Estimation of Forest Stand Volume on Coniferous Forest Cutting Area Based on Two Periods Unmanned Aerial Vehicle Images

被引：0
|
作者：
Zhou X. [1 ]
He Y. [1 ]
Huang H. [1 ]
Xu X. [2 ]
机构：
[1] Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education National & Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou University, Fuzhou
[2] Fujian Jinsen Forestry Co. Ltd., Sanming
来源：
Linye Kexue/Scientia Silvae Sinicae | 2019年 / 55卷 / 11期
关键词：
Coniferous forest; Diameter at breast height(DBH); Forest volume; Local maximum algorithm; UAV remote sensing;
D O I：
10.11707/j.1001-7488.20191113
中图分类号：
学科分类号：
摘要：
Objective: This study proposes a method for estimating the stem volume based on UAV images before and after cutting, and provides reference for UAV remote sensing estimation of forest stem volume. Method: Based on the state-owned forest of Jinsen Forestry Co. Ltd. in Jiangle county, Sanming city, Fujian Province, the first step in this dissertation was to use unmanned aerial vehicle remote sensing to get images whose resolution was more than 10 cm, and got point cloud after Pix4D processing. Based on it, the point cloud of before cutting canopy was matched to the point cloud of surface cloud after cutting. Secondly, the forest canopy and the surface cloud were separated by the cloth simulation filtering algorithm, the digital surface model(DSM)and digital elevation model(DEM)was generated by natural neighbour method, canopy height model(CHM)was generated by the two model subtraction. Then, the tree height was extracted by the improved local maximum algorithm to searched the top of tree in canopy height model. Finally, according to the tree high and diameter at breast height(DBH)of 400 Pinus massoniana and Cunninghamia lanceolata, five DBH estimation equation in Fujian Province were established. The highest correlation coefficient model was selected to calculate the DBH, then using single wood produce volume formula in Fujian Province to estimating sub-compartment stem volume. Result: 1) The matching of two-stage UAV point cloud can better eliminate the impact of large terrain slope on tree height extraction. 2) The improved local maximum algorithm effectively reduces the errors that usually happen in the fixed window searching for canopy vertex. 3) The estimated number of tree is 339, the measured number of tree is 366, the estimated average height of stand is 18 m, the measured average height of stand is 19 m, the estimated volume of sub-compartment is 182 m3 and the measured volume is 199 m3, the estimation accuracy of the number of tree average height of stand and volume are higher. Conclusion: With the technology of UAV remote sensing, automated estimation of forest stem volume can be achieved, thus greatly reducing the cost of traditional field investigation and promoting the rapid investigation and updating of the forest resources. © 2019, Editorial Department of Scientia Silvae Sinicae. All right reserved.
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页码：117 / 125
页数：8
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