Universität zu Köln

Brocks, Sebastian ORCID: 0000-0003-2332-8896 and Bareth, Georg (2018). Estimating Barley Biomass with Crop Surface Models from Oblique RGB Imagery. Remote Sens., 10 (2). BASEL: MDPI. ISSN 2072-4292

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Abstract

Non-destructive monitoring of crop development is of key interest for agronomy and crop breeding. Crop Surface Models (CSMs) representing the absolute height of the plant canopy are a tool for this. In this study, fresh and dry barley biomass per plot are estimated from CSM-derived plot-wise plant heights. The CSMs are generated in a semi-automated manner using Structure-from-Motion (SfM)/Multi-View-Stereo (MVS) software from oblique stereo RGB images. The images were acquired automatedly from consumer grade smart cameras mounted at an elevated position on a lifting hoist. Fresh and dry biomass were measured destructively at four dates each in 2014 and 2015. We used exponential and simple linear regression based on different calibration/validation splits. Coefficients of determination between 0.55 and 0.79 and root mean square errors (RMSE) between 97 and 234 g/m(2) are reached for the validation of predicted vs. observed dry biomass, while Willmott's refined index of model performance ranges between 0.59 and 0.77. For fresh biomass, values between 0.34 and 0.61 are reached, with root mean square errors (RMSEs) between 312 and 785 g/m(2) and between 0.39 and 0.66. We therefore established the possibility of using this novel low-cost system to estimate barley dry biomass over time.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Brocks, Sebastian UNSPECIFIED orcid.org/0000-0003-2332-8896 UNSPECIFIED Bareth, Georg UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-197102
DOI:	10.3390/rs10020268
Journal or Publication Title:	Remote Sens.
Volume:	10
Number:	2
Date:	2018
Publisher:	MDPI
Place of Publication:	BASEL
ISSN:	2072-4292
Language:	English
Faculty:	Faculty of Mathematics and Natural Sciences
Divisions:	Faculty of Mathematics and Natural Sciences > Department of Geosciences
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language UNMANNED AERIAL VEHICLE; PLANT HEIGHT; FIELD; UAV; CAMERAS; TRAITS; SYSTEM; GROWTH; SCALE Multiple languages Remote Sensing Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/19710