Message Board

Respected readers, authors and reviewers, you can add comments to this page on any questions about the contribution, review, editing and publication of this journal. We will give you an answer as soon as possible. Thank you for your support!

Full name
E-mail
Phone number
Title
Message
Verification Code
Volume 45 Issue 7
Jul.  2023
Turn off MathJax
Article Contents
Cai Shaomeng,Chen Chunhua,Liu Jianbo, et al. Study on inverting seagrass coverage ratio at Dongjiao Coconut Forest based on UAV aerial survey technology[J]. Haiyang Xuebao,2023, 45(7):183–194 doi: 10.12284/hyxb2023113
Citation: Cai Shaomeng,Chen Chunhua,Liu Jianbo, et al. Study on inverting seagrass coverage ratio at Dongjiao Coconut Forest based on UAV aerial survey technology[J]. Haiyang Xuebao,2023, 45(7):183–194 doi: 10.12284/hyxb2023113

Study on inverting seagrass coverage ratio at Dongjiao Coconut Forest based on UAV aerial survey technology

doi: 10.12284/hyxb2023113
  • Received Date: 2022-11-08
  • Rev Recd Date: 2023-02-12
  • Available Online: 2023-09-21
  • Publish Date: 2023-07-01
  • Seagrass coverage ratio is an important indicator reflecting the ecological status of seagrass beds. In this paper, through the design of aerial photography scheme and flight condition test, the high-resolution seagrass image map of the Dongjiao Coconut Forest sea area was obtained by using UAV aerial photography. Combined with the image classification tools of ArcGIS software and 3D tools, a new method for calculating the coverage ratio of seagrass were obtained and the coverage of seagrass was calculated. The station location of simulating survey method of the traditional seagrass coverage ratio was compared and discussed. Seagrasses in the coastal sea bed of the Dongjiao Coconut Forest are distributed on the coral reefs within 300 m from the shore with patches and intervals. Using the new method, the concentrated distribution area of seagrass at sea bed of the Dongjiao Coconut Forest is about 23 221 m2, and average concentration distribution ratio is 17.79%. The distribution area of seagrass in this study area is about 16 423 m2, and the coverage ratio of seagrass is 12.58%. The coverage ratio of seagrass is higher, and the ecological condition of seagrass bed is good. Sargassum is densely distributed in the southeast area of the study area, with a distribution area of 755.6 m2 and a coverage of 0.5%, and grows as a single cylinder floating. By simulating the investigation station location of the sample frame method and sample line method of traditional seagrass coverage survey, seagrass coverage ratio changes with different stations, sample frame, and sample line positions changing randomly, which is the reason for the representativeness and comparability of the traditional survey results. The research results of this project have the promotion and application value in the investigation of seagrass ecological monitoring area.
  • loading
  • [1]
    周媛媛. 海草床资源保护与可持续发展研究[J]. 国土与自然资源研究, 2021(2): 68−71. doi: 10.16202/j.cnki.tnrs.2021.02.021

    Zhou Yuanyuan. Study on the protection and sustainable development of seagrass bed resources[J]. Territory & Natural Resources Study, 2021(2): 68−71. doi: 10.16202/j.cnki.tnrs.2021.02.021
    [2]
    Fourqurean J W, Duarte C M, Kennedy H, et al. Seagrass ecosystems as a globally significant carbon stock[J]. Nature Geoscience, 2012, 5(7): 505−509. doi: 10.1038/ngeo1477
    [3]
    韩秋影, 施平. 海草生态学研究进展[J]. 生态学报, 2008, 28(11): 5561−5570. doi: 10.3321/j.issn:1000-0933.2008.11.040

