Research On Remote Sensing Models For Grassland Vegetation Biomass Monitoring In Xilinguole

The remote sensing technique was used to measure biomass in Xilinguole League. The correlation between the vegetation indics and the biomass was analysed. Application range for three types of vegetation indices and biomass monitoring method by remote sensing was discussed. Models based on vegetation index were set up for estimating biomass and dynamically vegetation monitoring in large area. Main results and conclusions from the research are as follows:1. Linear and nonlinear regression relationships show as follows: NDVI has the best correlation to the region of Xilinguole;S regression model is suitable for the region of Xilinguole.2. It can be concluded from the suitable landscape ecological regionalization that:Linear Regression Model are suitable for both meadow steppeand typical steppe;S Regression Model is suitable for desert steppe;Growth Regression Model is suitable for sand grassland.3. The grassland biomasses of meadow steppe, typical steppe, desert steppe and sand grassland have different correlations with three types of vegetation indices,EVI has the best correlation with meadow steppe;NDVI has the best correlation with typical steppe and sand grassland;SAVI has the best correlation with desert steppe。4. By the analysis of estimating errors in 2001 and 2005,the results show that the estimating accuracy of S regression model is 91.6% to the region of Xilinguole in 2001 and that is 87.1% in 2005。Estimating accuracy for the grassland biomass is improved further by dividing the different region for estimating biomass. The estimating accuracy of linear regression model is 97% to meadow steppe. The estimating accuracy of linear regression model is 97% to typical steppe. The estimating accuracy of S regression model is 97% to desert steppe. The estimating accuracy of growth regression model is 98% to sand grassland。5 Vegetation indics and estimating biomass'curve can well reflect the change of the four types of grasslands. This shows that relationship between NDVI and biomass production can be expained well,and the general regression model can meet the need of estimating biomass in Xilinguole。...