利用ALOS PALSAR双极化数据估测山区森林蓄积量模型  

Estimating forest volume in hilly regions with the ALOS PALSAR model's dual polarization data

作　　者：王晓宁[1] 徐天蜀[1] 李毅[1] 

机构地区：[1]西南林业大学林学院,云南昆明650224

出　　处：《浙江农林大学学报》2012年第5期667-670,共4页Journal of Zhejiang A&F University

基　　金：国家自然科学基金资助项目(30960302)

摘　　要：合成孔径雷达(SAR)技术以其独特的成像机制及其全天候、全天时成像能力,在森林生物量估测方面发挥着越来越重要的作用。利用野外实测数据分析了ALOS PALSAR双极化数据后向散射系数(σH0H,σH0V,σH0V/HH)与云南山区松林蓄积量的关系,并分别构建简单线性、自然指数和加入地理因子的多元回归模型。研究结果表明:极化比值(σH0V/HH)与蓄积量的相关系数(r=-0.407)比任何单极化(σH0H和σH0V分别为0.204和-0.242)都要高,加入地理因子的多元回归模型在森林蓄积量估算中有较好的精度。Synthetic Aperture Radar （SAR）, having a particular imaging mechanism that can acquire data at any time, has become more and more important for estimating forest biomass. In this research, based on field sur- vey data, correlations between ALOS PALSAR dual polarization data backscattering coefficients （σ0HH σ0Hv and σ0v/HH. ） and Yunnan pine forest volume from hilly regions were analyzed. A simple linear model, an exponential model, and a multiple regression model with terrain factors were developed. Results showed that correlation of 0 the polarization ratio （σ0v/H.） to forest volume （r = -0.407） was higher than any single polarization （O＇OH with r = 0.204 and σ0Hv with r = -0.242）. Also, the multiple regression model with terrain factors was with highest ac curacy. [Ch, 3 fig. 2 tab. 12 ref.]

关 键 词：森林测计学 ALOS PALSAR 森林蓄积量 地理因子 

分 类 号：S758.5[农业科学—森林经理学]