中文摘要：

提出一种九棵树多边形样地调查方法来建立林分调查因子模型,利用固定翼无人机拍摄北京松山影像数据,处理并区划后,根据九棵树法多边形样地算法估测各林分调查因子,再通过随机抽取18块样地作为检测数据,人工野外根据传统每木检尺方法计算平均胸径、平均高、林分密度以及林分蓄积量模型,然后通过经纬度、坡度、坡向、海拔等信息在影像中定位并利用九棵树法测得各林分因子调查数据,将测得数据与传统方法进行精度验证。经过精度分析,各林分调查因子相对误差介于8.80%～12.57%,相关系数介于0.624～0.927,满足森林资源二类调查需求,该方法可以替代传统每木检尺方法获取森林调查因子,将无人机融入九棵树多边形样地算法,弥补了利用传统方法耗材耗力浪费资源而用遥感影像测量精度有限制的局限性,适用于小尺度精准林业作业,既保证精度有可以极大程度减少野外人工作业量,为指定森林经营方案提供了新的方向。

英文摘要：

Forest survey factor is important parameter to master the forest vegetation growth, this paper proposes a method named nine-tree method to extract stand factors. 18 sample plots were selected to accuracy verification by comparing nine-tree method with traditional calculation formula of wood seized feet fieldwork in Beijing Song-mountain. The test result shows that relative error of stand factors between 8.80%-12.57%, correlation coefficient between 0.624-0.927. The results meet the requirements of the forest resources sub compartment surveying which can replace traditional measures. Combining UAV with ninetree method changes traditional wood seized feet fieldwork to the global, indoor, large scale survey witch provides a reference for the national forest management planning formulation.