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Deng Lu-Xi, Tang Sha-Sha, Zou Ting-Ting, Yang Cong, Lü Sen-Tao, Shang Shu-He, Wang Xiao-Fan. Application of UAV images in monitoring flowering coverage and insect visiting activities in wetland plant communities[J]. Plant Science Journal, 2021, 39(5): 467-475. DOI: 10.11913/PSJ.2095-0837.2021.50467
Citation: Deng Lu-Xi, Tang Sha-Sha, Zou Ting-Ting, Yang Cong, Lü Sen-Tao, Shang Shu-He, Wang Xiao-Fan. Application of UAV images in monitoring flowering coverage and insect visiting activities in wetland plant communities[J]. Plant Science Journal, 2021, 39(5): 467-475. DOI: 10.11913/PSJ.2095-0837.2021.50467

Application of UAV images in monitoring flowering coverage and insect visiting activities in wetland plant communities

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This work was supported by grants from the National Natural Science Foundation of China (31970250) and Teaching Specimens Sub-platform of China (http://mnh.scu.edu.cn).

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  • Received Date: March 09, 2021
  • Revised Date: April 07, 2021
  • Available Online: October 31, 2022
  • Published Date: October 27, 2021
  • In studies on pollination ecology at the community level, the use of traditional survey methods for quantitative analysis of large-scale sample plots has certain technical limitations. Here, we explored the feasibility of applying unmanned aerial vehicle (UAV) image data to study pollination biology at the herbaceous plant community level in a subalpine wetland of Shennongjia Dajiuhu. The support vector machine (SVM) classification method was used to calculate flowering coverage of different-colored flowers based on UAV visible light images of four sites (1600~3000 m2) across different seasons, which were then combined using ContextCapture software. Combined with field surveys of flower-visiting insect activity within 16 quadrats (2 m×2 m each), the results showed that:(1) Flowering coverage of different-colored flowers in the UAV images was significantly correlated with number of pollinators, showing an exponential relationship. (2) The observed value of flowering coverage showed a decreasing trend with the increase in UAV flight altitude. (3) In the different sample plots, the number of pollinators within a unit flowering area showed no significant differences. We also explored the feasibility of calculating flowering coverage through UAV images to monitor flowering season dynamics in the study area and estimate the number of pollinators.
  • [1]
    Ollerton J, Rouquette J, Breeze TD. Insect pollinators boost the market price of culturally important crops:holly, mistletoe and the spirit of Christmas[J]. Journal of Pollination Ecology, 2016, 19:93-97.
    [2]
    Mcewen JR, Vamosi JC. Floral colour versus phylogeny in structuring subalpine flowering communities[J]. Proc Biol Sci, 2010, 277(1696):2957-2965.
    [3]
    Tuell JK, Fiedler AK, Landis D, & Isaacs R. Visitation by wild and managed bees (Hymenoptera:Apoidea) to Eastern U.S. native plants for use in conservation programs[J]. Environ Entomol, 2008, 37:707-718.
    [4]
    Sletvold N. The context dependence of pollinator-mediated selection in natural populations[J]. Int J Plant Sci, 2019, 180(9):934-943.
    [5]
    方强,黄双全. 群落水平上传粉生态学的研究进展[J].科学通报, 2014, 59(6):449-458.

    Fang Q, Huang SQ. Progress in pollination ecology at the community level[J]. Chinese Science Bulletin, 2014, 59(6):449-458.
    [6]
    杜巍, 王红侠, 汪小凡. 神农架地区典型草本群落中的昆虫访花行为比较[J]. 生物多样性, 2007, 15(6):666-672.

    Du W, Wang HX, Wang XF. Insect visitors and their beha-viors in the typical herbaceous plant communities of the Shennongjia mountains[J]. Biodiversity Science, 2007, 15(6):666-672.
    [7]
    童泽宇, 徐环李, 黄双全. 探讨监测传粉者的方法[J]. 生物多样性, 2018, 26(5):433-444.

