Measuring crop biomass density by laser triangulation

Ehlert, Detlef; Horn, H. J.; Adamek, Rolf

doi:10.1016/j.compag.2007.09.013

Cited by 86 publications

(45 citation statements)

References 7 publications

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“…Cressy site results with a single campaign provide R 2 of 0.972, in accordance with a previous study [11]. Results with two flights showed higher R 2 of 0.988, in accordance with other findings [55]. Overall, the RMSE also varied depending on topography.…”

Section: Discussionsupporting

confidence: 91%

Poppy Crop Height and Capsule Volume Estimation from a Single UAS Flight

et al. 2017

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Abstract:The objective of this study was to estimate poppy plant height and capsule volume with remote sensing using an Unmanned Aircraft System (UAS). Data were obtained from field measurements and UAS flights over two poppy crops at Cambridge and Cressy in Tasmania. Imagery acquired from the UAS was used to produce dense point clouds using structure from motion (SfM) and multi-view stereopsis (MVS) techniques. Dense point clouds were used to generate a digital surface model (DSM) and orthophoto mosaic. An RGB index was derived from the orthophoto to extract the bare ground spaces. This bare ground space mask was used to filter the points on the ground, and a digital terrain model (DTM) was interpolated from these points. Plant height values were estimated by subtracting the DSM and DTM to generate a Crop Height Model (CHM). UAS-derived plant height (PH) and field measured PH in Cambridge were strongly correlated with R 2 values ranging from 0.93 to 0.97 for Transect 1 and Transect 2, respectively, while at Cressy results from a single flight provided R 2 of 0.97. Therefore, the proposed method can be considered an important step towards crop surface model (CSM) generation from a single UAS flight in situations where a bare ground DTM is unavailable. High correlations were found between UAS-derived PH and poppy capsule volume (CV) at capsule formation stage (R 2 0.74), with relative error of 19.62%. Results illustrate that plant height can be reliably estimated for poppy crops based on a single UAS flight and can be used to predict opium capsule volume at capsule formation stage.

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Section: Discussionsupporting

confidence: 91%

Poppy Crop Height and Capsule Volume Estimation from a Single UAS Flight

et al. 2017

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“…The height of the vegetation canopy has been used to measure plant volume and to infer biomass with success in the past [11,12,[22][23][24][25][26]. Of particular interest is the work by King et al [22], who reported that the sward height was linearly related to both the LAI and biomass over a range of 2 cm to 8 cm in two ryegrass dominant swards.…”

Section: Introductionmentioning

confidence: 99%

A Combination of Plant NDVI and LiDAR Measurements Improve the Estimation of Pasture Biomass in Tall Fescue (Festuca arundinacea var. Fletcher)

Schaefer

Lamb

2016

Remote Sensing

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Abstract:The total biomass of a tall fescue (Festuca arundinacea var. Fletcher) pasture was assessed by using a vehicle mounted light detection and ranging (LiDAR) unit to derive canopy height and an active optical reflectance sensor to determine the spectro-optical reflectance index, normalized difference vegetation index (NDVI). In a random plot design, measurements of NDVI and pasture height were combined to estimate biomass with a root mean square error of prediction (RMSEP) equal to˘455.28 kg green dry matter (GDM)/ha, over a range of 286 kg to 3933 kg GDM/ha. The combination of NDVI and height measurements were observed to be more accurate in assessing total biomass than just the NDVI (RMSEP˘846.51 kg/ha) and height (RMSEP˘708.13 kg/ha). Based on the results of the study it was concluded the use of combined LiDAR and active optical reflectance sensors can help unlock the complex interrelationship between green fraction and biomass in swards containing both green and senescent material.

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“…By contrast, studies show that terrestrial laser scanning (TLS), as an active system, can be applied for agricultural purposes. Investigated plant parameters are plant height (Zhang and Grift, 2012), biomass (Keightley and Bawden, 2010;Ehlert et al, 2009;2008), crop density (Hosoi and Omasa, * Corresponding author: nora.tilly@uni-koeln.de 2012;Saeys et al, 2009), and leaf area index (Gebbers et al, 2011). As mentioned the large height of maize plants causes difficulties for ground based system.…”

Section: Introductionmentioning

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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Measuring crop biomass density by laser triangulation

Cited by 86 publications

References 7 publications

Poppy Crop Height and Capsule Volume Estimation from a Single UAS Flight

Poppy Crop Height and Capsule Volume Estimation from a Single UAS Flight

A Combination of Plant NDVI and LiDAR Measurements Improve the Estimation of Pasture Biomass in Tall Fescue (Festuca arundinacea var. Fletcher)

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

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