基于ENVISAT ASAR数据的高山松林蓄积量估测模型研究  

Study on the Volume Estimation Model of Pinus Densata Forest Based on ENVISAT ASAR Data

作　　者：李毅[1] 徐天蜀[1] 王晓宁[1] 

机构地区：[1]西南林业大学林学院,昆明650224

出　　处：《中南林业调查规划》2012年第1期40-43,共4页Central South Forest Inventory and Planning

基　　金：国家自然基金项目(30960302);国家自然基金项目(40861009)

摘　　要：以香格里拉县南部为研究区,利用ENVISAT ASAR双极化数据,基于数理统计方法对该地区的高山松林蓄积量估测模型进行研究。首先分析HH,HV,HV/HH值与高山松林样地蓄积量之间的相关性,结果为HV极化数据与蓄积量相关性最高;然后建立简单线性模型、指数模型以及加入地理因子的多元线性模型与非线性模型,得出指数模型为最优模型;利用独立的检验样本对最优模型进行精度评价,预测值与实测值基本相符合,平均相对误差为14.41%。Based on the statistics method, the Pinus Densata forest volume estimation mode was studied by EN- VISAT ASAR dual polarization data in the southern of Shangri-la eounty. First, the correlations between forest volume and backseattering coefficient（HH,HV,HV/HH） were analyzed,it can be found that the correlation be- tween HV baekscattering coefficient and volume was highest. And then, a simple linear model, exponential model, multiple regression model and nonlinear model with terrain factors were established. It found that the ex- ponential model was optimal. Last, the precision of the optimal model had been verified by using the independ- ent checking samples. The result showed that the predicting values corresponded with the measured values and the average relative error was 14.41%.

关 键 词：ENVISAT ASAR:后向擞射系射:高山松!蓄积营榫刑 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置] S757.2[自动化与计算机技术—控制科学与工程]