无人机遥感影像速生桉林分参数自动化提取研究
收稿日期: 2021-02-03
修回日期: 2021-05-18
网络出版日期: 2021-08-04
Study on Automatic Extraction of Fast-Growing Eucalyptus Stand Parameters Based on UAV Remote Sensing Images
Received date: 2021-02-03
Revised date: 2021-05-18
Online published: 2021-08-04
在实景三维建模软件支持下,使用无人机遥感技术快速获取广西扶绥县龙头乡将军屯速生桉林影像,通过Pix4d软件对航摄数据进行自动化内业处理,获取数字正射影像成果(DOM)和数字地表模型(DSM)以及树冠高度模型。基于此树冠高度模型,提取速生桉林的株数、树高、郁闭度等森林参数,并进行精度分析。结果表明:株数精度验证指标(株数探测率、株数准确率、F参数)较优;树高估测值与树高实测值存在较强相关性;郁闭度参数准确率高达92.85%。该林分参数自动化提取方法,能够达到相关实践要求,可以在一定程度上替代人工实测,在人工林中具有广阔应用前景。
邱世平 , 韦明新 , 马依莎 . 无人机遥感影像速生桉林分参数自动化提取研究[J]. 林草资源研究, 2021 , 0(3) : 114 -119 . DOI: 10.13466/j.cnki.lyzygl.2021.03.018
With the support of real-world 3D modeling software,the UAV remote sensing technology was used to obtain images of fast-growing eucalyptus areas in Fusui County,Guangxi.The aerial photography data was processed automatically with Pix4d software,so as to obtain the Digital Orthophoto Map l(DOM),Digital Surface Model (DSM) and crown height model.Then the fast-growing eucalyptus forest tree stem,tree height,canopy density and other forest parameters were extracted based on the crown height model,and the precision of the extracted parameters was analyzed.The results showed that the stem precision verification index (stem detection rate,accuracy rate and f parameter) was better,and there was a strong correlation between the estimated value of tree height and the measured value of tree overestimation,and the accuracy of canopy density was 92.85%.The automatic extraction method of fast growing Eucalyptus stand parameters based on UAV remote sensing image could meet the relevant practical requirements,it could replace the manual measurement to a certain extent,and it would have broad application prospect in plantation.
| [1] | 王娟, 陈永富, 陈巧, 等. 基于无人机遥感的森林参数信息提取研究进展[J]. 林业资源管理, 2020(5):144-151. |
| [2] | 李祥, 郑淯文, 戴楚彦, 等. 基于无人机影像的森林信息获取研究进展[J]. 世界林业研究, 2017, 30(4):41-46. |
| [3] | 汪小钦, 王苗苗, 等. 基于可见光波段无人机遥感的植被信息提取[J]. 农业工程学报, 2015, 31(5):152-157. |
| [4] | 周小成, 何艺, 黄洪宇, 等. 基于两期无人机影像的针叶林伐区蓄积量估算[J]. 林业科学, 2019, 55(11):117-125. |
| [5] | 苏迪, 高心丹. 基于无人机航测数据的森林郁闭度和蓄积量估测[J]. 林业工程学报, 2020, 5(1):156-163. |
| [6] | 王枚梅, 林家元, 林沂, 等. 基于无人机可见光影像的亚高山针叶林树冠参数信息自动提取[J]. 林业资源管理, 2017(4):82-88. |
| [7] | 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. |
| [8] | 刘江俊, 高海力, 方陆明, 等. 基于无人机影像的树顶点和树高提取及其影响因素分析[J]. 林业资源管理, 2019(4):107-116. |
| [9] | 董新宇, 李家国, 陈瀚阅, 等. 无人机遥感影像林地单株立木信息提取[J]. 遥感学报, 2019, 23(6):1269-1280. |
| [10] | 王浩舟, 常雅荃, 李川, 等. 无人机影像处理软件 Pix4Dmapper 与 Photoscan在资源普查中的成像性能分析[J]. 甘肃科技, 2017, 33(22):46-51. |
| [11] | 何艺, 周小成, 黄洪宇, 等. 基于无人机遥感的亚热带森林林分株数提取[J]. 遥感技术与应用, 2018, 33(1):168-176. |
| [12] | 汪霖, 李明阳, 方子涵, 等. 基于无人机数据的人工林森林参数估测[J]. 林业资源管理, 2019(5):61-67. |
| [13] | 汪霖. 基于无人机高分影像的森林参数估测方法[D]. 南京:南京林业大学, 2020. |
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