Research On Temperature-Vegetation Drought Index Model Using AMSR-E Spaceborne Passive Microwave Remote Sensing Data

Drought is a water shortage caused by an imbalance between regional water supply and demand.It is an incredibly complex natural disaster.The global annual average economic losses because of drought are up to the US $ 6-8 billion.Globally,more than half of areas are affected by drought.Therefore,it is important to make full use of existing science and technology to monitor the drought,so as to minimize its harm.The traditional monitoring methods are difficult to accurately reflect the drought conditions due to the limited coverage of ground stations,and the monitoring cost is continuously raising due to the labor cost,which cannot meet the requirements to real-time monitoring drought of large areas.Remote sensing technology has the advantages of wide coverage,high spatial resolution,short revisit cycle,convenient data acquisition,and objective data,which can overcome the shortcomings of the conventional drought monitoring methods and is suitable for timely large-scale drought monitoring.At present,remote sensing drought monitoring methods mainly include Palmer Drought Severity Index(PDSI)?Thermal inertia model?Normalized Difference Vegetation Index(NDVI)?Crop Water Stress Index(CWSI)?Vegetation Condition Index(VCI)?Temperature Condition Index(TCI)?Vegetation Health Index(VHI)?Vegetation Supply Water Index,(VSWI)and Temperature Vegetation Drought Index(TVDI)etc.However,these methods,based on visible/infrared bands,might be significantly influenced by water vapor in clouds and atmosphere,and rainfall.Passive microwave remote sensing,which is less affected by weather and vegetation,can penetrate thin cloud and sparse vegetation,and efficiently overcome shortages of visible and thermal infrared remote sensing.TVDI,as a widely recognized drought index,can take into account both temperature and vegetation in drought monitoring,and can effectively avoid the shortcomings caused by the single factor.Therefore,combined with passive microwave remote sensing and TVDI to build a new passive microwave temperature-vegetation drought index(Microwave Temperature Vegetation Drought Index,MTVDI)has a very high feasibility.In this paper,regarding Chinese inland areas as the study area,we used the AMSR-E(The Advanced Microwave Scanning Radiometer-Earth Observing System)passive microwave remote sensing data.On the basis of improving temperature inversion model and vegetation index,the passive microwave temperature-vegetation drought index model was constructed for the first time,and the monitoring of drought in China was carried out.The main contents are as follows.1.Two empirical models of surface temperature inversion were constructed.Based on MODIS LST(Land Surface Temperature)surface temperature products as the ground surface measurements,a surface temperature inversion method based on AMSR-E was studied,and two different surface temperature inversion models were established: 1)In the central and southern regions of China,a four-variable AMSR-E passive remote sensing surface temperature inversion empirical model for regional humidity differentials was created,and about 80% of the regional inversion error <2.5K.2)A nonlinear empirical model of surface temperature inversion based on AMSR-E 18.7GHz(H),23.8GHz and 89.0GHz(V)has established in China,and the root means square error of the model is 6.492 K.2.The Microwave Temperature-Vegetation Drought Index(MTVDI)model was constructed.Firstly,based on the MODIS NDVI product,the relationship between Microwave Polarization Difference Index(MPDI)and NDVI was built to establish the Microwave Normalized Difference Vegetation Index(MNDVI)model.Then,on the basis of MNDVI model and nonlinear surface temperature inversion model,the dry edge and wet edge equations were constructed respectively,and the Microwave Temperature-Vegetation Drought Index(MTVDI)model was established.Finally,a classification mechanism was used to simulate and monitor the spatiotemporal change of drought in the study area from 2003 to 2010.3.The microwave temperature-vegetation drought index model was validated by rainfall and wetness index(ratio of rainfall to potential evapotranspiration,P/PET).Firstly,except for the Microwave Temperature-Vegetation Drought Index(MTVDI)model,we constructed MODIS Temperature-Vegetation Drought Index(TVDI),improved Temperature-Vegetation Drought Index(iTVDI)using the Ts-Tair(the land surface temperature minus air temperature)replace the Ts(land surface temperature),improved Microwave Temperature-Vegetation Drought Index(Imp-MTVDI)using the Ts-Tair(the land surface temperature minus air temperature)replace the Ts,and Nonlinear Microwave Temperature-Vegetation Drought Index(NonL-MTVDI)using nonlinear equation to fitting the dry and wet edge,respectively.Then,the five models were validated by precipitation and wetness index(P/PET).The results show that MTVDI,Imp-MTVDI and NonL-MTVDI have some advantages in the central and eastern regions of China compared with MODIS TVDI and iTVDI.But on the contrary,MTVDI,Imp-MTVDI and Non L-MTVDI in the Xinjiang,Gansu,Inner Mongolia,and Qinghai,which located in northwest China,showed weak correlation,while MODIS TVDI and iTVDI were relatively correlated,indicating that MODIS TVDI and iTVDI are more advantageous for drought monitoring in northwest China.In general,MTVDI is the best model for long-term and large-scale spatial scale drought monitoring.