Unmanned aerial vehicle-based remote sensing for rangeland assessment, monitoring, and management

被引:224
|
作者
Rango, Albert [1 ]
Laliberte, Andrea [2 ]
Herrick, Jeffrey E. [1 ]
Winters, Craig [2 ]
Havstad, Kris [1 ]
Steele, Caiti [2 ]
Browning, Dawn [1 ]
机构
[1] USDA ARS, Las Cruces, NM 88003 USA
[2] New Mexico State Univ, Las Cruces, NM 88003 USA
来源
基金
美国国家科学基金会;
关键词
Small unmanned aerial vehicles; aerial photography; autonomous flight; rangeland applications; indicators; IMAGE-ANALYSIS; LANDSAT-TM; HEALTH; ENCROACHMENT; PHOTOGRAPHY; VEGETATION; JORNADA; COVER;
D O I
10.1117/1.3216822
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Rangeland comprises as much as 70% of the Earth's land surface area. Much of this vast space is in very remote areas that are expensive and often impossible to access on the ground. Unmanned Aerial Vehicles (UAVs) have great potential for rangeland management. UAVs have several advantages over satellites and piloted aircraft: they can be deployed quickly and repeatedly; they are less costly and safer than piloted aircraft; they are flexible in terms of flying height and timing of missions; and they can obtain imagery at sub-decimeter resolution. This hyperspatial imagery allows for quantification of plant cover, composition, and structure at multiple spatial scales. Our experiments have shown that this capability, from an off-the-shelf mini-UAV, is directly applicable to operational agency needs for measuring and monitoring. For use by operational agencies to carry out their mandated responsibilities, various requirements must be met: an affordable and reliable platform; a capability for autonomous, low altitude flights; takeoff and landing in small areas surrounded by rugged terrain; and an easily applied data analysis methodology. A number of image processing and orthorectification challenges have been or are currently being addressed, but the potential to depict the land surface commensurate with field data perspectives across broader spatial extents is unrivaled.
引用
收藏
页数:15
相关论文
共 50 条
  • [1] RANGELAND RESOURCE ASSESSMENT, MONITORING, AND MANAGEMENT USING UNMANNED AERIAL VEHICLE-BASED REMOTE SENSING
    Rango, Albert
    Laliberte, Andrea
    Havstad, Kris
    Winters, Craig
    Steele, Caiti
    Browning, Dawn
    [J]. 2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2010, : 608 - 611
  • [2] Unmanned aerial vehicle-based remote sensing in monitoring smallholder, heterogeneous crop fields in Tanzania
    Yonah, Isack B.
    Mourice, Sixbert K.
    Tumbo, Siza D.
    Mbilinyi, Boniface P.
    Dempewolf, Jan
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2018, 39 (15-16) : 5453 - 5471
  • [3] Unmanned Aerial Vehicle-Based Multispectral Remote Sensing for Commercially Important Aromatic Crops in India for Its Efficient Monitoring and Management
    Bahuguna, Sonam
    Anchal, Shubham
    Guleria, Deepak
    Devi, Mamta
    Meenakshi
    Kumar, Devshree
    Kumar, Rakesh
    Murthy, P. V. S.
    Kumar, Amit
    [J]. JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 2022, 50 (02) : 397 - 407
  • [4] Unmanned Aerial Vehicle-Based Multispectral Remote Sensing for Commercially Important Aromatic Crops in India for Its Efficient Monitoring and Management
    Sonam Bahuguna
    Shubham Anchal
    Deepak Guleria
    Mamta Devi
    Devshree Meenakshi
    Rakesh Kumar
    P. V. S. Kumar
    Amit Murthy
    [J]. Journal of the Indian Society of Remote Sensing, 2022, 50 : 397 - 407
  • [5] Advances in Unmanned Aerial Vehicle-Based Sensing and Imaging
    Antonakakis, Marios
    Zervakis, Michail
    [J]. Sensors, 2024, 24 (24)
  • [6] Mini-Unmanned Aerial Vehicle-Based Remote Sensing Techniques, applications, and prospects
    Xiang, Tian-Zhu
    Xia, Gui-Song
    Zhang, Liangpei
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, 2019, 7 (03) : 29 - 63
  • [7] Evaluating an Unmanned Aerial Vehicle-based Remote Sensing System for Estimation of Rice Nitrogen Status
    Lu, Junjun
    Miao, Yuxin
    Huang, Yanbo
    Shi, Wei
    Hu, Xiaoyi
    Wang, Xinbing
    Wan, Jun
    [J]. 2015 FOURTH INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS, 2015,
  • [8] Nitrogen Monitoring of Winter Wheat Based on Unmanned Aerial Vehicle Remote Sensing Image
    Liu C.
    Wang Z.
    Chen Z.
    Zhou L.
    Yue X.
    Miao Y.
    [J]. Chen, Zhichao (logczc@163.com), 2018, Chinese Society of Agricultural Machinery (49): : 207 - 214
  • [9] Applications of unmanned aerial vehicle images on agricultural remote sensing monitoring
    [J]. Wang, L. (wanglimin01@caas.cn), 1600, Chinese Society of Agricultural Engineering (29):
  • [10] Construction of an unmanned aerial vehicle remote sensing system for crop monitoring
    Jeong, Seungtaek
    Ko, Jonghan
    Kim, Mijeong
    Kim, Jongkwon
    [J]. JOURNAL OF APPLIED REMOTE SENSING, 2016, 10