Assessing the accuracy of vegetative roughness estimates using unmanned aerial vehicles [UAVs]

被引:3
|
作者
Brignoli, Lorenzo [1 ]
Annable, William Kenneth [1 ]
Plumb, Benjamin Douglas [1 ]
机构
[1] Univ Waterloo, Dept Civil & Environm Engn, Waterloo, ON, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Aquatic vegetation; Image processing; UAV; Flow resistance; Resolution vs. accuracy; Roughness estimation; AQUATIC VEGETATION; FLOW RESISTANCE;
D O I
10.1016/j.ecoleng.2018.01.005
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Cost-effective UAV (Unmanned Aerial Vehicle) technologies were utilized to map both submerged and emergent aquatic vegetation in natural rivers. This study was undertaken along reaches characterized by vegetative conditions ranging from homogeneously distributed to strongly heterogeneous and anisotropic. Spatial extent of vegetation was identified using both manual and automated image post-processing methods. For the study reaches assessed here, if 13,000 pixels/m(2) image resolution is maintained (which mostly depends on flight elevation and camera resolution) aquatic vegetation can be detected accurately. The methods presented here can be used to inventory aquatic vegetation in under one hour, as opposed to field data collection methods which would require approximately 9.5 h to achieve a comparable level of spatial resolution. Results were also applied to re-evaluate the accuracy of flow resistance formulations based on plants spatial distribution found in literature. It was found that there can be up to a 20% difference if vegetation is inventoried at the cross-sectional scale rather than at the planform scale, however for dense vegetation cover this difference is much lower.
引用
收藏
页码:73 / 83
页数:11
相关论文
共 50 条
  • [1] Radiation Monitoring Using Unmanned Aerial Vehicles (UAVs)
    Cerba, Stefan
    Vrban, Branislav
    Luley, Jakub
    Osusky, Filip
    Dudas, Juraj
    ENERGY ECOLOGY ECONOMY 2018, 2018, : 28 - 32
  • [2] The resultant positional accuracy for the orthophotos obtained with Unmanned Aerial Vehicles (UAVs)
    Popescu, Gabriel
    Iordan, Daniela
    Paunescu, Vlad
    5TH INTERNATIONAL CONFERENCE - AGRICULTURE FOR LIFE, LIFE FOR AGRICULTURE, 2016, 10 : 458 - 464
  • [3] Using unmanned aerial vehicles (UAVs) to measure jellyfish aggregations
    Schaub, Jessica
    Hunt, Brian P. V.
    Pakhomov, Evgeny A.
    Holmes, Keith
    Lu, Yuhao
    Quayle, Lucy
    MARINE ECOLOGY PROGRESS SERIES, 2018, 591 : 29 - 36
  • [4] Antenna Pattern Reconstitution using Unmanned Aerial Vehicles (UAVs)
    Schreiber, Jason
    2016 IEEE CONFERENCE ON ANTENNA MEASUREMENTS & APPLICATIONS (CAMA), 2016,
  • [5] Special issue on unmanned aerial vehicles (UAVs)
    Kimon P. Valavanis
    Control Theory and Technology, 2018, 16 (2) : 81 - 81
  • [6] Formation of a group of unmanned aerial vehicles (UAVs)
    Koo, TJ
    Shahruz, SM
    PROCEEDINGS OF THE 2001 AMERICAN CONTROL CONFERENCE, VOLS 1-6, 2001, : 69 - 74
  • [7] Special Issue on Unmanned Aerial Vehicles (UAVs)
    Jung, Sunghun
    APPLIED SCIENCES-BASEL, 2020, 10 (22):
  • [8] Methodology for Infrastructure Site Monitoring using Unmanned Aerial Vehicles (UAVs)
    Garcia Casierra, Cristian Benjamin
    Calle Sanchez, Carlos Gustavo
    Castillo Garcia, Javier Ferney
    La Rivera, Felipe Munoz
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2022, 13 (03) : 340 - 348
  • [9] Detection and monitoring wheat diseases using unmanned aerial vehicles (UAVs)
    Joshi, Pabitra
    Sandhu, Karansher S.
    Dhillon, Guriqbal Singh
    Chen, Jianli
    Bohara, Kailash
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2024, 224
  • [10] Pavement Inspection in Transport Infrastructures Using Unmanned Aerial Vehicles (UAVs)
    Feitosa, Ianca
    Santos, Bertha
    Almeida, Pedro G.
    SUSTAINABILITY, 2024, 16 (05)