顾及森林区穿透深度影响的LT-1 InSAR区域网平差

doi:10.11947/j.AGCS.2025.20240426

测绘学报 ›› 2025, Vol. 54 ›› Issue (6): 1009-1020.doi: 10.11947/j.AGCS.2025.20240426

顾及森林区穿透深度影响的LT-1 InSAR区域网平差

吴可夫¹(), 付海强¹(), 朱建军¹, 韩启金², 王爱春², 张明霞², 李志伟¹

^1.中南大学地球科学与信息物理学院，湖南　长沙　410083
^2.中国资源卫星应用中心，北京　100094

收稿日期:2024-10-16 修回日期:2025-05-14 出版日期:2025-07-14 发布日期:2025-07-14
通讯作者: 付海强 E-mail:kefuwu@csu.edu.cn;haiqiangfu@csu.edu.cn
作者简介:吴可夫（2000—），男，博士生，研究方向为InSAR地形测绘及区域网平差。E-mail：kefuwu@csu.edu.cn
基金资助:
国家自然科学基金(42227801);国家杰出青年科学基金(41925016);湖南省自然科学基金优秀青年基金(2023JJ20061)

LT-1 InSAR block adjustment considering the impact of penetration depth in forest areas

Kefu WU¹(), Haiqiang FU¹(), Jianjun ZHU¹, Qijin HAN², Aichun WANG², Mingxia ZHANG², Zhiwei LI¹

^1.School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
^2.China Centre for Resources Satellite Data and Application, Beijing 100094, China

Received:2024-10-16 Revised:2025-05-14 Online:2025-07-14 Published:2025-07-14
Contact: Haiqiang FU E-mail:kefuwu@csu.edu.cn;haiqiangfu@csu.edu.cn
About author:WU Kefu (2000—), male, PhD candidate, majors in InSAR topographic mapping and regional network adjustment. E-mail: kefuwu@csu.edu.cn
Supported by:
The National Natural Science Foundation of China(42227801);The National Science Foundation for Distinguished Young Scholars of China(41925016);The Natural Science Foundation of Hunan Province(2023JJ20061)

摘要/Abstract

摘要：

首个L波段干涉SAR星座陆探1号(LT-1)因其强穿透力在林下地形测绘领域具有独特优势。联合高程控制点(星载LiDAR)和连接点进行区域网平差以校准系统误差，是LT-1开展大范围林下地形制图的基础。然而，为规避森林散射引发InSAR测高偏离LiDAR这一问题，现有区域网平差方法仅选取裸地点，易引发系统误差的病态观测。鉴于此，本文利用刻画森林散射过程的SINC模型补偿InSAR测高偏差，建立顾及穿透深度影响的区域网平差模型。为验证本文方法的有效性，选取森林覆盖度为85%和50%的两个试验区进行了测试。结果表明，本文估计的LT-1 DEM相对传统方法提升了22.1%和12.5%的测高精度，高程精度和林区穿透率与COP-DEM、SRTM、AW3D相比均处于最高水平。同时，基于SINC模型估计的LT-1林下地形相对LT-1 DEM提升了40.6%和25.5%的测高精度，RMSE分别为3.15 m和2.80 m。

关键词: 区域网平差, 合成孔径雷达干涉测量, 陆探1号, 数字高程模型, 林下地形, SINC模型

Abstract:

Due to its intense penetration, the first L-band interferometric SAR constellation, LuTan-1 (LT-1), has unique advantages in sub-canopy topography mapping. The block adjustment utilizes height control points (spaceborne LiDAR) and tie-points to calibrate the systematic error, which is the basis for LT-1 to carry out large-scale sub-canopy topography mapping. However, to avoid the problem of InSAR altimetry deviation from LiDAR caused by forest scattering, the existing block adjustment methods only select bare-earth points, which are prone to pathological observations with systematic error. Given this, this paper uses the SINC model that describes the forest scattering process to compensate for the InSAR altimetry deviation and establishes a block adjustment model considering the influence of penetration depth. We used two test sites with forest coverage of about 85% and 50% to verify the algorithm's effectiveness. The results show that the LT-1 DEM estimated in this paper improves the height accuracy by 22.1% and 12.5% compared with the traditional method, and the height accuracy and forest penetration rate are at the highest level compared with COP-DEM, SRTM, and AW3D. Furthermore, the LT-1 sub-canopy topography estimated based on the SINC model improved the height measurement accuracy by 40.6% and 25.5% compared with the LT-1 DEM, with RMSE of 3.15 m and 2.80 m, respectively.

