森林蓄积量遥感估测在林业系统中具有十分重要的意义。以建德市为研究区,基于2007年TM遥感影像和2007年森林资源二类调查数据,对松树林分立地质量等级和不分地位等级两种类型建立蓄积量的遥感估测模型,并进行精度检验。其中立地质量等级依据小班平均高和平均年龄建立的地位级表划分为好、中、差三种类型,以每个小班的总蓄积量为因变量,小班各单个遥感因子信息总量为自变量。研究结果表明:1)以TM遥感影像主成分分析中第一主成分为自变量的模型拟合效果最好,决定系数R2均在0.54以上,最高为0.802;2)利用预留独立样本对模型精度进行验证,不分地位级总体估测精度为87.64%,分立地质量等级好、中、差三种类型总体的估测精度分别为94.14%,95.32%,92.38%,分立地质量类型建模的精度明显优于统一建模的精度。研究结果为森林蓄积量遥感估测提供一种改进的思路,且为提高森林生物量和碳储量遥感估测精度提供一种参考方法。
It is very important to estimate forest volume in forest system.Taking Jiande as the research area,and using TM image(2007) and the fifth(2007) forest resource survey data,we established and evaluated the precise of the volume remote sensing estimation model,which was on pine trees with or without the discrete quality grades.Site quality grade according to the average height of the small class and the average age of the establishment of the status table is divided into three types good,medium and poor.Total volume of the sub-compartment is the dependent variable,and each individual remote sensing content is the independent variable.The results are:1.the first principal component analysis of R2 Landsat TM image is the best,the correlation of determination is more than 0.54,the highest is 0.802;2.The reserved independent sample on the accuracy of the model is validated,without the discrete site quality grades,the overall level of quality estimation accuracy was 87.64%,with the site quality grades the overall level of quality estimation accuracy was 94.14%,95.32%,92.38% respectively,the classification modeling precision is much better than the unified modeling accuracy.The research results provide an improved method for the estimation of forest volume,and provide a reference for improving the accuracy of forest biomass and carbon storage estimation.
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