塔里木河下游芦苇生物量遥感估算模型研建  

The Construction of the Remote Sensing Estimation Models for Reed Biomass in the Lower Reaches of the Tarim River

作　　者：牛婷[1,2] 李霞[1] 林海军[1] 赵钊[1] 董道瑞[1] 

机构地区：[1]新疆农业大学草业与环境学院,乌鲁木齐830052 [2]新疆水利水电勘察设计研究院,乌鲁木齐830000

出　　处：《国土资源遥感》2011年第4期42-45,共4页Remote Sensing for Land & Resources

基　　金：国家自然科学基金项目(编号:40961027);新疆维吾尔自治区草地资源与生态实验室共同资助

摘　　要：在对塔里木河下游大西海子水库周边芦苇生物量实地调查基础上,使用同期TM数据建立了芦苇生物量遥感估算模型。结果表明:TM1～5、TM7的灰度值和垂直植被指数(PVI)、亮度植被指数(BVI)及归一化差值植被指数(NDVI)与芦苇生物量实测值显著相关;生物量遥感估算模型中非线性回归模型的拟合精度高于线性回归模型。NDVI在一元线性、非线性回归模型中的拟合精度最高,TM4的拟合精度最低;多元逐步回归比一元线性、一元非线性回归拟合度精度高。若仅考虑简单、可靠、便于生产部门使用,基于PVI、NDVI的一元线性模型和基于TM1的一元非线性模型是较好的选择。The remote sensing estimation models for reed biomass were established by using TM data and the field investigation of reed biomass around the Daxihaizi reservoir in the lower reaches of Tarim river.The results show that the gray values of TM1~5 and TM7,the perpendicular vegetation index（PVI）,the brightness vegetation index（BVI） and the normalized difference vegetation index（NDVI）are significantly related to the measured values of Phragmites australis biomass,the fitting precision of the nonlinear regression model is higher than that of the linear regression model,and NDVI has the highest precision in the regression models but TM4 has the lowest precision.The multiple stepwise regression has a higher fitting precision than ordinary regressions.The ordinary linear regressions based on PVI and NDVI and the ordinary nonlinear regression based on TM1 are the best options due to the characteristics of simplicity,reliability and convenience.

关 键 词：生物量 估算模型 塔里木河 遥感 芦苇 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置] X171.4[自动化与计算机技术—控制科学与工程]