Sources of angle-dependent errors in terrestrial laser scanner-based crop stand measurement

Ehlert, Detlef; Heisig, Michael

doi:10.1016/j.compag.2013.01.002

Cited by 32 publications

(25 citation statements)

References 11 publications

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“…However, uncertainties still remain about the influence of the scanning angle and the fixed position of the scanner during the measurements. As maintained by Ehlert and Heisig [62]-the scanning angle can cause overestimations in the height of reflection points and should be considered in the calculation of heights. In this study, the crop surface was determined from the merged and cleaned point clouds of four scan positions, filtered with a scheme for selecting maximum points.…”

Section: Tls-derived Plant Heightmentioning

confidence: 99%

Fusion of Plant Height and Vegetation Indices for the Estimation of Barley Biomass

2015

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Plant biomass is an important parameter for crop management and yield estimation. However, since biomass cannot be determined non-destructively, other plant parameters are used for estimations. In this study, plant height and hyperspectral data were used for barley biomass estimations with bivariate and multivariate models. During three consecutive growing seasons a terrestrial laser scanner was used to establish crop surface models for a pixel-wise calculation of plant height and manual measurements of plant height confirmed the results (R 2 up to 0.98). Hyperspectral reflectance measurements were conducted with a field spectrometer and used for calculating six vegetation indices (VIs), which have been found to be related to biomass and LAI: GnyLi, NDVI, NRI, RDVI, REIP, and RGBVI. Furthermore, biomass samples were destructively taken on almost the same dates. Linear and exponential biomass regression models (BRMs) were established for evaluating plant height and VIs as estimators of fresh and dry biomass. Each BRM was established for the whole observed period and pre-anthesis, which is important for management decisions. Bivariate BRMs supported plant height as a strong estimator (R 2 up to 0.85), whereas BRMs based on individual VIs showed varying performances (R 2 : 0.07-0.87). Fused approaches, where plant height and one VI were used for establishing multivariate BRMs, yielded improvements in some cases (R 2 up to 0.89). Overall, this study reveals the potential of remotely-sensed plant parameters for estimations of barley biomass. Moreover, it is a first step towards the fusion of 3D spatial and spectral measurements for improving non-destructive biomass estimations. OPEN ACCESSRemote Sens. 2015, 7 11450

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Section: Tls-derived Plant Heightmentioning

confidence: 99%

Fusion of Plant Height and Vegetation Indices for the Estimation of Barley Biomass

2015

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“…11,12 In a previous study of plant height determination, Ehlert et al [13][14][15] proposed an approach of observing plant height in flat areas with a known ground level. The laser scanner is mounted on a tool carrier with an inclination angle (φ) to observe the plant from above.…”

Section: Introductionmentioning

confidence: 99%

Method for estimating rice plant height without ground surface detection using laser scanner measurement

Phan

Takahashi

Rikimaru

et al. 2016

J. Appl. Remote Sens

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, "Method for estimating rice plant height without ground surface detection using laser scanner measurement," J. Appl. Remote Sens. 10(4), 046018 (2016), doi: 10.1117/1.JRS.10.046018. Relative vertical distances (rD) were computed from the difference between the top and bottom positions of the rice plant. These correlated well with measured H, with slopes greater than 1.0. A greater number of stems in 2014 led to steeper slopes. Estimated H was more accurate when plant bottom positions were closer to the ground surface, and the best results were obtained with p b ¼ 95 (r 2 > 0.87; RMSE ≈ 4 cm). Overall, H was typically 16.0 cm greater than rD with p b ¼ 95.

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“…Thus, also lower parts of the plants are captured. This influence of the scanning angles is also stated by Ehlert and Heisig (2013). However they detected overestimations in the height of reflection points.…”

Section: Discussionmentioning

confidence: 51%

“…Those systems apply a two-dimensional profiling scanners based on a moving ground vehicle for achieving an areal coverage. Conceivable MLS approaches are presented by Ehlert and Heisig (2013) and Kukko et al (2012).…”

Section: Discussionmentioning

confidence: 99%

Terrestrial laser scanning for plant height measurement and biomass estimation of maize

Tilly

Hoffmeister

Schiedung

et al. 2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Over the last decades, the role of remote sensing gained in importance for monitoring applications in precision agriculture. A key factor for assessing the development of crops during the growing period is the actual biomass. As non-destructive methods of directly measuring biomass do not exist, parameters like plant height are considered as estimators. In this contribution, first results of multitemporal surveys on a maize field with a terrestrial laser scanner are shown. The achieved point clouds are interpolated to generate Crop Surface Models (CSM) that represent the top canopy. These CSMs are used for visualizing the spatial distribution of plant height differences within the field and calculating plant height above ground with a high resolution of 1 cm. In addition, manual measurements of plant height were carried out corresponding to each TLS campaign to verify the results. The high coefficient of determination (R² = 0.93) between both measurement methods shows the applicability of the presented approach. The established regression model between CSM-derived plant height and destructively measured biomass shows a varying performance depending on the considered time frame during the growing period. This study shows that TLS is a suitable and promising method for measuring plant height of maize. Moreover, it shows the potential of plant height as a non-destructive estimator for biomass in the early growing period. However, challenges are the non-linear development of plant height and biomass over the whole growing period.

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Sources of angle-dependent errors in terrestrial laser scanner-based crop stand measurement

Cited by 32 publications

References 11 publications

Fusion of Plant Height and Vegetation Indices for the Estimation of Barley Biomass

Fusion of Plant Height and Vegetation Indices for the Estimation of Barley Biomass

Method for estimating rice plant height without ground surface detection using laser scanner measurement

Terrestrial laser scanning for plant height measurement and biomass estimation of maize

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