties compare to higher frequency pair(C and X).Furthermore,the second method of MVI derivation((?))had better performance in vegetation properties retrieval than the first method((?)).In fact,while lower frequencies were used to derive MVI_B~T reliable correlation were found in higher vegetation canopy.The same method has been done for corn,but considering the height and structure of corn,multi-frequency MVI worked well until corn canopy was short.Third,since the optical depth and scattering albedo are two principal vegetation parameters and calculating them by the theoretical function are difficult,here we tried to calculate effective parameters based on fitting a high order model to the zero-order model to recognize the ability of this way in dense crop likes corn and wheat.By this way,no auxiliary data need to retrieve them.In this study,we named them equivalent vegetation optical depth(EVOD)and equivalent scattering albedo(ESA).To validate EVOD and ESA,theoretical optical depth(VODs)and scattering albedo(SAs)were used.Considering the equivalent results of wheat suggested they were polarization,incident angle,and frequency dependent.Generally,by increasing density,EVOD increased and its value at a higher incident angle was more than lower incident angle.Comparison of EVOD with VODs value at 10°incident angle indicated EVOD has a consistent correlation with VODs but overestimated.Applying this method in real satellite scale and comparison to VOD products should be investigated in the future work.