Integration of Unmanned Aerial Vehicle and Multispectral Sensor for Paddy Growth Monitoring Application: A Review

被引:0
|
作者
Mohidem, Nur Adibah [1 ,2 ]
Jaafar, Suhami [2 ]
Che'Ya, Nik Norasma [2 ,3 ,4 ,5 ]
机构
[1] Univ Sains Islam Malaysia, Fac Med & Hlth Sci, Dept Primary Hlth Care, Publ Hlth Unit, Nilai 71800, Negeri Sembilan, Malaysia
[2] Univ Putra Malaysia, Fac Agr, Dept Agr Technol, Serdang 43400, Selangor, Malaysia
[3] Univ Putra Malaysia, Ctr Adv Lightning Power & Energy Res ALPER, Serdang 43400, Selangor, Malaysia
[4] Univ Putra Malaysia, Fac Engn, Smart Farming Technol Res Ctr SFTRC, Serdang 43400, Selangor, Malaysia
[5] Univ Putra Malaysia, Inst Plantat Studies, Lab Plantat Syst Technol & Mechanizat PSTM, Serdang 43400, Selangor, Malaysia
来源
关键词
Multispectral; normalised difference vegetation index; paddy field; soil plant analysis development; unmanned aerial vehicle; VEGETATION INDEXES; MAIZE; UAV; RICE; AREA; SOIL; AGRICULTURE; IRRIGATION; RESOLUTION; IMAGES;
D O I
10.47836/pjst.32.2.04
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Using a conventional approach via visual observation on the ground, farmers encounter difficulties monitoring the entire paddy field area, and it is time-consuming to do manually. The application of unmanned aerial vehicles (UAVs) could help farmers optimise inputs such as water and fertiliser to increase yield, productivity, and quality, allowing them to manage their operations at lower costs and with minimum environmental impact. Therefore, this article aims to provide an overview of the integration of UAV and multispectral sensors in monitoring paddy growth applications based on vegetation indices and soil plant analysis development (SPAD) data. The article briefly describes current rice production in Malaysia and a general concept of precision agriculture technologies. The application of multispectral sensors integrated with UAVs in monitoring paddy growth is highlighted. Previous research on aerial imagery derived from the multispectral sensor using the normalised difference vegetation index (NDVI) is explored to provide information regarding the health condition of the paddy. Validation of the paddy growth map using SPAD data in determining the leaf's relative chlorophyll and nitrogen content is also being discussed. Implementation of precision agriculture among low-income farmers could provide valuable insights into the practical implications of this review. With ongoing education, training and experience, farmers can eventually manage the UAV independently in the field. This article concludes with a future research direction regarding the production of growth maps for other crops using a variety of vegetation indices and map validation using the SPAD metre values.
引用
收藏
页码:521 / 550
页数:30
相关论文
共 50 条
  • [1] Unmanned Aerial Vehicle Application of Multispectral Sensor Data in Agriculture
    Han, Xintong
    Sang, Yike
    Zhao, Songling
    PROCEEDINGS OF 2024 INTERNATIONAL CONFERENCE ON MACHINE INTELLIGENCE AND DIGITAL APPLICATIONS, MIDA2024, 2024, : 205 - 211
  • [2] Crop Discrimination Using Multispectral Sensor Onboard Unmanned Aerial Vehicle
    B. K. Handique
    A. Q. Khan
    C. Goswami
    M. Prashnani
    C. Gupta
    P. L. N. Raju
    Proceedings of the National Academy of Sciences, India Section A: Physical Sciences, 2017, 87 : 713 - 719
  • [3] Crop Discrimination Using Multispectral Sensor Onboard Unmanned Aerial Vehicle
    Handique, B. K.
    Khan, A. Q.
    Goswami, C.
    Prashnani, M.
    Gupta, C.
    Raju, P. L. N.
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES INDIA SECTION A-PHYSICAL SCIENCES, 2017, 87 (04) : 713 - 719
  • [4] Study on Application of Unmanned Aerial Vehicle for Disaster Monitoring
    Chen Cheng
    Tan YueJin
    Xing LiNing
    RESEARCH JOURNAL OF CHEMISTRY AND ENVIRONMENT, 2012, 16 : 51 - 55
  • [5] Unmanned Aerial Vehicle Application for air Pollution Monitoring
    Szymocha, Slawomir
    Piwowarski, Dawid
    Anweiler, Stanislaw
    MECHATRONICS SYSTEMS AND MATERIALS 2018, 2018, 2029
  • [6] Rice nitrogen nutrition monitoring based on unmanned aerial vehicle multispectral image
    Ling Q.
    Kong F.
    Ning Q.
    Wei Y.
    Liu Z.
    Dai M.
    Zhou Y.
    Zhang Y.
    Shi X.
    Wang J.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2023, 39 (13): : 160 - 170
  • [7] Monitoring Maize Lodging Grades via Unmanned Aerial Vehicle Multispectral Image
    Sun, Qian
    Sun, Lin
    Shu, Meiyan
    Gu, Xiaohe
    Yang, Guijun
    Zhou, Longfei
    PLANT PHENOMICS, 2019, 2019
  • [8] Application Method of Unmanned Aerial Vehicle for Crop Monitoring in Korea
    Na, Sang-il
    Park, Chan-won
    So, Kyu-ho
    Ahn, Ho-yong
    Lee, Kyung-do
    KOREAN JOURNAL OF REMOTE SENSING, 2018, 34 (05) : 829 - 846
  • [9] Simulation of Reflectance and Vegetation Indices for Unmanned Aerial Vehicle (UAV) Monitoring of Paddy Fields
    Hashimoto, Naoyuki
    Saito, Yuki
    Maki, Masayasu
    Homma, Koki
    REMOTE SENSING, 2019, 11 (18)
  • [10] Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle
    Berni, Jose A. J.
    Zarco-Tejada, Pablo J.
    Suarez, Lola
    Fereres, Elias
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2009, 47 (03): : 722 - 738