Estimating vertical plant area density profile and growth parameters of a wheat canopy at different growth stages using three-dimensional portable lidar imaging

Hosoi, Fumiki; Omasa, Kenji

doi:10.1016/j.isprsjprs.2008.09.003

Cited by 137 publications

(100 citation statements)

References 60 publications

(71 reference statements)

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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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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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“…In-situ studies confirmed the potential of ground-based LIDAR methods, also known as terrestrial laser scanning (TLS), for the assessment of plant parameters in agricultural applications. Previous studies focused on the acquisition of plant height [25], post-harvest growth [26], leaf area index [27], crop density [28,29], nitrogen status [30], or the detection of individual plants [31,32]. Moreover, the potential of TLS for estimating the biomass of small-grain cereals was emphasized [33][34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Transferability of Models for Estimating Paddy Rice Biomass from Spatial Plant Height Data

et al. 2015

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It is known that plant height is a suitable parameter for estimating crop biomass. The aim of this study was to confirm the validity of spatial plant height data, which is derived from terrestrial laser scanning (TLS), as a non-destructive estimator for biomass of paddy rice on the field scale. Beyond that, the spatial and temporal transferability of established biomass regression models were investigated to prove the robustness of the method and evaluate the suitability of linear and exponential functions. In each growing season of two years, three campaigns were carried out on a field experiment and on a farmer's conventionally managed field. Crop surface models (CSMs) were generated from the TLS-derived point clouds for calculating plant height with a very high spatial resolution of 1 cm. High coefficients of determination between CSM-derived and manually measured plant heights (R 2 : 0.72 to 0.91) confirm the applicability of the approach. Yearly averaged differences between the measurements were ~7% and ~9%. Biomass regression models were established from the field experiment data sets, based on strong coefficients of determination between plant height and dry biomass (R : 0.60 to 0.90 and 0.56 to 0.85 for linear and exponential models, respectively). Hence, the suitability of TLS-derived spatial plant height as a non-destructive estimator for biomass of paddy rice on the field scale was verified and the transferability demonstrated.

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“…Several crops were already investigated with ground-based LIDAR approaches for various purposes like determining plant height (Zhang and Grift, 2012) and estimating biomass (Keightley and Bawden, 2010;Ehlert et al, 2009;, crop density (Hosoi and Omasa, 2009;Saeys et al, 2009), or leaf area index (Gebbers et al, 2011). Furthermore, analysis of the measured intensity values can lead to the detection of single plants of maize (Höfle, 2013) or sugar beet .…”

Section: Introductionmentioning

confidence: 99%

Precise plant height monitoring and biomass estimation with Terrestrial Laser Scanning in paddy rice

Tilly

Hoffmeister

Cao

et al. 2013

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Optimizing crop management is a major topic in the field of precision agriculture as the growing world population puts pressure on the efficiency of field production. Accordingly, methods to measure plant parameters with the needed precision and within-field resolution are required. Studies show that Terrestrial Laser Scanning (TLS) is a suitable method to capture small objects like crop plants. In this contribution, the results of multi-temporal surveys on paddy rice fields with the TLS system Riegl LMS-Z420i are presented. Three campaigns were carried out during the key vegetative stage of rice plants in the growing period 2012 to monitor the plant height. The TLS-derived point clouds are interpolated to visualize plant height above ground as crop surface models (CSMs) with a high resolution of 0.01 m. Spatio-temporal differences within the data of one campaign and between consecutive campaigns can be detected. The results were validated against manually measured plant heights with a high correlation (R² = 0.71). Furthermore, the dependence of actual biomass from plant height was evaluated. To the present, no method for the non-destructive determination of biomass is found yet. Thus, plant parameters, like the height, have to be used for biomass estimations. The good correlation (R² = 0.66) leads to the assumption that biomass can be estimated from plant height measurements. The results show that TLS can be considered as a very promising tool for precision agriculture.

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Estimating vertical plant area density profile and growth parameters of a wheat canopy at different growth stages using three-dimensional portable lidar imaging

Cited by 137 publications

References 60 publications

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

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

Transferability of Models for Estimating Paddy Rice Biomass from Spatial Plant Height Data

Precise plant height monitoring and biomass estimation with Terrestrial Laser Scanning in paddy rice

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