基于机载激光雷达的杉木林分高生长变化分析

Height Growth Changes of Cunninghamia lanceolata Stands Based on Airborne LiDAR

机载激光雷达可准确获取林分高生长量,实现林分高生长量在更广阔空间尺度上的年生长监测。为实现杉木(Cunninghamia lanceolata)人工林年生长量监测,通过直升飞机搭载的机载激光雷达系统获取试验区林分点云数据,通过重采样得到10 m×10 m、20 m×20 m和30 m×30 m分辨率的冠层高度模型;分别设置100、200、300和400个随机点,并提取不同分辨率下的杉木林分冠层年高生长量,共获取12个处理;通过比较不同处理杉木林分年高生长量差异,选择最优的重采样分辨率;结合数字正射影像,提取杉木林分不同小班年高生长量。结果表明,400随机点数且分辨率为10 m×10 m处理下获取的数据较准确,出现异常的概率较小。2016—2017年,杉木林分年高生长量均值为0.80 m。总体上,杉木林分年高生长量增长阶段为12~15年,最大值约为2.61 m;下降阶段为15~20年,波动阶段为20~27年,最小值约为0.19 m。通过机载激光雷达数据获取冠层高生长量,能有效监测杉木林分高生长情况,可为森林资源管理与监测提供参考。

Airborne LiDAR could accurately capture stand height growth,and achieve continuous monitoring of stand height growth on larger spatial scale.In order to monitor annual growths of Cunninghamia lanceolata plantations,data was collected by helicopter-mounted airborne LiDAR system in experimental area,and three canopy height models with resolutions of 10 m×10 m,20 m×20 m and 30 m×30 m through resampling were obtained.A total of 12 treatments were acquired by setting 100,200,300 and 400 random points and extracting annual height growths of canopies in C.lanceolata stands under different resolutions.Optimal resampling reso-lution was determined by comparing differences among annual height growths of C.lanceolata stands under dif-ferent treatments.Digital orthophoto was used to extract annual height growths of C.lanceolata stands in differ-ent subcompartments.Results showed that data obtained in conditions of 400 random points with resolution of 10 m×10 m was accurate and had low chance of anomalies.Average annual height growth of C.lanceolata stands was 0.80 m from 2016 to 2017.In general,annual height growths of C.lanceolata stands increased at 12-15 years with maximum value of about 2.61 m,decreased at 15-20 years,and fluctuated at 20-27 years,with minimum value of about 0.19 m.Height growths could be obtained by airborne LiDAR data,which could effec-tively monitor height growths of C.lanceolata stands,and could provide references for management and monitor-ing of forest resources.