IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v197y2018icp132-137.html
   My bibliography  Save this article

Effective and efficient agricultural drainage pipe mapping with UAS thermal infrared imagery: A case study

Author

Listed:
  • Allred, Barry
  • Eash, Neal
  • Freeland, Robert
  • Martinez, Luis
  • Wishart, DeBonne

Abstract

Effective and efficient methods are needed to map agricultural subsurface drainage systems. Visible (VIS), near infrared (NIR), and thermal infrared (TIR) imagery obtained by unmanned aircraft systems (UAS) may provide a means for determining drainage pipe locations. Preliminary UAS surveys with VIS, NIR, and TIR sensors were carried out at a farm field test site in central Ohio (U.S.A). During the UAS surveys, the soil surface was very dry (less than 5mm of rainfall the previous week, soil surface volumetric water content below 16%, and soil surface temperature above 33°C), and the ground was partially covered with past growing season crop residue and existing early growth stage corn/soybeans. Under these field conditions, drainage pipes were not detected with the VIS and NIR imagery. Conversely, the TIR image detected roughly 60% of the subsurface drainage infrastructure known to be present. Consequently, TIR imagery from UAS surveys was found to have considerable potential for drainage pipe mapping purposes, and compared to VIS and NIR imagery, may be better suited for detecting drain line locations under dry surface conditions. However, more evaluation of VIS, NIR, and TIR imagery for drainage pipe mapping is certainly needed under different soil wetness/dryness conditions and at a number of test sites having different types of soil and drainage system characteristics.

Suggested Citation

  • Allred, Barry & Eash, Neal & Freeland, Robert & Martinez, Luis & Wishart, DeBonne, 2018. "Effective and efficient agricultural drainage pipe mapping with UAS thermal infrared imagery: A case study," Agricultural Water Management, Elsevier, vol. 197(C), pages 132-137.
  • Handle: RePEc:eee:agiwat:v:197:y:2018:i:c:p:132-137
    DOI: 10.1016/j.agwat.2017.11.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377417303633
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.agwat.2017.11.011?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Naz, B.S. & Ale, S. & Bowling, L.C., 2009. "Detecting subsurface drainage systems and estimating drain spacing in intensively managed agricultural landscapes," Agricultural Water Management, Elsevier, vol. 96(4), pages 627-637, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Allred, Barry & Martinez, Luis & Khanal, Sami & Sawyer, Audrey H. & Rouse, Greg, 2022. "Subsurface drainage outlet detection in ditches and streams with UAV thermal infrared imagery: Preliminary research," Agricultural Water Management, Elsevier, vol. 271(C).
    2. Allred, Barry & Martinez, Luis & Fessehazion, Melake K. & Rouse, Greg & Koganti, Triven & Freeland, Robert & Eash, Neal & Wishart, DeBonne & Featheringill, Robert, 2021. "Time of day impact on mapping agricultural subsurface drainage systems with UAV thermal infrared imagery," Agricultural Water Management, Elsevier, vol. 256(C).
    3. Li Zhao & Tong Heng & Lili Yang & Xuan Xu & Yue Feng, 2021. "Study on the Farmland Improvement Effect of Drainage Measures under Film Mulch with Drip Irrigation in Saline–Alkali Land in Arid Areas," Sustainability, MDPI, vol. 13(8), pages 1-18, April.
    4. Allred, Barry & Martinez, Luis & Fessehazion, Melake K. & Rouse, Greg & Williamson, Tanja N. & Wishart, DeBonne & Koganti, Triven & Freeland, Robert & Eash, Neal & Batschelet, Adam & Featheringill, Ro, 2020. "Overall results and key findings on the use of UAV visible-color, multispectral, and thermal infrared imagery to map agricultural drainage pipes," Agricultural Water Management, Elsevier, vol. 232(C).
    5. Puppala, Harish & Peddinti, Pranav R.T. & Tamvada, Jagannadha Pawan & Ahuja, Jaya & Kim, Byungmin, 2023. "Barriers to the adoption of new technologies in rural areas: The case of unmanned aerial vehicles for precision agriculture in India," Technology in Society, Elsevier, vol. 74(C).
    6. Kratt, C.B. & Woo, D.K. & Johnson, K.N. & Haagsma, M. & Kumar, P. & Selker, J. & Tyler, S., 2020. "Field trials to detect drainage pipe networks using thermal and RGB data from unmanned aircraft," Agricultural Water Management, Elsevier, vol. 229(C).
    7. Woo, Dong Kook & Song, Homin & Kumar, Praveen, 2019. "Mapping subsurface tile drainage systems with thermal images," Agricultural Water Management, Elsevier, vol. 218(C), pages 94-101.
    8. Barry Allred & DeBonne Wishart & Luis Martinez & Harry Schomberg & Steven Mirsky & George Meyers & John Elliott & Christine Charyton, 2018. "Delineation of Agricultural Drainage Pipe Patterns Using Ground Penetrating Radar Integrated with a Real-Time Kinematic Global Navigation Satellite System," Agriculture, MDPI, vol. 8(11), pages 1-14, October.

    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. Woo, Dong Kook & Song, Homin & Kumar, Praveen, 2019. "Mapping subsurface tile drainage systems with thermal images," Agricultural Water Management, Elsevier, vol. 218(C), pages 94-101.
    2. Allred, Barry & Martinez, Luis & Fessehazion, Melake K. & Rouse, Greg & Koganti, Triven & Freeland, Robert & Eash, Neal & Wishart, DeBonne & Featheringill, Robert, 2021. "Time of day impact on mapping agricultural subsurface drainage systems with UAV thermal infrared imagery," Agricultural Water Management, Elsevier, vol. 256(C).
    3. Woo, Dong Kook & Ji, Junghu & Song, Homin, 2023. "Subsurface drainage pipe detection using an ensemble learning approach and aerial images," Agricultural Water Management, Elsevier, vol. 287(C).
    4. Ale, S. & Bowling, L.C. & Owens, P.R. & Brouder, S.M. & Frankenberger, J.R., 2012. "Development and application of a distributed modeling approach to assess the watershed-scale impact of drainage water management," Agricultural Water Management, Elsevier, vol. 107(C), pages 23-33.
    5. Song, Homin & Woo, Dong Kook & Yan, Qina, 2021. "Detecting subsurface drainage pipes using a fully convolutional network with optical images," Agricultural Water Management, Elsevier, vol. 249(C).
    6. Allred, Barry & Martinez, Luis & Fessehazion, Melake K. & Rouse, Greg & Williamson, Tanja N. & Wishart, DeBonne & Koganti, Triven & Freeland, Robert & Eash, Neal & Batschelet, Adam & Featheringill, Ro, 2020. "Overall results and key findings on the use of UAV visible-color, multispectral, and thermal infrared imagery to map agricultural drainage pipes," Agricultural Water Management, Elsevier, vol. 232(C).
    7. Tlapáková Lenka, 2017. "Development of drainage system in the Czech landscape – identification and functionality assessment by means of remote sensing," European Countryside, Sciendo, vol. 9(1), pages 77-98, March.
    8. Kratt, C.B. & Woo, D.K. & Johnson, K.N. & Haagsma, M. & Kumar, P. & Selker, J. & Tyler, S., 2020. "Field trials to detect drainage pipe networks using thermal and RGB data from unmanned aircraft," Agricultural Water Management, Elsevier, vol. 229(C).

    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:eee:agiwat:v:197:y:2018:i:c:p:132-137. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    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.