Analysis Of Precipitation And Vegetation Change In Qinba Mountainous Area Based On Satellite Remote Sensing Data

The precipitation data with high spatial and temporal resolution play an important role in the application of meteorology,ecology and hydrology.The main use of precipitation data in meteorological research can be divided into two types:ground meteorological stations observation data;satellite remote sensing products.A large number of studies have shown that the data measured by traditional surface meteorological stations are single point data,which can not effectively reflect the spatial variation characteristics of precipitation,especially in some areas with complex terrain.But satellite remote sensing products is restricted by terrain is smaller,and can generate relatively accurate spatial raster data.Satellite remote sensing products have been widely used in previous studies.However,in the application process,the spatial resolution of these products is slightly rough,and the data accuracy is relatively low.Therefore,it is of great importance to study the downscaling method of satellite remote sensing products and apply the remote sensing precipitation data with high spatial resolution obtained after downscaling to other related applications.In order to obtain high resolution TRMM data from Qinling-Daba Mountains.Based on TRMM 3B43 precipitation data and MODIS NDVI vegetation data in the past 16 years,and combined with geographic weighted regression model(GWR),Qinling-Daba Mountains region was used as the object of study in this paper.The precipitation data with high spatial resolution were obtained by statistical downscaling method.The results show as follows:(1)There is a good consistency between TRMM precipitation data and meteorological stations' measured precipitation in annual,seasonal and monthly time scales.Correlation coefficient is generally over 0.80,relative deviation and root mean square error are also good.TRMM 3B43 data has good practicability in Qinling-Daba Mountains;(2)In the past16 years,the annual NDVI trend in the Qinba mountain is mainly positive change,and the ndvi and precipitation in the Qinba mountains are correlated with each other at the annual,seasonal and monthly scales,and the response of NDVI to TRMM3b43 precipitation data has a hysteresis,which is about 1-2 months;(3)The 1km high-resolution TRMM 3B43 precipitation data obtained from the GWR model on the annual and monthly scale showed good results in general,and verified by correlation coefficient,relative bias and root mean square error.Overall,the GWR model shows precipitation in Qinling-Daba Mountains from south to north graduallydecreased,compared with the original TRMM data,GWR downscaling results overall low,but on average for many years,the latter is better than the former(the correlation coefficient was 0.92,by 0.001 reliability test).Therefore,using the GWR model to carry out the downscaling study of the TRMM 3B43 precipitation data in Qinling-Daba Mountains has certain credibility;(4)Based on the 1km high-resolution TRMM 3B43 precipitation data obtained by downscaling GWR model,the drought and flood situation in Qinling-Daba Mountains was monitored by combining the traditional drought index and precipitation anomaly percentage.The results show that the 1km high resolution TRMM 3B43 precipitation data can better reflect the drought and flood distribution in the Qinling-Daba Mountains in winter.It can reflect more details of drought and flood distribution,which can not be displayed by meteorological station data.The percentage of precipitation calculated by 1km high-resolution TRMM 3B43 data is more detailed and specific for the distribution of dry and wet conditions in Qinling-Daba Mountains.