基于MODIS数据的草地生物量估算模型比较  

Comparison of grassland biomass estimation models based on MODIS data

作　　者：渠翠平[1,2] 关德新[1] 王安志[1] 金昌杰[1] 倪攀[1,2] 袁凤辉[1,2] 张晓静[1,2] 

机构地区：[1]中国科学院沈阳应用生态研究所,沈阳110016 [2]中国科学院研究生院,北京100039

出　　处：《生态学杂志》2008年第11期2028-2032,共5页Chinese Journal of Ecology

基　　金：国家科技支撑项目(2006BAC01A12);国家自然科学基金资助项目(40875069)

摘　　要：准确估算草地生物量对合理规划区域畜牧业、评估草地植被的生态效益有重要意义。目前,在常用的遥感估算模型中,采用的植被指数和模型函数形式多样。本文根据野外生物量调查结果和MODIS数据,分别采用归一化植被指数(NDVI)、增强植被指数(EVI)和修正的土壤调节植被指数(MSAVI)建立了内蒙古科尔沁左翼后旗草地地上生物量和地上地下总生物量估测的3种(线性、乘幂和指数)模型,并进行了比较。结果表明:3种模型能够对草地生物量进行较好的模拟,其中指数模型效果最佳;3个植被指数(NDVI,EVI和MSAVI)与草地生物量均有较高的相关性,可用于该草地产量估测,其中MSAVI对地上生物量拟合效果最好(R2=0.900);NDVI和EVI的线性模型对总生物量的模拟明显好于对地上生物量的模拟。TO accurately estimate grassland biomass is of significance for the reasonable management of regional stock-raising and the evaluation of ecological benefit. Various vegetation indices and regression functions have been used in estimating grassland biomass by remote sensing data. Based on the field Survey and MODIS data, and adopting the significant remote sensing-based vegetation indices including Normalized Difference Vegetation Index （NDVI） , Enhanced Vegetation Index （EVI） and Modified Soil Adjusted Vegetation Index （MSAVI）, three regression models （linear, power, and exponential functions） for each paired grassland biomass and vegetation index in Keerqinzuoyihou County, Inner Mongolia were established and compared. The results showed that grassland biomass could be well simulated by linear, power, and exponential functions, and exponential function performed best. Three vegetation indices （NDVI, EVI and MSAVI） had significant positive correlation with grassland biomass, and were suitable for the successful quantification of grassland biomass based on MODIS. MSAVI functioned most efficient with above-ground biomass （R^2 = 0. 900） , and the simulation of total biomass was more effective than that of above-ground grassland biomass by using linear function with NDVI and EVI.

关 键 词：MODIS 植被指数 草地 生物量 遥感模型 科尔沁左翼后旗 

分 类 号：S812[农业科学—草业科学]