USE OF HIGH-RESOLUTION MULTISPECTRAL IMAGERY FROM AN UNMANNED AERIAL VEHICLE IN PRECISION AGRICULTURE

被引:7
作者
Al-Arab, Manal [1 ]
Torres-Rua, Alfonso [1 ]
Ticlavilca, Andres [1 ]
Jensen, Austin [1 ]
McKee, Mac [1 ]
机构
[1] Utah State Univ, Utah Water Res Lab, Logan, UT 84322 USA
来源
2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2013年
关键词
Remote Sensing; High Resolution Imaging; AggieAir; Agriculture; Machine Learning Algorithms; CROPS;
D O I
10.1109/IGARSS.2013.6723419
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Precision agriculture requires high spatial management of the inputs to agricultural production. This requires that actionable information about crop and field status be acquired at the same high spatial resolution and at a temporal frequency appropriate for timely responses. This paper presents some results from an on-going project to explore the use of imagery collected from the use of a small unmanned aerial vehicle, called AggieAir, to estimate plant nitrogen and chlorophyll at approximately 13-cm resolution for a field of oats served by a center pivot sprinkler system. When combined with appropriate analytic tools, the AggieAir imagery can be successfully used to estimate plant nitrogen and chlorophyll levels at much finer than 1-m resolution.
引用
收藏
页码:2852 / 2855
页数:4
相关论文
共 50 条
  • [11] Mapping Coastal Wetland Biomass from High Resolution Unmanned Aerial Vehicle (UAV) Imagery
    Doughty, Cheryl L.
    Cavanaugh, Kyle C.
    REMOTE SENSING, 2019, 11 (05)
  • [12] MAPPING CROP STATUS FROM AN UNMANNED AERIAL VEHICLE FOR PRECISION AGRICULTURE APPLICATIONS
    Guo, T.
    Kujirai, T.
    Watanabe, T.
    XXII ISPRS CONGRESS, TECHNICAL COMMISSION I, 2012, 39-B1 : 485 - 490
  • [13] Enhancing Georeferencing and Mosaicking Techniques over Water Surfaces with High-Resolution Unmanned Aerial Vehicle (UAV) Imagery
    Roman, Alejandro
    Heredia, Sergio
    Windle, Anna E.
    Tovar-Sanchez, Antonio
    Navarro, Gabriel
    REMOTE SENSING, 2024, 16 (02)
  • [14] Detecting White Cotton Bolls Using High-Resolution Aerial Imagery Acquired Through Unmanned Aerial System
    Xu, Zhongjian
    Latif, Muhammad Ahsan
    Madni, Syed Shaham
    Rafiq, Ammar
    Alam, Iqbal
    Habib, Muhammad Asif
    IEEE ACCESS, 2021, 9 : 169068 - 169081
  • [15] Machine Learning for Precision Agriculture Using Imagery from Unmanned Aerial Vehicles (UAVs): A Survey
    Zualkernan, Imran
    Abuhani, Diaa Addeen
    Hussain, Maya Haj
    Khan, Jowaria
    ElMohandes, Mohamed
    DRONES, 2023, 7 (06)
  • [16] Development of a high-resolution aerial remote-sensing system for precision agriculture
    Bagheri, Nikrooz
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2017, 38 (8-10) : 2053 - 2065
  • [17] Optimal Collection of High Resolution Aerial Imagery with Unmanned Aerial Systems
    Stark, Brandon
    Chen, YangQuan
    2014 INTERNATIONAL CONFERENCE ON UNMANNED AIRCRAFT SYSTEMS (ICUAS), 2014, : 89 - 94
  • [18] Phenological analysis of unmanned aerial vehicle based time series of barley imagery with high temporal resolution
    A. Burkart
    V. L. Hecht
    T. Kraska
    U. Rascher
    Precision Agriculture, 2018, 19 : 134 - 146
  • [19] Mapping intertidal oyster farms using unmanned aerial vehicles (UAV) high-resolution multispectral data
    Roman, Alejandro
    Prasyad, Hermansyah
    Oiry, Simon
    Davies, Bede F. R.
    Brunier, Guillaume
    Barille, Laurent
    ESTUARINE COASTAL AND SHELF SCIENCE, 2023, 291
  • [20] Phenological analysis of unmanned aerial vehicle based time series of barley imagery with high temporal resolution
    Burkart, A.
    Hecht, V. L.
    Kraska, T.
    Rascher, U.
    PRECISION AGRICULTURE, 2018, 19 (01) : 134 - 146