TREE SPECIES CLASSIFICATION BASED ON AIRBORNE LIDAR AND HYPERSPECTRAL DATA

被引：2
|
作者：
Lu, Xukun [1 ]
Liu, Gang [1 ]
Ning, Silan [2 ]
Su, Zhonghua [2 ]
He, Ze [2 ]
机构：
[1] China Acad Elect & Informat Technol, 11 Shuangyuan Rd, Beijing 10041, Peoples R China
[2] Univ Elect Sci & Technol China, Sch Resources & Environm, 2006 Xiyuan Ave, Chengdu 611731, Peoples R China
来源：
IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2020年
关键词：
hyperspectral image; airborne LiDAR; feature extraction; tree species classification; INDIVIDUAL TREES; BIOMASS;
D O I：
10.1109/IGARSS39084.2020.9324266
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Forest resources are of great significance in regulating climate, maintaining biodiversity, and providing ecological products. Accurate identification of tree species is the basis for research and utilization of forest resources. This study combined the characteristics of multi-source data, based on the AISA EAGLE II hyperspectral images and airborne LiDAR point clouds which were obtained in August, 2016. Point cloud characteristics, spectral and texture characteristics were extracted from both datasets. Then SVM was used to classify the main tree species of Genhe experimental area. The results showed that tree species classification accuracy can be improved by using airborne LiDAR and hyperspectral image features.
引用
收藏
页码：2787 / 2790
页数：4
相关论文
共 50 条
  • [31] Tree species classification in a typical natural secondary forest using UAV-borne LiDAR and hyperspectral data
    Quan, Ying
    Li, Mingze
    Hao, Yuanshuo
    Liu, Jianyang
    Wang, Bin
    GISCIENCE & REMOTE SENSING, 2023, 60 (01)
  • [32] UAV LiDAR and Hyperspectral Data Synergy for Tree Species Classification in the Maoershan Forest Farm Region
    Wang, Bin
    Liu, Jianyang
    Li, Jianing
    Li, Mingze
    REMOTE SENSING, 2023, 15 (04)
  • [33] Tree Species Classification by Combining LiDAR, Hyperspectral Data and 3D-CNN Method
    Mao Y.
    Guo Y.
    Zhang W.
    Su Y.
    Guan Y.
    Linye Kexue/Scientia Silvae Sinicae, 2023, 59 (03): : 73 - 83
  • [34] Tree species classification of LiDAR data based on 3D deep learning
    Liu, Maohua
    Han, Ziwei
    Chen, Yiming
    Liu, Zhengjun
    Han, Yanshun
    MEASUREMENT, 2021, 177 (177)
  • [35] A Multifeature Fusion Network for Tree Species Classification Based on Ground-Based LiDAR Data
    Liu, Yaoting
    Chen, Yiming
    Liu, Zhengjun
    Chen, Jianchang
    Liu, Yuxuan
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2025, 18 : 4648 - 4663
  • [36] Classification of Protection Forest Tree Species Based on UAV Hyperspectral Data
    Zhao Q.
    Jiang P.
    Wang X.
    Zhang L.
    Zhang J.
    Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2021, 52 (11): : 190 - 199
  • [37] Spectral and Texture Features Combined for Forest Tree species Classification with Airborne Hyperspectral Imagery
    Yuanyong Dian
    Zengyuan Li
    Yong Pang
    Journal of the Indian Society of Remote Sensing, 2015, 43 : 101 - 107
  • [38] The use of airborne hyperspectral data for tree species classification in a species-rich Central European forest area
    Richter, Ronny
    Reu, Bjoern
    Wirth, Christian
    Doktor, Daniel
    Vohland, Michael
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2016, 52 : 464 - 474
  • [39] CNN-BASED TREE SPECIES CLASSIFICATION USING AIRBORNE LIDAR DATA AND HIGH-RESOLUTION SATELLITE IMAGE
    Li, Hui
    Hu, Baoxin
    Li, Qian
    Jing, Linhai
    IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2020, : 2679 - 2682
  • [40] Tree Species Classification of Airborne Hyperspectral Image in Cloud Shadow Area
    Li, Junling
    Pang, Yong
    Li, Zengyuan
    Jia, Wen
    5TH INTERNATIONAL SYMPOSIUM OF SPACE OPTICAL INSTRUMENTS AND APPLICATIONS, 2020, 232 : 389 - 398
12345