Key words: block adjustment, InSAR, LT-1, DEM, sub-canopy topography, SINC model

中图分类号:

P207

吴可夫, 付海强, 朱建军, 韩启金, 王爱春, 张明霞, 李志伟. 顾及森林区穿透深度影响的LT-1 InSAR区域网平差[J]. 测绘学报, 2025, 54(6): 1009-1020.

Kefu WU, Haiqiang FU, Jianjun ZHU, Qijin HAN, Aichun WANG, Mingxia ZHANG, Zhiwei LI. LT-1 InSAR block adjustment considering the impact of penetration depth in forest areas[J]. Acta Geodaetica et Cartographica Sinica, 2025, 54(6): 1009-1020.

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数据集	数据来源	筛选法则
控制点	ICESat-2 ATL08	1. 利用COP-DEM剔除粗差
		2. 强波束
		3. 云量小于20%
		4. 非InSAR几何畸变区
		5. InSAR相干性大于第60百分位数
		6. 与LT-1 DEM差分相互剔除粗差
连接点	InSAR DEM	1. 坡度小于30°
		2. 非InSAR几何畸变区
		3. InSAR相干性大于第60百分位数
		4. 连接点对差分相互剔除粗差

数据集	发布年份	水平基准	垂直基准	分辨率/m
COP-DEM	2020	WGS-84	EGM2008	30
SRTM V3	2013	WGS-84	EGM96	30
AW3D V2.2	2019	GRS80	EGM96	30
FNF	2019	WGS-84	—	50

地形产品	（0°，5°]		（5°，10°]		（10°，15°]		（15°，20°]		（20°，90°]
地形产品	RMSE	MAE	RMSE	MAE	RMSE	MAE	RMSE	MAE	RMSE	MAE
LT-1 DEM	4.39	3.47	4.96	4.11	5.50	4.56	6.24	5.19	7.25	5.99
林下地形	2.26	1.70	2.79	2.13	3.41	2.63	4.20	3.24	5.45	4.20
COP-DEM	9.01	7.53	10.46	9.41	11.26	10.21	12.16	11.00	13.06	11.51
SRTM	5.40	4.39	6.48	5.51	7.54	6.44	8.84	7.49	10.43	8.68
AW3D	6.20	5.15	7.27	6.28	8.00	6.78	8.40	6.93	9.70	7.72

地形产品	（0°，5°]		（5°，10°]		（10°，15°]		（15°，20°]		（20°，90°]
地形产品	RMSE	MAE	RMSE	MAE	RMSE	MAE	RMSE	MAE	RMSE	MAE
LT-1 DEM	2.31	1.56	3.13	2.32	4.00	3.07	5.15	4.05	6.67	5.30
林下地形	1.84	1.28	2.40	1.77	3.09	2.30	4.06	3.05	5.54	4.17
COP-DEM	4.91	3.28	6.68	5.21	7.83	6.42	9.10	7.59	10.53	8.84
SRTM	3.12	2.39	3.99	3.11	4.82	3.78	5.96	4.71	7.59	6.17
AW3D	3.83	2.88	5.14	4.06	6.23	4.97	7.08	5.56	9.32	7.22

试验区	地形产品	（0°，5°]	（5°，10°]	（10°，15°]	（15°，20°]	（20°，90°]
1	LT-1 DEM	75.6	75.6	76.5	76.5	76.0
	LT-1林下地形	99.2	99.1	99.4	100.5	100.6
	COP DEM	51.7	52.0	48.9	50.9	51.6
	SRTM	68.4	68.2	67.5	61.5	58.9
	AW3D	67.8	67.6	66.7	64.7	63.2
2	LT-1 DEM	77.4	77.8	76.3	74.2	76.7
	LT-1林下地形	99.5	99.0	98.9	99.7	100.2
	COP DEM	54.9	57.0	54.3	48.2	47.6
	SRTM	70.8	71.9	72.8	72.9	70.3
	AW3D	63.9	65.5	65.5	66.0	64.4

顾及森林区穿透深度影响的LT-1 InSAR区域网平差

LT-1 InSAR block adjustment considering the impact of penetration depth in forest areas

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试验区	森林类型	RMSE/m	MAE/m	检核点数
1	落叶阔叶林	2.61	2.00	135217
	常绿针叶林	2.69	2.09	49508
	落叶针叶林	2.47	1.91	37962
2	落叶阔叶林	2.29	1.62	79289
	常绿针叶林	2.73	2.02	2725
	落叶针叶林	2.33	1.68	7311

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