Calibration and Validation of National Forest and Grassland Inventory Airborne Large-Footprint LiDAR

doi:10.13466/j.cnki.lyzygl.2021.02.008

Abstract

Abstract:

Forests play an important role in global terrestrial ecosystems.Precisely assessing forest resources and carbon sink with sample survey at a large scale is important before LiDAR is commonly used.To acquire precise geolocation of LiDAR footprint is an important step before it is applied in forest resource investigation because of the high special heterogeneity of forest height.In this paper,we use newly developed National Forest and Grassland Inventory Large-footprint LiDAR (NFGI-LIDAR-L)and ground Laser detector,develope a large-footprint LiDAR calibration method,improve the method of calculating the geocentric based on spatial pattern of laser from ground Laser detector,and calibrate NFGI-LIDAR-L.The results show that the method based on energy density of LiDAR improve the accuracy of calculating center location of large-footprint LiDAR from 5m to 1m.After calibration,the x,y,z and total accuracies of NFGI-LIDAR-L are improved from 60.51,52.76,1.88m and 80.30m to 0.61,0.54,0.05m and 0.82m,respectively.The absolute elevation accuracy of NFGI-LIDAR-L is 0.12m with flat surfaces validate with Ground Control Points.Therefore,the calibration method can be used in both calibration of airborne and spaceborne large-footprint LiDAR.

Key words: National Forest and Grassland Inventory Airborne Large-footprint LiDAR (NFGI-LIDAR-L), geometric calibration, Terrestrial Ecosystem Carbon Inventory Satellite, ground Laser detector, spatial pattern

CLC Number:

S771.5
P231

LIU Yingchun, GAO Xianlian, HE Yan, CUI Chenyan, GAO Jianxin, YU Jiayong, CAI Longtao, WU Fayun. Calibration and Validation of National Forest and Grassland Inventory Airborne Large-Footprint LiDAR[J]. FOREST RESOURCES WANAGEMENT, 2021, 0(2): 52-60.

Figures/Tables 9

Fig.1

Fig.2

Tab.1

Fig.3

Fig.4

Fig.5

Tab.2

Tab.3

Tab.4

References 15

[1]	肖兴威. 中国森林资源清查[M]. 北京: 中国林业出版社, 2005.
[2]	刘迎春, 高显连, 付超, 等. 基于森林资源清查数据估算中国森林生物量固碳潜力[J]. 生态学报, 2019,39(11):4002-4010.
[3]	Pang Yong, Lefsky M, Andersen H, et al. Validation of the ICEsat vegetation product using crown-area-weighted mean height derived using crown delineation with discrete return lidar data[J]. Canadian Journal of Remote Sensing, 2008,34(S2):471-484.
[4]	Saatchi S S, Harris N L, Brown S, et al. Benchmark map of forest carbon stocks in tropical regions across three continents[J]. Proceedings of the National Academy of Sciences, 2011,108(24):9899-9904. doi: 10.1073/pnas.1019576108
[5]	Su Yanjun, Guo Qinghua, Xue Baolin, et al. Spatial distribution of forest aboveground biomass in China:Estimation through combination of spaceborne lidar,optical imagery,and forest inventory data[J]. Remote Sensing of Environment, 2016,173:187-199. doi: 10.1016/j.rse.2015.12.002
[6]	邢艳秋. 星载激光雷达反演森林生物量方法及其应用[M]. 北京: 科学出版社, 2016.
[7]	许昌建, 刘迎春, 左丽君, 等. 基于仿真大光斑激光雷达和多层感知器的森林地上生物量估算模型[J]. 林业资源管理. 2021(1):50-60.
[8]	Schutz B E. GLAS Altimeter Post-Launch Calibration/Validation Plan[R/OL]. (2002 -02-01)[2021-04-05]. www.csr.utexas.edu/glas/pdf/plan/validation_plan_v1_oct2001.pdf.
[9]	Magruder L, Silverberg E, Webb C, et al. In situ timing and pointing verification of the ICESat altimeter using a ground-based system[J]. Geophysical Research Letters, 2005,doi: 10.1029/2005GL-023504.
[10]	韩玲, 田世强, 谢俊峰. 星载激光测高仪检校技术发展现状浅析[J]. 航天返回与遥感, 2016,37(6):11-19.
[11]	唐新明, 谢俊峰, 付兴科, 等. 资源三号02星激光测高仪在轨几何检校与试验验证[J]. 测绘学报, 2017,46(6):714-723.
[12]	吴发云, 高显连, 潘超, 等. 机载林业探测大光斑激光雷达系统的设计与应用[J]. 林业资源管理, 2018(4):125-132.
[13]	谢方. 基于2000国家大地坐标系的中国大陆速度场模型建立方法研究[D]. 西安: 长安大学, 2013.
[14]	Altamimi Z, Rebischung P, Métivier L, et al. ITRF2014:A new release of the International Terrestrial Reference Frame modeling nonlinear station motions[J]. Journal of Geophysical Research:Solid Earth, 2016,121(8):6109-6131. doi: 10.1002/2016JB013098
[15]	牛丽娟. 测量坐标转换模型研究与转换系统实现[D]. 西安: 长安大学, 2010.

