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

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  • 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
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    References listed on IDEAS

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    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.
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    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. Carlsen, Ask Holm & Fensholt, Rasmus & Looms, Majken Caroline & Gominski, Dimitri & Stisen, Simon & Jepsen, Martin Rudbeck, 2024. "Systematic review of the detection of subsurface drainage systems in agricultural fields using remote sensing systems," Agricultural Water Management, Elsevier, vol. 299(C).
    7. 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).
    8. 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.
    9. 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.

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