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Time of day impact on mapping agricultural subsurface drainage systems with UAV thermal infrared imagery

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  • Allred, Barry
  • Martinez, Luis
  • Fessehazion, Melake K.
  • Rouse, Greg
  • Koganti, Triven
  • Freeland, Robert
  • Eash, Neal
  • Wishart, DeBonne
  • Featheringill, Robert

Abstract

Due to economic and environmental considerations, there exists a need for effective, efficient, and nondestructive methods for locating buried agricultural drainage pipes. Previous research indicates that thermal infrared (TIR) imagery obtained with an unmanned aerial vehicle (UAV) has potential for mapping agricultural subsurface drainage systems, thereby warranting further investigation to determine the best time of day to conduct these UAV TIR surveys. Accordingly, a set of sunrise to sunset UAV TIR surveys were carried out at four different farm field sites in Ohio, U.S.A. Late morning through late afternoon UAV TIR surveys were generally found to work well for determining drainage system patterns. During late morning through late afternoon, the apparent radiant temperature of the soil surface over the drain lines was higher than between the drain lines (i.e., emitted TIR radiation from the soil surface over a drain line was greater than between the drain lines). Conversely, near sunrise or sunset, the UAV surveys often showed the apparent radiant temperature of the soil surface over the drain lines to be lower than between the drain lines (i.e., less emitted TIR radiation over the drain lines than between drain lines). Some excellent UAV TIR drainage mapping results were obtained near sunrise/sunset due to TIR drain line responses that were more easily distinguished from those of farm field operations. However, difficulties were occasionally encountered processing this sunrise/sunset TIR imagery, likely due to the impact on image quality from high relative humidity during these times of the day. Consequently, strictly on a consistency of success basis alone, late morning through late afternoon are the best times for locating drainage pipes with UAV TIR surveys; however, in certain cases, UAV TIR surveys at sunrise/sunset can provide exceptional drainage pattern recognition. These results provide valuable guidance for those considering UAV TIR drainage mapping surveys.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:agiwat:v:256:y:2021:i:c:s037837742100336x
    DOI: 10.1016/j.agwat.2021.107071
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    References listed on IDEAS

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    1. 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.
    2. 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).
    3. 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.
    4. 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.
    5. 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).
    6. Lenka Tlapáková & Jiří Žaloudík & Jaromír Kolejka, 2017. "Thematic survey of subsurface drainage systems in the Czech Republic," Journal of Maps, Taylor & Francis Journals, vol. 13(2), pages 55-65, November.
    7. 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.
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    Cited by:

    1. 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).
    2. 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).

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