IDEAS home Printed from https://ideas.repec.org/a/gam/jdataj/v8y2023i6p98-d1159692.html
   My bibliography  Save this article

Unmanned Aerial Vehicle (UAV) and Spectral Datasets in South Africa for Precision Agriculture

Author

Listed:
  • Cilence Munghemezulu

    (Agricultural Research Council—Natural Resources and Engineering, Private Bag X79, Pretoria 0001, South Africa)

  • Zinhle Mashaba-Munghemezulu

    (Agricultural Research Council—Natural Resources and Engineering, Private Bag X79, Pretoria 0001, South Africa)

  • Phathutshedzo Eugene Ratshiedana

    (Agricultural Research Council—Natural Resources and Engineering, Private Bag X79, Pretoria 0001, South Africa)

  • Eric Economon

    (Agricultural Research Council—Natural Resources and Engineering, Private Bag X79, Pretoria 0001, South Africa)

  • George Chirima

    (Agricultural Research Council—Natural Resources and Engineering, Private Bag X79, Pretoria 0001, South Africa)

  • Sipho Sibanda

    (Agricultural Research Council—Natural Resources and Engineering, Private Bag X79, Pretoria 0001, South Africa)

Abstract

Remote sensing data play a crucial role in precision agriculture and natural resource monitoring. The use of unmanned aerial vehicles (UAVs) can provide solutions to challenges faced by farmers and natural resource managers due to its high spatial resolution and flexibility compared to satellite remote sensing. This paper presents UAV and spectral datasets collected from different provinces in South Africa, covering different crops at the farm level as well as natural resources. UAV datasets consist of five multispectral bands corrected for atmospheric effects using the PIX4D mapper software to produce surface reflectance images. The spectral datasets are filtered using a Savitzky–Golay filter, corrected for Multiplicative Scatter Correction (MSC). The first and second derivatives and the Continuous Wavelet Transform (CWT) spectra are also calculated. These datasets can provide baseline information for developing solutions for precision agriculture and natural resource challenges. For example, UAV and spectral data of different crop fields captured at spatial and temporal resolutions can contribute towards calibrating satellite images, thus improving the accuracy of the derived satellite products.

Suggested Citation

  • Cilence Munghemezulu & Zinhle Mashaba-Munghemezulu & Phathutshedzo Eugene Ratshiedana & Eric Economon & George Chirima & Sipho Sibanda, 2023. "Unmanned Aerial Vehicle (UAV) and Spectral Datasets in South Africa for Precision Agriculture," Data, MDPI, vol. 8(6), pages 1-14, May.
    • Handle: RePEc:gam:jdataj:v:8:y:2023:i:6:p:98-:d:1159692
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2306-5729/8/6/98/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2306-5729/8/6/98/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kathryn Elmer & Raymond J. Soffer & J. Pablo Arroyo-Mora & Margaret Kalacska, 2020. "ASDToolkit: A Novel MATLAB Processing Toolbox for ASD Field Spectroscopy Data," Data, MDPI, vol. 5(4), pages 1-15, October.
    2. Parthasarathy Velusamy & Santhosh Rajendran & Rakesh Kumar Mahendran & Salman Naseer & Muhammad Shafiq & Jin-Ghoo Choi, 2021. "Unmanned Aerial Vehicles (UAV) in Precision Agriculture: Applications and Challenges," Energies, MDPI, vol. 15(1), pages 1-19, December.
    3. Maria C. Torres-Madronero & Manuel Goez & Manuel A. Guzman & Tatiana Rondon & Pablo Carmona & Camilo Acevedo-Correa & Santiago Gomez-Ortega & Mariana Durango-Flórez & Smith V. López & July Galeano & M, 2022. "Spectral Library of Maize Leaves under Nitrogen Deficiency Stress," Data, MDPI, vol. 8(1), pages 1-10, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohammed Al-Naeem & M M Hafizur Rahman & Anuradha Banerjee & Abu Sufian, 2023. "Support Vector Machine-Based Energy Efficient Management of UAV Locations for Aerial Monitoring of Crops over Large Agriculture Lands," Sustainability, MDPI, vol. 15(8), pages 1-17, April.
    2. Yi Liu & Tiezhu Shi & Zeying Lan & Kai Guo & Dachang Zhuang & Xiangyang Zhang & Xiaojin Liang & Tianqi Qiu & Shengfei Zhang & Yiyun Chen, 2024. "Estimating the Soil Copper Content of Urban Land in a Megacity Using Piecewise Spectral Pretreatment," Land, MDPI, vol. 13(4), pages 1-21, April.
    3. Mario Lillo-Saavedra & Alberto Espinoza-Salgado & Angel García-Pedrero & Camilo Souto & Eduardo Holzapfel & Consuelo Gonzalo-Martín & Marcelo Somos-Valenzuela & Diego Rivera, 2022. "Early Estimation of Tomato Yield by Decision Tree Ensembles," Agriculture, MDPI, vol. 12(10), pages 1-13, October.
    4. Barbara Dobosz & Dariusz Gozdowski & Jerzy Koronczok & Jan Žukovskis & Elżbieta Wójcik-Gront, 2023. "Evaluation of Maize Crop Damage Using UAV-Based RGB and Multispectral Imagery," Agriculture, MDPI, vol. 13(8), pages 1-14, August.
    5. Coraline Wyard & Rodolphe Marion & Eric Hallot, 2023. "WaRM: A Roof Material Spectral Library for Wallonia, Belgium," Data, MDPI, vol. 8(3), pages 1-12, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jdataj:v:8:y:2023:i:6:p:98-:d:1159692. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.