    Han Qiuying, Shi Ping. Progress in the study of seagrass ecology[J]. Acta Ecologica Sinica, 2008, 28(11): 5561−5570. doi: 10.3321/j.issn:1000-0933.2008.11.040
    [4]
    Duarte C M, Borum J, Short F T, et al. Seagrass ecosystems: their global status and prospects[M]//Polunin N V C. Aquatic Ecosystems. Cambridge: Cambridge University Press, 2008: 281−294.
    [5]
    Orth R J, Carruthers T J B, Dennison W C, et al. A global crisis for seagrass ecosystems[J]. Bioscience, 2006, 56(12): 987−996. doi: 10.1641/0006-3568(2006)56[987:AGCFSE]2.0.CO;2
    [6]
    Wahl T, Haigh I D, Woodworth P L, et al. Observed mean sea level changes around the North Sea coastline from 1800 to present[J]. Earth-Science Reviews, 2013, 124: 51−67. doi: 10.1016/j.earscirev.2013.05.003
    [7]
    Waycott M, Duarte C M, Carruthers T J B, et al. Accelerating loss of seagrasses across the globe threatens coastal ecosystems[J]. Proceedings of the National Academy of Sciences of the United States of America, 2009, 106(30): 12377−12381.
    [8]
    黄小平, 黄良民, 李颖虹, 等. 华南沿海主要海草床及其生境威胁[J]. 科学通报, 2006, 51(2): 136−142.

    Huang Xiaoping, Huang Liangmin, Li Yinghong. Main seagrass beds and threats to their habitats in the coastal sea of South China[J]. Chinese Science Bulletin, 2006, 51(2): 136−142.
    [9]
    陈石泉, 王道儒, 吴钟解, 等. 海南岛东海岸海草床近10 a变化趋势探讨[J]. 海洋环境科学, 2015, 34(1): 48−53. doi: 10.13634/j.cnki.mes.2015.01.009

    Chen Shiquan, Wang Daoru, Wu Zhongjie, et al. Discussion of the change trend of the seagrass beds in the east coast of Hainan Island in nearly a decade[J]. Marine Environmental Science, 2015, 34(1): 48−53. doi: 10.13634/j.cnki.mes.2015.01.009
    [10]
    吴钟解, 陈石泉, 蔡泽富, 等. 海南岛海草床分布变化及恢复建议[J]. 海洋环境科学, 2021, 40(4): 542−549. doi: 10.12111/j.mes.20200130

    Wu Zhongjie, Chen Shiquan, Cai Zefu, et al. Analysis of distribution change and restoration suggestion of the seagrass beds in Hainan Island[J]. Marine Environmental Science, 2021, 40(4): 542−549. doi: 10.12111/j.mes.20200130
    [11]
    陈春华, 吴钟解, 张光星. 新村港海草床的生态状况及可持续利用探讨[J]. 海洋开发与管理, 2011, 28(11): 74−78. doi: 10.3969/j.issn.1005-9857.2011.11.021

    Chen Chunhua, Wu Zhongjie, Zhang Guangxing. Discussion on the ecological status and sustainable utilization of seagrass beds in Xincun Port[J]. Ocean Development and Management, 2011, 28(11): 74−78. doi: 10.3969/j.issn.1005-9857.2011.11.021
    [12]
    王道儒, 吴钟解, 陈春华, 等. 海南岛海草资源分布现状及存在威胁[J]. 海洋环境科学, 2012, 31(1): 34−38. doi: 10.3969/j.issn.1007-6336.2012.01.008

    Wang Daoru, Wu Zhongjie, Chen Chunhua, et al. Distribution of sea-grass resources and existing threat in Hainan Island[J]. Marine Environmental Science, 2012, 31(1): 34−38. doi: 10.3969/j.issn.1007-6336.2012.01.008
    [13]
    陈石泉, 林国尧, 蔡泽富, 等. 海南东寨港海草资源分布特征及影响因素[J]. 湿地科学与管理, 2019, 15(4): 53−56. doi: 10.3969/j.issn.1673-3290.2019.04.13

    Chen Shiquan, Lin Guoyao, Cai Zefu, et al. Patterns and impacting factors of the distribution of the seagrass resources in Dongzhai Harbour of Hainan[J]. Wetland Science & Management, 2019, 15(4): 53−56. doi: 10.3969/j.issn.1673-3290.2019.04.13
    [14]
    李政, 李文涛, 杨晓龙, 等. 威海荣成桑沟湾海域海草床分布现状及其生态特征[J]. 海洋科学, 2020, 44(10): 52−59.

