%0 Journal Article
%T Study on Pertinence between the RS Vegetation Indexes and Aboveground Biomass of Baihe Pasture of Zoige County
若尔盖白河牧场地上生物量与遥感植被指数关系研究
%A Wen Meiji
%A Jia Guanglin
%A Song Jingyuan
%A Xie Caixiang
%A Liu Meizi
%A Zheng Sihao
%A Xin Tianyi
%A
温美佳
%A 贾光林
%A 宋经元
%A 谢彩香
%A 刘美子
%A 郑司浩
%A 辛天怡
%J 世界科学技术-中医药现代化
%D 2012
%I
%X To study the aboveground biomass using remote sensing (RS) on the grassland, and serve better for the protection area, the TM images technology was used to research the relationship between aboveground biomass and RS Vegetation Indexes of Baihe Pasture of Zoige County. The linear and 6 nonlinear (Logarithmic, Inverse functions, Quadratic polynomial, Cubic polynomial, Composite and Power function) regression models were established respectively to estimate the pertinence between 7 vegetation indexes (NDVI, RVI, DVI, SAVI, MSAVI, PVI, GVI) and aboveground biomass. Results indicated that, the cubic polynomial regression model was the best model for the 7 vegetation indexes, followed by the quadratic polynomial model, inverse function curve model, logarithmic curve model, linear model, power function curve model and composite curve model. The cubic polynomial model based on MSAVI-aboveground biomass was the best model, the multiple correlation coefficient R2, average error, rating precision was 0.823005, 38.7%, 61.3% respectively. This model was able to meet the mesoscale estimates of the aboveground biomass.
%K TM image
%K regression model
%K vegetation index
%K Aboveground biomass
TM影像
%K 回归模型
%K 植被指数
%K 地上生物量
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=A9DB1C13C87CE289EA38239A9433C9DC&cid=B5F35A1FC27C1FF7&jid=44257A35316DB0727BA6BC707B9EDAAB&aid=790A9358A1C1D655452533C45CFA3DDE&yid=99E9153A83D4CB11&vid=F3583C8E78166B9E&iid=CA4FD0336C81A37A&sid=53A4507B400B4E65&eid=1805714CB338690A&journal_id=1674-3849&journal_name=世界科学技术-中医药现代化&referenced_num=0&reference_num=0