Forest and Grassland Resources Research >
Method for Sub-compartment Investigation Factors Setting and Information Acquisition Based on Integrated Aerial-Space-Ground Forest Inventory System
Received date: 2020-10-03
Revised date: 2020-12-03
Online published: 2021-03-30
In order to solve the problems in the current forest resources planning,design and forest inventory,a novel technology system of integrated aerial-space-ground forest resources survey and monitoring system was proposed and tested.This paper introduced the method for forest sub-compartment investigation factors setting and information acquisition.Compared with the traditional methods,this method lacks some factors which need to be recorded in the field,such as understory vegetation,natural regeneration and forest health status.However,the sub-compartment investigation factors of the novel technology system could still reflect the forest land and tree status(type,quantity,quality and structure),as well as the natural environment conditions.It can completely satisfied the requirements of forest resources management and statistics of forest resources reports in collective forest areas,and it also can meet the demands of various related applications for the basic data of forest resources.The basic attributes of sub-compartment(land type,dominant tree species,tree origin and associated tree species) need remotely sensed image interpretation and some supplementary field investigation,while the other attributes of sub-compartment can be obtained automatically by computer program.This method greatly reduces the investigation workload and labor force,while improves the efficiency and quality.The results indicated that it can effectively ensure the reliability of sub-compartment investigation data and the quality of forest resources inventory results.
Key words: forest resources; sub-compartment; investigation factors; remote sensing; GIS; LiDAR
Huabing DAI , Chungan LI , Yong PANG , Chonggui LI . Method for Sub-compartment Investigation Factors Setting and Information Acquisition Based on Integrated Aerial-Space-Ground Forest Inventory System[J]. Forest and Grassland Resources Research, 2021 , 0(1) : 180 -188 . DOI: 10.13466/j.cnki.lyzygl.2021.01.023
| [1] | 何齐发, 蒋苏珍, 宋辛森. 江西森林资源二类调查的主要问题及对策[J]. 江西林业科技, 2004(2):45-47. |
| [2] | 邱瑶德, 蔡良良. 现行森林资源调查方法存在问题及对策研究[J]. 浙江林业科技, 2004,24(1):36-38. |
| [3] | 王建明, 郎子岩. 谈森林资源二类调查技术的发展过程及存在问题[J].林业勘查设计, 2014(1):8-10. |
| [4] | 尹关聪. 航空像片设计带状样地调查小班森林蓄积量精度和工效探索[J]. 浙江林学院学报, 1989,6(4):383-386. |
| [5] | 李春干, 代华兵, 李崇贵. 基于高分辨率卫星图像的小班勾绘精度检验[J]. 福建林学院学报, 2006,26(2):127-130. |
| [6] | 秦树林, 崔书丹, 王国胜, 等. 森林资源二类调查存在的主要问题与改进方法[J]. 吉林林业科技, 2011,40(1):56-57. |
| [7] | 李洁. 云南省森林资源二类调查调研报告[J]. 林业建设, 2006(6):31-32. |
| [8] | 戢建华. 对辽宁省森林资源二类调查的技术特点和问题的探讨[J]. 防护林科技, 2009(5):106-109. |
| [9] | 李春干, 代华兵, 谭必增, 等. 基于SPOT5图像分割的森林小班边界自动提取[J]. 林业科学研究, 2010,23(1):53-58. |
| [10] | 李爱民. 森林资源二类调查新技术应用、存在主要问题及对策建议[J]. 内蒙古林业调查设计, 2012,35(1):40-43. |
| [11] | 孙亚丽, 周筑, 黄海燕, 等. 基于卫星遥感影像的森林资源二类调查[J]. 西部林业科学, 2017,46(2):150-152. |
