中国农业科学院农业信息研究所 中国农学会
Agricultural Information Institute of CAAS China Association of Agricultural Science Societies
En
Ch
中国农业科学院农业信息研究所 中国农学会 主办

AI检索

订阅

返回顶部
当前位置: 首页 > 文章 > 基于聚类分析与岭估计模型的森林蓄积量遥感估测 中国农学通报 2019,35 (35) 35-39
Position: Home > Articles > Remote Sensing Estimation of Forest Volume Based on Cluster Analysis and Ridge Estimation Model Chinese Agricultural Science Bulletin 2019,35 (35) 35-39

基于聚类分析与岭估计模型的森林蓄积量遥感估测

作  者：
涂云燕;彭道黎
单  位：
北京林业大学林学院;贵州省林业调查规划院
关键词：
森林蓄积量;自变量;聚类分析;岭估计
摘  要：
为提高森林蓄积量遥感估测的可靠性及解决自变量间相关性问题,本研究拟采用基于聚类分析与岭估计模型对密云县森林蓄积量进行估测。选取对森林蓄积量有影响的遥感、地形因子作为分类刻画因子进行聚类分析。根据聚类结果选取建模样本,采用岭估计模型对森林蓄积量进行估测,并对其进行适用性评价与精度验证。用离差平方和进行聚集得到3种分类结果,按个数权重抽取建模样本,用30个独立预留样本对模型进行验证。结果表明,预留样本实测值与估测值的R2为0.5311,均方根误差为1.4553,相对偏差为8.9%,实测值为90.942 m3,估测值为82.842 m3。模型适用性一般,估测精度达到91.1%,总体估测精度高。
译  名：
Remote Sensing Estimation of Forest Volume Based on Cluster Analysis and Ridge Estimation Model
作  者：
Tu Yunyan;Peng Daoli;Forestry Survey and Planning Institute of Guizhou Province;Beijing Forestry University;
关键词：
forest volume;;independent variables;;cluster analysis;;ridge estimation
摘  要：
To improve the reliability of remote sensing of forest stocking equation and solve the correlation problem among independent variables, this study intended to use the clustering analysis and ridge estimation model to estimate the forest stock in Miyun County. Remote sensing and topographic factors that having an impact on forest stocks were selected as classification characterization factors for cluster analysis. According to the clustering results, the modeling samples were selected, and the forest estimation volume was estimated by the ridge estimation model, and the applicability evaluation and accuracy verification were carried out. Three kinds of classification results were obtained by aggregating the sum of squared deviations, the model samples were extracted by weights, and the models were verified by 30 independent reserved samples. The results showed that the R2 of the measured value and the estimated value of the reserved sample was 0.5311, the root mean square error was 1.4553, the relative deviation was 8.9%, the measured value was 90.942 m3, and the estimated value was 82.842 m3. The applicability of the model was general, the estimation accuracy reached91.1%, and the overall estimation accuracy was high.

相似文章

导出引用
计量
文章访问数: 8
HTML全文浏览量: 0
PDF下载量: 1

所属期刊

推荐期刊

友情链接Friendly link
农业信息研究所Agricultural information institute 农业智能知识服务平台Agricultural intelligent knowledge service platform 农业学术服务平台Agricultural Knowledge Service System 中国知网CNKI 维普网VIP 万方WANFANG DATA
联系我们Contact us

电话Tell：010-82109652-808

邮箱E-mail：agrijournal@caas.cn

服务Service
关于我们About us 意见建议Opinions and suggest
版权说明Copyright
单位：中国农业科学院农业信息研究所 中国农学会 © 2017中国农业科学院农业信息研究所 ICP备案号：京ICP备09089781号-46