Accuracy Assessment of ICESat-2 Ground Elevation and Canopy Height Estimates in Mangroves

被引:12
|
作者
Yu, Jianan [1 ,2 ]
Nie, Sheng [3 ]
Liu, Wenjie [1 ]
Zhu, Xiaoxiao [3 ]
Lu, Dajin [3 ,4 ]
Wu, Wenyin [1 ]
Sun, Yue [2 ,5 ]
机构
[1] Hainan Univ, Coll Ecol & Environm, Haikou 570208, Hainan, Peoples R China
[2] Chinese Acad Sci, Aerosp Informat Res Inst, Beijing 100094, Peoples R China
[3] Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
[4] Kunming Univ Sci & Technol, Fac Land Resource Engn, Kunming 650093, Yunnan, Peoples R China
[5] Anhui Agr Univ, Sch Forestry & Landscape Architecture, Hefei 230036, Peoples R China
基金
中国国家自然科学基金;
关键词
Laser radar; Photonics; Estimation; Laser beams; Forestry; Ice; Data mining; Accuracy assessment; error analysis; ground and canopy heights; ice; cloud; and land elevation satellite-2 (ICESat-2); mangrove;
D O I
10.1109/LGRS.2021.3107440
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Rapid and accurate ecological surveys of mangroves are of great significance for coastal protection and global carbon balance assessments. Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2)/Advanced Topographic Laser Altimeter System (ATLAS) data provide an opportunity to conduct large-scale surveys of mangroves. The purpose of this study was to assess the expressiveness of ICESat-2 data for ground and canopy height retrievals in mangroves. First, the ICESat-2 data were processed to obtain the ground and canopy heights of mangrove areas. Second, the accuracies of the ground and canopy heights retrieved from the ICESat-2 data were verified by airborne light detection and ranging (LiDAR) data. Finally, we analyzed the influence of various factors on the ground and canopy height estimation accuracies. The results showed that the average errors of ICESat-2 for the ground and canopy heights were 0.28 and -0.21 m and that the root mean squared errors (RMSEs) were 0.96 and 2.50 m. The accuracies of the ICESat-2 ground and canopy height estimates differed significantly when day/night and strong/weak beams were used. The strong beams at night provided the most accurate estimations of canopy height (RMSE% = 24.4%) and are thus the most suitable choice for studying mangrove areas. In addition, the results indicated that slope is the variable that has the greatest influence on the accuracy of the ground elevation estimates of the four factors above, while the accuracy of canopy height estimates is significantly affected by the canopy height itself. Overall, our study found that ICESat-2 data are suitable for ecological investigations of mangroves.
引用
收藏
页数:5
相关论文
共 50 条
  • [41] A hydraulic model of the Amur River informed by ICESat-2 elevation
    Bauer-Gottwein, Peter
    Zakharova, Elena
    Frias, Monica Coppo
    Ranndal, Heidi
    Nielsen, Karina
    Christoffersen, Linda
    Liu, Jun
    Jiang, Liguang
    HYDROLOGICAL SCIENCES JOURNAL, 2023, 68 (14) : 2027 - 2041
  • [42] Development of Onboard Digital Elevation and Relief Databases for ICESat-2
    Leigh, Holly W.
    Magruder, Lori A.
    Carabajal, Claudia C.
    Saba, Jack L.
    McGarry, Jan F.
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2015, 53 (04): : 2011 - 2020
  • [43] Assessment of terrain elevation estimates from ICESat-2 and GEDI spaceborne LiDAR missions across different land cover and forest types
    Urbazaev, Mikhail
    Hess, Laura L.
    Hancock, Steven
    Sato, Luciane Yumie
    Ometto, Jean Pierre
    Thiel, Christian
    Dubois, Clemence
    Heckel, Kai
    Urban, Marcel
    Adam, Markus
    Schmullius, Christiane
    SCIENCE OF REMOTE SENSING, 2022, 6
  • [44] A Fine-Scale and Highly Reliable Ground and Canopy Top Extraction Method Using ICESat-2 Data
    Chang, Jingxin
    Jiang, Yonghua
    Lin, Zhiyong
    Tan, Meilin
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2024, 17 : 5266 - 5279
  • [45] A Comparison of Machine Learning and Geostatistical Approaches for Mapping Forest Canopy Height over the Southeastern US Using ICESat-2
    Tiwari, Kasip
    Narine, Lana L.
    REMOTE SENSING, 2022, 14 (22)
  • [46] ICESat-2 Derived Canopy Covers With Radiometric and Reflectance Ratio Corrections
    Zhang, Qianyin
    Zhou, Hui
    Ma, Yue
    Wang, Hong
    Li, Song
    Chen, Yuwei
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2024, 62 : 1 - 14
  • [47] A Density-Based Adaptive Ground and Canopy Detecting Method for ICESat-2 Photon-Counting Data
    Xie, Huan
    Ye, Dan
    Xu, Qi
    Sun, Yuan
    Huang, Peiqi
    Tong, Xiaohua
    Guo, Yalei
    Liu, Xiaoshuai
    Liu, Shijie
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [48] A denoising approach for detection of canopy and ground from ICESat-2's airborne simulator data in Maryland, USA
    Chen Bowei
    Pang Yong
    AOPC 2015: ADVANCES IN LASER TECHNOLOGY AND APPLICATIONS, 2015, 9671
  • [49] Evaluating ICESat-2 and GEDI with Integrated Landsat-8 and PALSAR-2 for Mapping Tropical Forest Canopy Height
    Liu, Aobo
    Chen, Yating
    Cheng, Xiao
    REMOTE SENSING, 2024, 16 (20)
  • [50] Mapping Forest Canopy Height at Large Scales Using ICESat-2 and Landsat: An Ecological Zoning Random Forest Approach
    Wu, Zhaocong
    Shi, Fanglin
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 61