    Li Zheng, Li Wentao, Yang Xiaolong, et al. Distribution and ecological characteristics of seagrass beds in Rongcheng Sanggou Bay, Weihai[J]. Marina Sciences, 2020, 44(10): 52−59.
    [15]
    杨中华, 庞海. 我国资源环境监测中遥感技术应用现状及展望[J]. 中外企业家, 2009(12): 164−165.

    Yang Zhonghua, Pang Hai. Application status and prospect of remote sensing technology in resource and environmental monitoring in China[J]. Chinese & Foreign Entrepreneurs, 2009(12): 164−165.
    [16]
    Guerrero M K M R, Vivar J A M, Ramos R V, et al. Assessment of seagrass percent cover and water quality using UAV images and field measurements in Bolinao, Pangasinan[J]. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019, XLII-4/W19: 233−240. doi: 10.5194/isprs-archives-XLII-4-W19-233-2019
    [17]
    Nahirnick N K, Hunter P, Costa M, et al. Benefits and challenges of UAS imagery for eelgrass (Zostera marina) mapping in small estuaries of the Canadian west coast[J]. Journal of Coastal Research, 2019, 35(3): 673−683. doi: 10.2112/JCOASTRES-D-18-00079.1
    [18]
    Chand S, Bollard B. Detecting the spatial variability of seagrass meadows and their consequences on associated macrofauna benthic activity using novel drone technology[J]. Remote Sensing, 2022, 14(1): 160.
    [19]
    Ventura D, Bonifazi A, Gravina M F, et al. Mapping and classification of ecologically sensitive marine habitats using unmanned aerial vehicle (UAV) imagery and object-based image analysis (OBIA)[J]. Remote Sensing, 2018, 10(9): 1331. doi: 10.3390/rs10091331
    [20]
    Pasqualini V, Pergent-martini C, Pergent G, et al. Use of SPOT 5 for mapping seagrasses: an application to Posidonia oceanica[J]. Remote Sensing of Environment, 2005, 94(1): 39−45. doi: 10.1016/j.rse.2004.09.010
    [21]
    Barillé L, Robin M, Harin N, et al. Increase in seagrass distribution at Bourgneuf Bay (France) detected by spatial remote sensing[J]. Aquatic Botany, 2010, 92(3): 185−194. doi: 10.1016/j.aquabot.2009.11.006
    [22]
    Yang Chaoyu, Yang Dingtian, Cao Wenxi, et al. Analysis of seagrass reflectivity by using a water column correction algorithm[J]. International Journal of Remote Sensing, 2010, 31(17/18): 4595−4608.
    [23]
    Hobley B, Arosio R, French G, et al. Semi-supervised segmentation for coastal monitoring seagrass using RPA imagery[J]. Remote Sensing, 2021, 13(9): 1741. doi: 10.3390/rs13091741
    [24]
    Duffy J P, Pratt L, Anderson K, et al. Spatial assessment of intertidal seagrass meadows using optical imaging systems and a lightweight drone[J]. Estuarine Coastal and Shelf Science, 2018, 200: 169−180. doi: 10.1016/j.ecss.2017.11.001
    [25]
    Chayhard S, Manthachitra V, Naulchawee K, et al. Multi-temporal mapping of seagrass distribution by using integrated remote sensing data in Kung Kraben Bay (KKB), Chanthaburi Province, Thailand[J]. International Journal of Agricultural Technology, 2018, 14(2): 161−170.
    [26]
    Konar B, Iken K. The use of unmanned aerial vehicle imagery in intertidal monitoring[J]. Deep-Sea Research Part II: Topical Studies in Oceanography, 2018, 147: 79−86. doi: 10.1016/j.dsr2.2017.04.010
    [27]
    Riniatsih I, Ambariyanto A, Yudiati E, et al. Monitoring the seagrass ecosystem using the unmanned aerial vehicle (UAV) in coastal water of Jepara[J]. IOP Conference Series: Earth and Environmental Science, 2021, 674(1): 012075. doi: 10.1088/1755-1315/674/1/012075
    [28]
    Yang Bo, Hawthorne T L, Searson H, et al. High-resolution UAV mapping for investigating eelgrass beds along the west coast of north America[C]//Proceedings of the IGARSS 2020−2020 IEEE International Geoscience and Remote Sensing Symposium. Waikoloa, HI, USA: IEEE, 2020: 6317−6320.
    [29]
    孙家抦. 遥感原理与应用[M]. 武汉: 武汉大学出版社, 2009.

