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Open AccessArticle

Quantifying Lodging Percentage and Lodging Severity Using a UAV-Based Canopy Height Model Combined with an Objective Threshold Approach

1
Institute of Bio- and Geosciences, Plant Sciences (IBG-2), Forschungszentrum Jülich GmbH, 52428 Jülich, Germany
2
Department of Geodesy, University of Bonn, 53115 Bonn, Germany
3
JB Hyperspectral Devices UG, 40225 Düsseldorf, Germany
4
Field Lab Campus Klein, Altendorf, University of Bonn, 53359 Rheinbach, Germany
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(5), 515; https://doi.org/10.3390/rs11050515
Received: 31 January 2019 / Revised: 26 February 2019 / Accepted: 27 February 2019 / Published: 3 March 2019
Unmanned aerial vehicles (UAVs) open new opportunities in precision agriculture and phenotyping because of their flexibility and low cost. In this study, the potential of UAV imagery was evaluated to quantify lodging percentage and lodging severity of barley using structure from motion (SfM) techniques. Traditionally, lodging quantification is based on time-consuming manual field observations. Our UAV-based approach makes use of a quantitative threshold to determine lodging percentage in a first step. The derived lodging estimates showed a very high correlation to reference data (R2 = 0.96, root mean square error (RMSE) = 7.66%) when applied to breeding trials, which could also be confirmed under realistic farming conditions. As a second step, an approach was developed that allows the assessment of lodging severity, information that is important to estimate yield impairment, which also takes the intensity of lodging events into account. Both parameters were tested on three ground sample distances. The lowest spatial resolution acquired from the highest flight altitude (100 m) still led to high accuracy, which increases the practicability of the method for large areas. Our new lodging assessment procedure can be used for insurance applications, precision farming, and selecting for genetic lines with greater lodging resistance in breeding research. View Full-Text
Keywords: precision agriculture; remote sensing; unmanned aerial vehicles (UAVs); structure from motion; ground model; digital terrain model; plant height; canopy height model; lodging percentage and severity; ground sample distance influence precision agriculture; remote sensing; unmanned aerial vehicles (UAVs); structure from motion; ground model; digital terrain model; plant height; canopy height model; lodging percentage and severity; ground sample distance influence
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MDPI and ACS Style

Wilke, N.; Siegmann, B.; Klingbeil, L.; Burkart, A.; Kraska, T.; Muller, O.; van Doorn, A.; Heinemann, S.; Rascher, U. Quantifying Lodging Percentage and Lodging Severity Using a UAV-Based Canopy Height Model Combined with an Objective Threshold Approach. Remote Sens. 2019, 11, 515. https://doi.org/10.3390/rs11050515

AMA Style

Wilke N, Siegmann B, Klingbeil L, Burkart A, Kraska T, Muller O, van Doorn A, Heinemann S, Rascher U. Quantifying Lodging Percentage and Lodging Severity Using a UAV-Based Canopy Height Model Combined with an Objective Threshold Approach. Remote Sensing. 2019; 11(5):515. https://doi.org/10.3390/rs11050515

Chicago/Turabian Style

Wilke, Norman; Siegmann, Bastian; Klingbeil, Lasse; Burkart, Andreas; Kraska, Thorsten; Muller, Onno; van Doorn, Anna; Heinemann, Sascha; Rascher, Uwe. 2019. "Quantifying Lodging Percentage and Lodging Severity Using a UAV-Based Canopy Height Model Combined with an Objective Threshold Approach" Remote Sens. 11, no. 5: 515. https://doi.org/10.3390/rs11050515

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