    Tong ZY, Xu HL, Huang SQ, Examining methodologies of pollinator detection in the field[J]. Biodiversity Science, 2018, 26(5):433-444.
    [8]
    Chen B, Huang B, Xu B. Multi-source remotely sensed data fusion for improving land cover classification[J]. Isprs J Photogramm Remote Sens, 2017, 124:27-39.
    [9]
    Landmann T, Piiroinen R, Makori DM, Abdel-Rahman EM, Makau S, Raina SK. Application of hyperspectral remote sensing for flower mapping in African savannas[J]. Remote Sens Environ, 2015, 166:50-60.
    [10]
    Christin C, Dirk L, Marieke MT, Peter B, Hans P. Robinia pseudoacacia L. flower analyzed by using unmanned aerial vehicle (UAV)[J]. Remote Sens(basel), 2017, 9(11):1091.
    [11]
    Lino ACL, Sanches J, Dias-Tagliacozzo GM, Fabbro IMD, Nascimento TS. Flower classification supported by digital imaging techniques[J]. Journal of Information Technology in Agriculture, 2011, 1(4):1-6.
    [12]
    Xavier SS, Coffin AW, Olson DM, Dawn MO, Jason MS. Remotely estimating beneficial arthropod populations:Implications of a low-cost small unmanned aerial system[J]. Remote Sens(basel), 2018, 10(9):1485.
    [13]
    Müllerová J, Bartaloš T, Br[AKu。D] na J, Petr Dvo[AKrˇD] ák, Michaela Vítková. Unmanned aircraft in nature conservation:an example from plant invasions[J]. Int J Remote Sens, 2017, 38(8-10):2177-2198.
    [14]
    孙中宇, 荆文龙, 乔曦, 杨龙. 基于无人机遥感的盛花期薇甘菊爆发点识别与监测[J]. 热带地理, 2019, 39(4):482-491.

    Sun ZY, Jing WL, Qiao X, Yang L. Identification and monitoring of blooming Mikania micrantha outbreak points based on UAV remote sensing[J]. Tropical Geography, 2019, 39(4):482-491.
    [15]
    冯家莉, 刘凯, 朱远辉, 李勇, 柳林, 蒙琳. 无人机遥感在红树林资源调查中的应用[J]. 热带地理, 2015, 35(1):35-42.

    Feng JL, Liu K, Zhu YH, Li Y, Liu L, Meng L. Application of unmanned aerial vehicles to mangrove resources monitoring[J]. Tropical Geography, 2015, 35(1):35-42.
    [16]
    Kaneko K, Nohara S. Review of effective vegetation mapping using the UAV (Unmanned Aerial Vehicle) method[J]. Journal of Geographic Information System, 2014, 6(6):733-742.
    [17]
    Getzin S, Wiegand K, Schöning I. Assessing biodiversity in forests using very high-resolution images and unmanned aerial vehicles[J]. Methods Ecol Evol, 2012, 3(2):397-404.
    [18]
    Gonzalez LF, Montes GA, Puig E, Johnson S, Menger-sen K, Gaston KJ. Unmanned aerial vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation[J]. Sensors, 2016, 16:1-18.
    [19]
    Yang J, Li B. New perspectives and techniques are needed to advance invasion science[J]. Biodiversity Science, 2017, 25(12):1255-1256.
    [20]
    Galbraith SM, Vierling LA, Bosque-Pérez NA. Remote sensing and ecosystem services:Current status and future opportunities for the study of bees and pollination-related services[J]. Curr For Rep, 2015, 1(4):261-274.
    [21]
    胡健波, 张健. 无人机遥感在生态学中的应用进展[J]. 生态学报, 2018, 38(1):20-30.

    Hu JB, Zhang J. Unmanned aerial vehicle remote sensing in ecology:Advances and prospects[J]. Acta Ecologica Sinica, 2018, 38(1):20-30.
    [22]
    Chen B, Jin Y, Brown PH. An enhanced bloom index for quantifying floral phenology using multi-scale remote sensing observations[J]. Isprs J Photogramm Remote Sens, 2019, 156:108-120.
    [23]
    周文昌, 史玉虎, 潘磊, 崔鸿侠,张志鳞,杨敬元.神农架林区大九湖湿地生态系统服务价值评价[J].水土保持通报, 2018, 38(1):208-213.

    Zhou WC, Shi YH, Pan L, Cui HX, Zhang ZL, Yang JY. Evaluation of ecosystem services value of Dajiuhu wetland in Shennongjia forest region[J]. Bulletin of Soil and Water Conservation, 2018, 38(1):208-213.
    [24]
    Williams NM, Ward KL, Pope N, Isaacs R, Wilson J, et al. Native wildflower plantings support wild bee abundance and diversity in agricultural landscapes across the United States[J]. Ecol Appl, 2015, 25(8):2119-2131.
    [25]
    Horton R, Cano E, Bulanon D, Fallahi E. Peach flower monitoring using aerial multispectral imaging[J]. Journal of Imaging, 2017, 3(1):2.
    [26]
    Shen M, Chen J, Zhu X, Tang Y, Chen X. Do flowers affect biomass estimate accuracy from NDVI and EVI?[J]. Int J Remote Sens, 2010, 31(7/8):2139-2149.
    [27]
    黄双全, 郭友好. 传粉生物学的研究进展[J]. 科学通报, 2000, 45(3):225-237.

    Huang SQ, Guo YH. Research progress of pollination bio-logy[J]. Chinese Science Bulletin, 2000, 45(3):225-237.
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