10 September 2008 Study on models for monitoring of aboveground biomass about Bayinbuluke grassland assisted by remote sensing
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Using the CBERS data in August,2005 and the corresponding measured grass yield data from 15 samples in the region of Bayinbuluke grassland, we established the monadic linear regression models the non-linear regression models and the logarithm models to express the relationship between grassland aboveground biomass and the Vegetation Index(VI). The results showed that: 1)there were close relation between the VI and grassland aboveground biomass: 2) the comparison of different forms showed that the logarithm equation was the best one in terms of the suitability of use in study area: 3) the results from the non-linear regression analysis showed that the order was MSAVI NDVI LAI and SAVI in terms of the fitting accuracy between these VI and grassland aboveground biomass data: 4) the non-linear regression Y=-1242.2MSAVI3+6254.1MSAVI2-10044MSAVI+5267 was the best model which could be used in monitoring grassland biomass based on the VI Bayinbuluke grassland.5) the calculated results were as follows: the total aboveground biomass of Bayinbuluke in 2005 was 1.23x104t; the total biomass of high grass was 8.82×103t and the density was 116.14g/m2;the total biomass of low grass was 2.04x103t and the density was 70.33g/m2 the total biomass of swampland was 1.30x103t and the density was 122.36g/m2 Keywords Remote Sensing, vegetation index(VI), grassland, aboveground biomass, Bayinbuluke
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Anming Bao, Anming Bao, Xiaoming Cao, Xiaoming Cao, Xi Chen, Xi Chen, Yun Xia, Yun Xia, } "Study on models for monitoring of aboveground biomass about Bayinbuluke grassland assisted by remote sensing", Proc. SPIE 7083, Remote Sensing and Modeling of Ecosystems for Sustainability V, 70830R (10 September 2008); doi: 10.1117/12.791724; https://doi.org/10.1117/12.791724

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