Universität zu Köln

Tilly, Nora ORCID: 0000-0002-2978-6188 and Bareth, Georg (2019). Estimating Nitrogen from Structural Crop Traits at Field Scale-A Novel Approach Versus Spectral Vegetation Indices. Remote Sens., 11 (17). BASEL: MDPI. ISSN 2072-4292

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Abstract

A sufficient nitrogen (N) supply is mandatory for healthy crop growth, but negative consequences of N losses into the environment are known. Hence, deeply understanding and monitoring crop growth for an optimized N management is advisable. In this context, remote sensing facilitates the capturing of crop traits. While several studies on estimating biomass from spectral and structural data can be found, N is so far only estimated from spectral features. It is well known that N is negatively related to dry biomass, which, in turn, can be estimated from crop height. Based on this indirect link, the present study aims at estimating N concentration at field scale in a two-step model: first, using crop height to estimate biomass, and second, using the modeled biomass to estimate N concentration. For comparison, N concentration was estimated from spectral data. The data was captured on a spring barley field experiment in two growing seasons. Crop surface height was measured with a terrestrial laser scanner, seven vegetation indices were calculated from field spectrometer measurements, and dry biomass and N concentration were destructively sampled. In the validation, better results were obtained with the models based on structural data (R-2 < 0.85) than on spectral data (R-2 < 0.70). A brief look at the N concentration of different plant organs showed stronger dependencies on structural data (R-2: 0.40-0.81) than on spectral data (R-2: 0.18-0.68). Overall, this first study shows the potential of crop-specific across-season two-step models based on structural data for estimating crop N concentration at field scale. The validity of the models for in-season estimations requires further research.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Tilly, Nora UNSPECIFIED orcid.org/0000-0002-2978-6188 UNSPECIFIED Bareth, Georg UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-142548
DOI:	10.3390/rs11172066
Journal or Publication Title:	Remote Sens.
Volume:	11
Number:	17
Date:	2019
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 PLANT HEIGHT; CHLOROPHYLL CONTENT; YIELD PREDICTION; USE EFFICIENCY; CANOPY HEIGHT; GROWTH-STAGES; WINTER-WHEAT; PADDY RICE; BIOMASS; LEAF Multiple languages Remote Sensing Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/14254