| [12] | Arp H, Griesbach J, Burns J. Mapping in tropical forests:A new approach using the laser APR[J]. Photogrammetric Engineering & Remote Sensing, 1982,48:91-100. |
| [13] | Nelson R, Krabill W, MacLean G.Determining forestcanopy characteristics using airborne laser data[J]. Remote Sensing of Environment, 1984,15:201-212. |
| [14] | Nelson R, Krabill W, Tonelli J. Estimating forest biomassand volume using airborne laser data.Remote Sensing of Environment[J], 1988,24:247-267. |
| [15] | Aldred A H, Bonner G M, Application of airborne lasers to forest surveys[J/OL].(1985-01)[2020-09-09].https://cfs.nrcan.gc.ca/publications?id=4525 |
| [16] | MacLean G A, Krabill W B. Gross merchantable timber volume estimation using an airborne LiDAR system[J]. Canadian Journal of Remote Sensing, 1986,12:7-l8. |
| [17] | Nilsson M. Estimation of tree heights and stand volumeusing an airborne Lidar system.Remote Sensing of nvironment[J]. Remote Sensing of Environment, 1996,56:1-7. |
| [18] | Nelson R, Oderwald R, Gregoire T G. Separating the ground and airborne laser sampling phases to estimatetropical forest basal area,volume,and biomass[J]. Remote Sensing of Environment, 1997,60:311-326. |
| [19] | Lefsky M A, Cohen W B, Acker S A, et al. Lidar remote sensing of the canopy structure and biophysical properties of Douglas-Fir Western Hemlock Forests[J]. Remote Sens Environ, 1999,70:339-361. |
| [20] | Means J E, Acker S A, Fitt B J, et al. Predicting forest stand characteristics with airborne scanning LiDAR[J]. Photogrammetric Engineering and Remote Sensing, 2000,66, 367-1371. |
| [21] | Kvochkin O O, Ustyugov V A. Perspectives of use of lidar devices for forest inventory in Komi republic[J]. Ecology,Environment and Conservation, 2017,23(1):562-566. |
| [22] | Steen M, Thomas N-L, Torben R-N. Lidar supported estimators of wood volume and aboveground biomass from the Danish national forest inventory(2012-2016)[J]. Remote Sensing of Environment:An Interdisciplinary Journal, 2018,211:146-153. |
| [23] | 曾伟生, 孙乡楠, 王六如, 等. 基于机载激光雷达数据估计林分蓄积量及平均高和断面积[J]. 林业资源管理, 2020(2):79-86. |
| [24] | 许粲, 江腾达. 一种机载LIDAR数据估算森林蓄积参数的方法[J]. 林业资源管理, 2020(3):105-110. |
| [25] | 孙忠秋, 吴发云, 高显连, 等. 基于机载大光斑激光雷达的森林冠层高度估测[J]. 林业资源管理, 2020(3):111-117. |
| [26] | 付甜, 庞勇, 黄庆丰, 等. 亚热带森林参数的机载激光雷达估测[J]. 遥感学报, 2011(5):1092-1104. |
| [27] | 李文娟, 赵传燕, 别强, 等. 基于机载激光雷达数据的森林结构参数反演[J]. 遥感技术与应用, 2015(5):917-924. |
| [28] | 刘清旺, 谭炳香, 胡凯龙, 等. 机载激光雷达和高光谱组合系统的亚热带森林估测遥感试验[J]. 高技术通讯, 2016(3):264-274. |
| [29] | 陈雪峰, 唐小平, 翁国庆. 新时期森林资源规划设计调查的新思路[J]. 林业资源管理, 2004(1):9-14. |
| [30] | GB/T 2624-2010,森林资源规划设计调查技术规程[S]. |
| [31] | GB/T 21010-2017,土地利用现状分类[S]. |
| [32] | 李春干, 张连华. 林地斑块勾绘的空间定位精度评价方法[J]. 林业资源管理, 2014(2):126-129. |
| [33] | CH/T 8024-2011,机载激光雷达数据获取技术规范[S]. |
| [34] | 曾伟生, 周佑明. 森林资源一类和二类调查存在的主要问题与对策[J]. 中南林业调查规划, 2003,22(4):8-11. |
| [35] | 陈新林. 浅议森林资源二类调查存在的主要问题与对策[J]. 华东森林经理, 2016,30(3):19-21. |
| [36] | 高喜贵, 姜涛. 改进和完善我省森林资源二类调查体系的探讨[J]. 黑龙江生态工程职业学院学报, 2006,19(3):46-47. |
| [37] | 任瑞才, 罗刚. 加强森林资源二类调查中生态环境信息的调查[J]. 内蒙古林业调查设计, 2001(1):54-56. |
/
| 〈 |
|
〉 |