    Sun Jiabing. Principles and Applications of Remote Sensing[M]. Wuhan: Wuhan University Press, 2009.
    [30]
    任艳中, 王弟, 李轶涛, 等. 无人机遥感在森林资源监测中的应用研究进展[J]. 中国农学通报, 2020, 36(8): 111−118. doi: 10.11924/j.issn.1000-6850.casb19010104

    Ren Yanzhong, Wang Di, Li Yitao, et al. Applications of unmanned aerial vehicle-based remote sensing in forest resources monitoring: a review[J]. Chinese Agricultural Science Bulletin, 2020, 36(8): 111−118. doi: 10.11924/j.issn.1000-6850.casb19010104
    [31]
    周游. 无人机遥感在农田信息监测中的应用进展[J]. 农村实用技术, 2020(8): 92−93.

    Zhou You. Application progress of UAV remote sensing in farmland information monitoring[J]. Rural Practical Technology, 2020(8): 92−93.
    [32]
    张敏霞, 梅丹英, 高伟俊, 等. 无人机遥感技术在城市绿地监测中的应用进展[J]. 中国城市林业, 2019, 17(5): 5−11. doi: 10.12169/zgcsly.2019.05.12.0005

    Zhang Minxia, Mei Danying, Gao Weijun, et al. Review on the applications of UAV remote sensing technology to urban green space monitoring[J]. Journal of Chinese Urban Forestry, 2019, 17(5): 5−11. doi: 10.12169/zgcsly.2019.05.12.0005
    [33]
    蔡泽富, 陈石泉, 吴钟解, 等. 海南岛海湾与潟湖中海草的分布差异及影响分析[J]. 海洋湖沼通报, 2017(3): 74−84. doi: 10.13984/j.cnki.cn37-1141.2017.03.011

    Cai Zefu, Chen Shiquan, Wu Zhongjie, et al. Distribution differences and environmental effects of seagrasses between bays and lagoons of Hainan Island[J]. Transactions of Oceanology and Limnology, 2017(3): 74−84. doi: 10.13984/j.cnki.cn37-1141.2017.03.011
    [34]
    郑凤英, 邱广龙, 范航清, 等. 中国海草的多样性、分布及保护[J]. 生物多样性, 2013, 21(5): 517−526.

    Zheng Fengying, Qiu Guanglong, Fan Hangqing, et al. Diversity, distribution and conservation of Chinese seagrass species[J]. Biodiversity Science, 2013, 21(5): 517−526.
    [35]
    陈春华, 蔡绍孟, 刘建波, 等. 无人机航测技术在海草床调查中的试点应用[J]. 应用海洋学学报, 2022, 41(4): 637−643. doi: 10.3969/J.ISSN.2095-4972.2022.04.009

    Chen Chunhua, Cai Shaomeng, Liu Jianbo, et al. Pilot application of UAV aerial survey technique in seagrass bed investigation[J]. Journal of Applied Oceanography, 2022, 41(4): 637−643. doi: 10.3969/J.ISSN.2095-4972.2022.04.009
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(9)  / Tables(5)

    Article views (300) PDF downloads(39) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return