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Construction Of Remote Sensing Inversion Models For Estimating Grassland Biomass In The Aletai Region

Posted on:2014-02-04Degree:MasterType:Thesis
Country:ChinaCandidate:X Q ZhangFull Text:PDF
GTID:2233330401453693Subject:Agricultural extension
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Because of the special geographical location and the environmental condition, there are main fourpillar industries in Aletai region. They are animal husbandry、mining、tourism and aquaculture. In themeanwhile, this region is one of the most important animal husbandry base in Xinjiang, and it has goodresources and geographical advantages. So obtain the distribution of typical grassland biomass efficiently isthe key to develop the grassland resource of Aletai region. Therefore the research of estimation of typicalgrassland biomass in Aletai region has the vital significance.This article uses the environment disaster mitigation satellite (HJ-1A/B) remote sensing data, and the88sampling points of grassland biomass data from Aletai region in July and August2012.Analysis thecorrelation between remote sensing vegetation index and the grassland biomass,.Establishes estimationmodel of the typical grassland biomass and provide a effective way to estimate and dynamic monitorlarge-area grassland. conclusion is as follows:1. Through linear and quadratic polynomial correlation analysis, there is a significant positivecorrelation between NDVI、RVI and the grassland biomass. Meanwhile, the vegetation index increasedalong with the increase of grassland biomass, including the RVI has the most significant correlation withgrassland biomass, the highest correlation coefficient of0.911.2. During so many estimated models which based on remote sensing vegetation index and the biomassdata, RVI-quadratic polynomial regression model is the most suitable for the inversion of the grasslandbiomass, and the R~2is0.83.3. Compared the precision of inversion results validation of6estimation models based on the NDVIand RVI, and the estimation accuracy reached74%、73%、60%、66%、80%、85%.4. The trend line of the HJ-1A/B vegetation index and the grassland biomass can reflect the spatialdistribution of typical grassland. It indicate that the regression model based on vegetation index can reflectthe typical grassland biomass of Aletai Region, and could meet the actual production need.
Keywords/Search Tags:HJ-1A/B, remote sensing inversion, Quadratic polynomial, Estimation accuracy
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