2019年天山云杉背包式激光雷达三维参数测量数据集

doi:10.19788/j.issn.2096-6369.220118

Abstract

Abstract:

Three-dimensional structural parameters such as single wood DBH, tree height and crown width are an important basis for research on the structure, function and pattern of forest ecosystems. The application of space-based satellite remote sensing images and space-based UAV images were mostly used to extract forest structure parameters at the regional, stand and sample plot scales. Based on ground-based backpack LIDAR, high-precision feature data at the single-wood scale can be efficiently obtained to improve the efficiency and accuracy of traditional manual ground surveys, which is a powerful supplement to the data sources for forest structure parameter inversion. This dataset was based on the Picea Schrenkiana var. tianshanica forest at the National Positioning Observation and Research Station for Forest Ecosystems in the Western Tianshan Mountains of Xinjiang. Based on the characteristics of the site conditions, stand origin and spatial distribution of Picea Schrenkiana var. tianshanica, three plantation and three natural forest sample plots were selected for backpack LiDAR scanning in October 2019, and 3D point cloud data of 320 single woods of Picea Schrenkiana var. tianshanica were obtained. By preprocessing the point cloud data and identifying the single wood parameters, the 3D structural parameters such as single wood X coordinate, Y coordinate, DBH, tree height, crown diameter, crown area and crown volume were extracted to construct the 3D Parameter Measurement Dataset of Picea Schrenkiana var. tianshanica by using backpack LiDAR in 2019. This dataset could provide basic data for inversion studies of key parameters of multi-scale forest ecosystems, and can also provide a case study for evaluating the effect of backpack LiDAR application in the process of forest resource field survey.

Key words: Picea Schrenkiana var. tianshanica, single wood 3D data, backpack LIDAR, scientific data

CLC Number:

Yapeng Wang, Wenge Zhang, Lin Hu, TingTing Liu, Shanshan Cao, Lei Wang, Wei Sun. 3D Parameter Measurement Dataset of Picea Schrenkiana var. tianshanica by Using Backpack LiDAR in 2019[J].Journal of Agricultural Big Data, 2022, 4(1): 119-124.

Figures/Tables 7

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References 13

1	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(06):1269-1280.
	Dong X Y, Li J G, Chen H Y, et al. Extraction of individual tree information based on remote sensing images from an Unmanned Aerial Vehicle[J]. National Remote Sensing Bulletin, 2019,23(06):1269-1280.
2	张珊珊,孟园,林文树.基于三维激光扫描技术的单木参数提取精度研究[J].西北林学院学报,2017,32(5):189-196.
	Zhang S S, Meng Y, Lin W S. Extraction Precision of Forest Parameters at Single-tree Level Based on 3D Laser Scanning Technology[J]. Journal of Northwest Forestry University, 2017,32(5):189-196.
3	HOMOLOVA L, MALENOVSK'Y Z, CLEVERS J G,et al.Review of optical-based remote sensing for plant trait mapping[J].Ecological Complexity,2013,15:1-16.
4	李擎,王振锡,王雅佩,等.基于GF-2号遥感影像的天山云杉林郁闭度估测研究[J].中南林业科技大学学报,2019,39(08):48-54.
	LI Q, Wang Z X, et al. Study on canopy density inversion of Picea schrenkiana forest based on GF-2 remote sensing image[J]. Journal of Central South University of Forestry & Technology, 2019,39(08):48-54.
5	金忠明,曹姗姗,王蕾,等.天山云杉林无人机可见光影像树冠信息提取方法研究[J].林业资源管理,2020(01):125-135.
	Jin Z M, Cao S S, Wang L, et al. Study on Extraction of Tree Crown Information from UAV Visible Light Image of Piceaschrenkiana var. tianschanica Forest[J]. Forest Resources Management, 2020(01):125-135.
6	朱思名,王振锡,裴媛,等.基于无人机影像的天山云杉林冠幅提取及蓄积量反演[J].干旱区资源与环境,2020,34(10):160-165.
	Zhu S M, Wang Z X, Pei Y, et al. Crown extraction and volume inversion of Picea Schrenkiana var tianshanica forest based on UAV image[J]. Journal of Arid Land Resources and Environment, 2020,34(10):160-165.
7	刘东起, 范文义, 李明泽.利用小光斑激光雷达估测林分参数和生物量[J].东北林业大学学报, 2012, 40 (1) :39-43.
	Liu D Q, Fan W Y, Li M Z. Estimation of Forest Stand Parameters and Biomass by Small-Footprint Lidar[J]. Journal of Northeast Forestry University, 2012, 40 (1) :39-43.
8	Wulder M A, White J C, Stinson G,et al. 2010. Implications of differing input data sources and approaches upon forest carbon stock estimation. Environmental Monitoring and Assessment,166:543-561.
9	Thomas V, Noland T, Treitz P,et al. 2011. Leaf area and clumping indices for a boreal mixed-wood forest:LiD AR,hyperspectral,and landsat models. International Journal of Remote Sensing,32(23):8271-8297.
10	邱琴,张文革,王蕾,等.基于背包式激光雷达的天山云杉林单木因子估测[J].林业资源管理,2021(02):99-109.
	Qiu Q, Zhang W G, Wang Lei, et al. Estimation of Single Wood Factor of Picea schrenkiana var. tianshanica Forest Based on Backpack LiDAR[J]. Forest Resources Management, 2021(02):99-109.
11	包艳丽, 牛树奎, 张国林. 天山云杉林碳储量研究[J]. 干旱区资源与环境, 2009, 23(09): 113-117.
	Bao Y L, Niu S K, Zhang G L. Study on carbon storage in Picea schrenkiana[J]. Journal of Arid Land Resources and Environment, 2009, 23(09): 113-117.
12	刘贵峰, 刘玉平, 郭仲军, 等. 天山云杉林生物量及其变化规律的研究[J]. 西北林学院学报, 2013, 28(05): 13-17.
	Liu G F, Liu Y P, Guo Z J, et al. Study of Biomass of Picea schrenkiana var. tianschanica and Its Variation[J]. Journal of Northwest Forestry University, 2013, 28(05): 13-17.
13	Lee H, Slatton K C, Roth B E, et al.Adaptive clustering of airborne LiDAR data to segment individual tree crowns in managed pine forests[J].International Journal of Remote Sensing, 2010, 31 (1) :117-139.

