矿区土地复垦植被高度提取方法研究

Research on Extraction Method of Vegetation Height for Land Reclamation in Mining Area

文章以某露天矿区植被信息调查项目为研究对象,选择两个平均高程具有一定差异的样地进行测试研究,采用机载激光雷达技术进行矿区点云数据采集,经去噪、分类等处理后,生成矿区植被点云数据,然后以克里金插值法、不规则三角网插值法和反距离权重插值法共3种插值算法为基础,对矿区分类处理后的点云数据进行插值运算,建立植被冠层高度模型,然后进行树高提取,并与现场实测样本数据进行对比分析,通过建立不同插值算法的线性回归模型,对比决定系数R2和均方根误差发现:利用反距离权重插值法建立的植被冠层高度模型进行树高提取,估算树高与实测值贴合度相对较好,数据精度相对较高,其次为不规则三角网插值法,克里金插值法估算效果最差,但3种方法均能对矿区植被高度信息进行较好反映,且数据采集速度较快,可靠性较高,能够大大提高复垦矿区植被信息的更新效率,为矿区生态恢复评价工作提供数据支撑。

Taking a vegetation information survey project in an open-pit mining area as the research object,this paper selects two sample plots with a certain difference in average elevation for test research.After that,based on three interpolation algorithms,namely,Kriging interpolation,irregular triangular network interpolation and inverse distance weight interpolation,the point cloud data after classification in mining area are interpolated to establish a vegetation canopy height model,and then the tree height is extracted and compared with the field measured sample data.Finally,by establishing a linear regression model of different interpolation algorithms,comparing the coefficient of determination and root mean square error,it is found that:the tree height extracted by the inverse distance weight interpolation method had a relatively good fit with the measured value,and its data accuracy was relatively high,than the irregular triangulation interpolation method was second,and the Kriging interpolation method was the worst.However,all of them can better reflect the vegetation height information in the mining area,and the data collection speed is fast and the reliability is high,which can greatly improve the efficiency of vegetation information update in the reclamation mining area,and provide data support for the ecological recovery evaluation of the mining area.