Remote Sensing Technology and Application, Volume. 39, Issue 1, 87(2024)

Study on Classification of Arbor Tree Species at Single Tree Scale based on Cross-modal Hybrid Fusion of UAV Point Cloud and Image

Min YAN1、*, Yonghua XIA1,2, Chong WANG3, Xiali KONG1, Haoyu TAI1, and Chen LI1
Author Affiliations
  • 1Faculty of Land Resources Engineering,Kunming University of Science and Technology,Kunming 650093,China
  • 2City College,Kunming University of Science and Technology,Kunming 650051,China
  • 3Kunming Survey and Design Institute Co. ,Ltd. ,China Power Construction Group,Kunming 650200,China
  • show less
    References(26)

    [1] Yijun LIU, Yong PANG, Shenxi LIAO et al. Merged airborne lidar and hyperspectral data for Tree Species Classification in Puer’s mountainous area. Forest Research, 29, 407-412(2016).

    [2] A Modzelewska, F E Fassnacht, K Sterenczak. Tree species identification within an extensive forest area with diverse management regimes using airborne hyperspectral data. International Journal of Applied Earth Observation and Geoinformation, 84: 101960(2020).

    [3] B X Hu. Contribution of topographic features and categorization uncertainty for a tree species classification in the boreal biome of Northern Ontario. GIScience & Remote Sensing, 60, 1(2023).

    [4] Z Y ZHANG, X Y LIU. Support vector machines for tree species identification using LiDAR-derived structure and intensity variables. Geocarto International, 28, 364-378(2013).

    [5] Shuai ZHAO, Meiqin CAO, Xiandie JIANG et al. Man-made tree species classification in Lixin County,Anhui Province. Remote Sensing Technology and Application, 37, 589-598(2022).

    [6] Guang OUYANG, Linhai JING, Shijie YAN et al. Classification of individual tree species in high-resolution remote sensing imagery based on convolution neural network. Laser & Optoelectronics Progress, 58, 349-362(2021).

    [7] Zhiwei LIN, Qilu GONG, Jiahang HUANG et al. Studu on tree species classification of UAV optical image based on DenseNet. Remote Sensing Technology and Application, 34, 704-711(2019).

    [8] M YAN, Y H XIA, X Y YANG et al. Biomass estimation of subtropical arboreal forest at single tree scale based on feature fusion of airborne LiDAR data and aerial images. Sustainability, 15, 1676(2023).

    [9] Camile Sothe, Michele Dalponte et al. Tree species classification in a highly diverse subtropical forest integrating UAV-based photogrammetric point cloud and hyperspectral data. Remote Sensing, 11(2019).

    [10] Somayeh Nezami, Ehsan Khoramshahi, Olli Nevalainen et al. Tree species classification of drone hyperspectral and rgb imagery with deep learning convolutional neural networks. Remote Sensing, 12(2020).

    [11] Yi XU, Jianing ZHEN, Xiapeng JIANG et al. Mangrove species classification with UAV-based remote sensing data and XGBoost. National Remote Sensing Bulletin, 25, 737-752(2021).

    [12] Zhiyang XU, Qiao CHEN, Yongfu CHEN. Tree species recognition based on unmanned aerial vehicle image with LiDAR Individual Tree Segmentation Aided. Transactions of the Chinese Society for Agricultural Machinery, 53, 197-205(2022).

    [13] Juan SHI, De XIE, Qing JIANG. Deep Consistency-preserving Hashing. Journal of Xidian University, 48, 71(2021).

    [14] K ZHANG, Y GENG, J ZHAO et al. Multimodal sentiment analysis based on attention mechanism and tensor fusion network, 1473-1477(2021).

    [15] Sai ZENG, Xuanmin DU. Multimodal underwater target recognition method based on deep learning. Journal of Applied Acoustics, 38, 589-595(2019).

    [16] S FATHOLOLOUMI, M K FIROZJAEI, H J LI et al. Surface biophysical features fusion in remote sensing for improving land crop/cover classification accuracy. Science of The Total Environment, 9(2022).

    [17] YT HU, Z WANG, X F LI et al. Nondestructive classification of maize moldy seeds by hyperspectral imaging and optimal machine learning algorithms. Sensors, 22, 6064(2022).

    [18] Mengmeng ZHANG, Wei LI, Huan LIU et al. Classification of hyperspectral forest tree species based on morphological transform and spatial logical integration. Acta Geodaetica et Cartographica Sinica, 52, 1202-1211(2023).

    [20] Tianqi Chen, Carlos Guestrin. XGBoost: A Scalable Tree Boosting System, 785-794(2016).

    [21] G KE, Q MENG, T FINLEY et al. Lightgbm: A highly efficient gradient boosting decision tree, 3146-3154(2017).

    [22] D H Wolpert. Stacked generalization. Neural networks, 5, 241-259(1992).

    [23] Lin JIN, Yan LI. Analysis and realization of several correlation coefficients in R language. Journal of Statistics and Information, 34, 3-11(2019).

    [24] Haiyang YU, Saifei XIE, Linghui GUO et al. Extremely Randomized Trees Estimation of Soil Heavy Metal Content by Fusing Spectra and Spatial Features. Transactions of the Chinese Society for Agricultural Machinery, 53, 231-239(2022).

    [25] T Y LIN, A ROYCHOWDHURY, S MAJI. Bilinear CNN Models for Fine-grained Visual Recognition, 1449-1457(2015).

    [26] A ZADEH, M CHEN, S PORIA et al. Tensor fusion network for multimodal sentiment analysis, 1103-1114(2017).

    [27] Z LIU, Y SHEN, V B LAKSHMINARASIMHAN et al. Efficient Low-rank Multimodal Fusion with Modality-Speci-fic Factors, 2247-2256(2018).

    Tools

    Get Citation

    Copy Citation Text

    Min YAN, Yonghua XIA, Chong WANG, Xiali KONG, Haoyu TAI, Chen LI. Study on Classification of Arbor Tree Species at Single Tree Scale based on Cross-modal Hybrid Fusion of UAV Point Cloud and Image[J]. Remote Sensing Technology and Application, 2024, 39(1): 87

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Research Articles

    Received: Jul. 20, 2022

    Accepted: --

    Published Online: Jul. 22, 2024

    The Author Email: YAN Min (1626020236@qq.com)

    DOI:10.11873/j.issn.1004-0323.2024.1.0087

    Topics