数据库（集）名称	2019年天山云杉背包式激光雷达三维参数测量数据集
通信作者及邮箱	王蕾，E-mail: wanglei@163.com; 孙伟，E-mail: sunwei02@caas.cn
数据时间范围	2019年
空间分布	6块样地四至角点坐标如下，1号样地：82°53'27.64",43°09'06.40"；2号样地：82°53'19.20",43°09'07.74"；3号样地：82°52'51.09",43°09'02.66"；4号样地：82°52'33.21",43°08'51.02"；5号样地：82°52'20.52",43°08'45.07"；6号样地：82°52'15.87",43°08'36.50"
数据量	320株
数据格式	*.xlsx
数据服务系统网址	http://dx.doi.org/10.12205/A0007.20220609.30.ds.2055
基金项目	国家自然科学基金项目（31860180，41807005，32060321）
数据库（集）组成	对新疆西天山森林生态系统国家定位观测研究站的6块天山云杉林样地进行激光雷达扫描，提取单木三维参数，数据集包括：3个人工林和3个天然林样地文件，共有320株天山云杉单木测量数据，包含每株天山云杉的编号、X坐标、Y坐标、胸径、树高、树冠直径、冠幅面积、树冠体积，总数据量约77.4 KB。

名称	示例	名称	示例
样地	样地1	胸径/(cm)	20.1
类型	人工林	树高/(m)	7.244
编号	124	树冠直径/(m)	1.867
X坐标	-3.882	冠幅面积/(m²)	2.738
Y坐标	2.328	冠幅体积/(m³)	9.556

样地	分割正确株数	分割错误株数	漏分株数	Percision	Recall	F1-Score
1号样地	126	10	4	0.93	0.97	0.95
2号样地	72	7	3	0.91	0.96	0.94
3号样地	78	8	3	0.91	0.96	0.93
4号样地	16	2	1	0.89	0.94	0.91
5号样地	13	2	0	0.87	1.00	0.93
6号样地	15	2	1	0.88	0.94	0.91

样地	样本株数	回归关系	R²	RMSE
1号样地	126	y = 0.9299x + 0.9373	0.9413	0.89
2号样地	72	y = 0.936x + 1.1236	0.9237	1.38
3号样地	78	y = 0.9812x + 0.7597	0.9548	1.06
4号样地	16	y = 0.975x + 1.9675	0.9857	2.55
5号样地	13	y = 1.0104x - 2.9406	0.9452	4.53
6号样地	15	y = 0.9856x + 0.6628	0.9873	5.02

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3D Parameter Measurement Dataset of Picea Schrenkiana var. tianshanica by Using Backpack LiDAR in 2019

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