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:
CreatorsEmailORCIDORCID Put Code
Tilly, NoraUNSPECIFIEDorcid.org/0000-0002-2978-6188UNSPECIFIED
Bareth, GeorgUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
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:
KeywordsLanguage
PLANT HEIGHT; CHLOROPHYLL CONTENT; YIELD PREDICTION; USE EFFICIENCY; CANOPY HEIGHT; GROWTH-STAGES; WINTER-WHEAT; PADDY RICE; BIOMASS; LEAFMultiple languages
Remote SensingMultiple languages
Refereed: Yes
URI: http://kups.ub.uni-koeln.de/id/eprint/14254

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