
基于TLS数据的杨树削度方程建立及材积估算
Assessing the stem taper function and volume estimation of poplar (Populus) by terrestrial laser scanning
【目的】削度方程可以很好地描述树干直径随树高变化的情况,基于地基激光雷达(terrestrial laser scanner, TLS)的高精度三维点云数据建立准确的削度方程并进行立木材积估算,对活立木尺度的材积估计具有重要意义。【方法】以江苏省黄海海滨国家森林公园杨树人工林为研究对象,获取4块样地的TLS点云数据,通过MATLAB 2020a软件计算点云平坦度和法向量以提取单木主干,采用圆拟合方法进行不同高度处的直径拟合,利用32株样木的数据,选取6种削度模型进行建模,得到杨树树干削度方程最优拟合模型,并进行材积估算。【结果】利用TLS数据提取的胸径能替代实测胸径,其平均误差小于0.90 cm。通过对6种模型的拟合优度检验,Schumacher and Hall模型为该地区杨树削度方程最优拟合模型,模型的决定系数R2=0.984,均方根误差为1.00 cm,相对百分误差为2.79%,平均预估误差为0.271%。利用Schumacher and Hall 削度方程最优拟合模型进行活立木材积的估算,经与二元材积方程估计结果进行对比,其相对差异为3.34%,二者在统计上无显著差异。【结论】该方法可以减少地面调查对树木造成的永久性破坏,为人工林的蓄积量调查提供有效的技术支持。
【Objective】The taper function can describe variations in the trunk diameter and tree height, and it is important to estimate standing tree volume using an accurate taper function based on the high-precision three-dimensional point cloud data of the terrestrial laser scanner (TLS). 【Method】 A poplar (Populus) artificial forest in Huanghai Haibin National Forest Park, Jiangsu Province, was examined, and TLS was used to obtain point cloud data from four sampling plots. The single tree trunk point cloud was extracted by calculating flatness and a normal vector using MATLAB 2020a software. The circular fitting method was used to fit diameters at different heights. Using data of 32 sample trees, six types of taper functions were selected for modeling. The poplar tree volume was estimated using an optimized taper function. 【Result】The DBH(diameter at breast height) produced from TLS data corresponds to the measured DBH values, with an average error of less than 0.90 cm. According to the goodness of fit test of six models, a Schumacher and Hall model was the optimal taper function for poplars in this region, with an R2 value of 0.984, RMSE is 1.00 cm, MAPE is 2.79%, and MPE is 0.271%. Volumes of standing trees were estimated using the optimal taper function. Compared with the estimation results of the binary volume equation, the relative difference was 3.34%, and there was no significant difference between them. 【Conclusion】This method may help reduce ground surveys and provide an effective technical support for artificial forest volume investigations.
杨树 / 地基激光雷达 / 削度方程 / 材积 / 主干提取 / 点云数据
poplar (Populus spp.) / terrestrial laser scanner (TLS) / taper function / tree volume / trunk detection / point cloud data
[1] |
孟宪宇. 测树学[M]. 3版.北京: 中国林业出版社, 2006:159-170.
|
[2] |
庞丽峰, 贾宏炎, 陆元昌, 等. 分段削度方程2种估计方法比较[J]. 林业科学, 2015, 51(12):141-148.
|
[3] |
|
[4] |
田佳榕, 代婷婷, 徐雁南, 等. 基于地基激光雷达的采矿废弃地生态修复的植被参数提取[J]. 生态与农村环境学报, 2018, 34(8):686-691.
|
[5] |
庞勇, 李增元, 陈尔学, 等. 激光雷达技术及其在林业上的应用[J]. 林业科学, 2005, 41(3):129-136.
|
[6] |
晏颖杰, 范少辉, 官凤英. 地基激光雷达技术在森林调查中的应用研究进展[J]. 世界林业研究, 2018, 31(4):42-47.
|
[7] |
刘鲁霞, 庞勇, 李增元, 等. 用地基激光雷达提取单木结构参数:以白皮松为例[J]. 遥感学报, 2014, 18(2):365-377.
|
[8] |
|
[9] |
杨玉泽, 张珊珊, 林文树. 依据地面三维激光扫描及点云数据建立的白桦树干削度方程[J]. 东北林业大学学报, 2018, 46(12):58-63.
|
[10] |
梅光义, 孙玉军. 国内外削度方程研究进展[J]. 世界林业研究, 2015, 28(4):44-49.
|
[11] |
王鹏程, 庄尔奇, 涂炳坤, 等. 湖北省马尾松人工林削度方程及材种出材率表的研究[J]. 华中农业大学学报, 2001, 20(1):67-72.
|
[12] |
梁子瑜, 孙圆, 梁欣廉, 等. 基于地面激光扫描仪的树干削度方程提取[J]. 南京林业大学学报(自然科学版), 2014, 38(5):6-10.
|
[13] |
|
[14] |
|
[15] |
|
[16] |
|
[17] |
|
[18] |
|
[19] |
|
[20] |
|
[21] |
|
[22] |
|
[23] |
[24] |
曾伟生, 廖志云. 削度方程的研究[J]. 林业科学, 1997, 33(2):32-37.
|
[25] |
严若海, 吴富桢. 商品材积变型估测系统的研究[J]. 南京林业大学学报, 1992, 16(3):31-37.
|
[26] |
肖君. 南方型杨树人工林生长与收获模型的研究[D]. 南京:南京林业大学, 2006.
|
[27] |
|
[28] |
|
[29] |
|
[30] |
骆钰波, 黄洪宇, 唐丽玉, 等. 基于地面激光雷达点云数据的森林树高、胸径自动提取与三维重建[J]. 遥感技术与应用, 2019, 34(2):243-252.
|
[31] |
张煜星, 王雪军, 刘明博. 基于无人机遥感影像的DSM及遥感数据林分平均高提取[J]. 林业资源管理, 2017(2):23-27,52.
|
[32] |
杨坤, 赵艳玲, 张建勇, 等. 利用无人机高分辨率影像进行树木高度提取[J]. 北京林业大学学报, 2017, 39(8):17-23.
|
[33] |
张良, 姜晓琦, 周薇薇, 等. 大光斑激光雷达数据的森林冠层高度反演[J]. 测绘科学, 2018, 43(3):148-153,160.
|
[34] |
刘方舟, 刘浩, 云挺. 基于分水岭优化思想的单木信息分割算法[J]. 林业工程学报, 2020, 5(5):109-116.
|
/
〈 |
|
〉 |