设备及检校场	参数名称	参数值
全国林草资源调查机载大光斑激光雷达	激光波长/nm	1064.4
	激光脉冲宽度/ns	3.037
	激光发射频率/Hz	40~200
	激光扫描角度/(°)	±15
	激光扫描周期/s	0.7
	激光发射能量/μJ	936
	发散角/mrad	10
	波形采样时间间隔/ns	1
航飞	飞行速度/(km/h)	240
	相对航高/m	2000,1500
	光斑地面直径/m	20,15
地面激光探测器	探测中心波长/nm	1064
	能量密度探测范围/(nJ/cm²)	0.05~1
	能量密度等级输出	>4000
	探测频率/Hz	>200
检校场	检校场地范围/m×m	50×50
	激光雷达探测器间距/m×m	5×5

序号	左右角/(°) ρ	前后角/(°) β	位置差(RMSE)/m				备注
序号	左右角/(°) ρ	前后角/(°) β	Δx	Δy	Δz	Δp	备注
0	-	-	60.51	52.76	1.88	80.30	检校前
1	2.2190	-0.7995	0.93	0.93	0.05	1.32
2	2.2422	-0.7515	0.74	0.85	0.05	1.13
3	2.2507	-0.7727	0.68	0.71	0.05	0.99
4	2.2133	-0.7469	1.12	0.86	0.04	1.41
5	2.2455	-0.7595	0.65	0.77	0.05	1.01
6	2.2587	-0.7819	0.89	0.80	0.06	1.20
7	2.2340	-0.7988	0.93	0.74	0.05	1.19
8	2.2275	-0.7739	0.64	0.56	0.05	0.85
9	2.2364	-0.7731	0.61	0.55	0.05	0.82	平均参数
10	2.2345	-0.7732	0.61	0.54	0.05	0.82	最优参数

序号	航向角/(°) h₀	俯仰角/(°) p₀	翻滚角/(°) r₀	位置差/m				备注
序号	航向角/(°) h₀	俯仰角/(°) p₀	翻滚角/(°) r₀	Δx	Δy	Δz	Δp	备注
0	-	-	-	60.51	52.76	1.88	80.30	检校前
1	0.0100	0.7995	2.2190	0.92	0.93	0.05	1.31
2	0.0100	0.7518	2.2422	0.74	0.85	0.05	1.13
3	0.0220	0.7727	2.2509	0.68	0.71	0.06	0.98
4	0.0250	0.7468	2.2135	1.12	0.85	0.05	1.41
5	0.0700	0.7575	2.2455	0.66	0.77	0.05	1.02
6	0.0200	0.7818	2.2589	0.88	0.80	0.06	1.19
7	0.0310	0.7981	2.2340	0.92	0.74	0.05	1.19
8	0.0400	0.7734	2.2280	0.64	0.56	0.05	0.85
9	0.0285	0.7727	2.2365	0.61	0.55	0.05	0.82	平均参数
10	0.0200	0.7734	2.2310	0.62	0.54	0.05	0.82	最优参数

序号	大光斑中心位置差/m				相对航高/m	码盘角(θ)/ (°)	备注
序号	ε_x	ε_y	ε_z	ε_p	相对航高/m	码盘角(θ)/ (°)	备注
1	-0.070	0.112	-0.001	0.132	2000	-1.69
2	-0.074	0.112	0.000	0.134	2000	-2.38
3	0.074	-0.116	0.003	0.137	2000	-3.36
4	0.076	-0.115	0.003	0.137	2000	-3.48
5	0.090	0.045	0.000	0.100	1500	-2.21
6	0.089	0.050	0.001	0.102	1500	-2.88
7	-0.048	0.124	-0.001	0.132	2000	-1.67
8	-0.116	-0.058	-0.003	0.129	2000	-0.74
9	0.083	0.094	0.002	0.125			平均