Frost damage assessment in wheat using spectral mixture analysis

Glenn J. Fitzgerald, Eileen M. Perry, Ken C. Flower, J. Nikolaus Callow, Bryan Boruff, Audrey Delahunty, Ashley Wallace, James Nuttall

Research output: Contribution to journalArticle

Abstract

Frost damage to broadacre crops can cause up to an 85% loss in productivity. Although growers have few options for crop protection from frost, a rapid method for assessing frost-induced sterility would allow for timely management decisions (e.g., cutting for hay and altering marketing strategies). Spectral mixture analysis (SMA) has shown success in mapping landscape components and was used with hyperspectral data collected on the canopy, heads, and leaves of wheat at different sites to determine if this could quantify frost damage. Spectral libraries were assembled from canopy components collected from local field sites to generate spectral libraries for SMA from which a series of fraction sets was derived. The frost (Fr) fraction was then used to estimate final yield as a means of measuring frost damage. The best-fitting Fr fractions to yield were derived from the same data set as the source Fr spectra, and these ranged over R2 = 0.58-0.75 at the canopy scale. It was clear that spectral signatures need to be collected at scale to assess frost damage. While Fr fractions were able to estimate yield there was no "universal" endmember set from which a Fr fraction could be derived. The normalized difference vegetation index (NDVI) was not able to estimate frost damage consistently. Future work requires determining whether there is a "universal" set of endmembers and a minimum set of targeted wavebands that could lead to multispectral instruments for frost assessment for use in ground and aerial sensors.

Original languageEnglish
Article number2476
JournalRemote Sensing
Volume11
Issue number21
DOIs
Publication statusPublished - 1 Nov 2019

Fingerprint

frost
wheat
damage
canopy
damage assessment
analysis
sterility
hay
NDVI
marketing
sensor

Cite this

Fitzgerald, G. J., Perry, E. M., Flower, K. C., Nikolaus Callow, J., Boruff, B., Delahunty, A., ... Nuttall, J. (2019). Frost damage assessment in wheat using spectral mixture analysis. Remote Sensing, 11(21), [2476]. https://doi.org/10.3390/rs11212476
Fitzgerald, Glenn J. ; Perry, Eileen M. ; Flower, Ken C. ; Nikolaus Callow, J. ; Boruff, Bryan ; Delahunty, Audrey ; Wallace, Ashley ; Nuttall, James. / Frost damage assessment in wheat using spectral mixture analysis. In: Remote Sensing. 2019 ; Vol. 11, No. 21.
@article{f4b6f6ab1ce343aca88c7a23f194f961,
title = "Frost damage assessment in wheat using spectral mixture analysis",
abstract = "Frost damage to broadacre crops can cause up to an 85{\%} loss in productivity. Although growers have few options for crop protection from frost, a rapid method for assessing frost-induced sterility would allow for timely management decisions (e.g., cutting for hay and altering marketing strategies). Spectral mixture analysis (SMA) has shown success in mapping landscape components and was used with hyperspectral data collected on the canopy, heads, and leaves of wheat at different sites to determine if this could quantify frost damage. Spectral libraries were assembled from canopy components collected from local field sites to generate spectral libraries for SMA from which a series of fraction sets was derived. The frost (Fr) fraction was then used to estimate final yield as a means of measuring frost damage. The best-fitting Fr fractions to yield were derived from the same data set as the source Fr spectra, and these ranged over R2 = 0.58-0.75 at the canopy scale. It was clear that spectral signatures need to be collected at scale to assess frost damage. While Fr fractions were able to estimate yield there was no {"}universal{"} endmember set from which a Fr fraction could be derived. The normalized difference vegetation index (NDVI) was not able to estimate frost damage consistently. Future work requires determining whether there is a {"}universal{"} set of endmembers and a minimum set of targeted wavebands that could lead to multispectral instruments for frost assessment for use in ground and aerial sensors.",
keywords = "Abiotic stress, Hyperspectral, Scaling, Spectral signature",
author = "Fitzgerald, {Glenn J.} and Perry, {Eileen M.} and Flower, {Ken C.} and {Nikolaus Callow}, J. and Bryan Boruff and Audrey Delahunty and Ashley Wallace and James Nuttall",
year = "2019",
month = "11",
day = "1",
doi = "10.3390/rs11212476",
language = "English",
volume = "11",
journal = "Default journal",
issn = "2072-4292",
publisher = "MDPI AG",
number = "21",

}

Fitzgerald, GJ, Perry, EM, Flower, KC, Nikolaus Callow, J, Boruff, B, Delahunty, A, Wallace, A & Nuttall, J 2019, 'Frost damage assessment in wheat using spectral mixture analysis' Remote Sensing, vol. 11, no. 21, 2476. https://doi.org/10.3390/rs11212476

Frost damage assessment in wheat using spectral mixture analysis. / Fitzgerald, Glenn J.; Perry, Eileen M.; Flower, Ken C.; Nikolaus Callow, J.; Boruff, Bryan; Delahunty, Audrey; Wallace, Ashley; Nuttall, James.

In: Remote Sensing, Vol. 11, No. 21, 2476, 01.11.2019.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Frost damage assessment in wheat using spectral mixture analysis

AU - Fitzgerald, Glenn J.

AU - Perry, Eileen M.

AU - Flower, Ken C.

AU - Nikolaus Callow, J.

AU - Boruff, Bryan

AU - Delahunty, Audrey

AU - Wallace, Ashley

AU - Nuttall, James

PY - 2019/11/1

Y1 - 2019/11/1

N2 - Frost damage to broadacre crops can cause up to an 85% loss in productivity. Although growers have few options for crop protection from frost, a rapid method for assessing frost-induced sterility would allow for timely management decisions (e.g., cutting for hay and altering marketing strategies). Spectral mixture analysis (SMA) has shown success in mapping landscape components and was used with hyperspectral data collected on the canopy, heads, and leaves of wheat at different sites to determine if this could quantify frost damage. Spectral libraries were assembled from canopy components collected from local field sites to generate spectral libraries for SMA from which a series of fraction sets was derived. The frost (Fr) fraction was then used to estimate final yield as a means of measuring frost damage. The best-fitting Fr fractions to yield were derived from the same data set as the source Fr spectra, and these ranged over R2 = 0.58-0.75 at the canopy scale. It was clear that spectral signatures need to be collected at scale to assess frost damage. While Fr fractions were able to estimate yield there was no "universal" endmember set from which a Fr fraction could be derived. The normalized difference vegetation index (NDVI) was not able to estimate frost damage consistently. Future work requires determining whether there is a "universal" set of endmembers and a minimum set of targeted wavebands that could lead to multispectral instruments for frost assessment for use in ground and aerial sensors.

AB - Frost damage to broadacre crops can cause up to an 85% loss in productivity. Although growers have few options for crop protection from frost, a rapid method for assessing frost-induced sterility would allow for timely management decisions (e.g., cutting for hay and altering marketing strategies). Spectral mixture analysis (SMA) has shown success in mapping landscape components and was used with hyperspectral data collected on the canopy, heads, and leaves of wheat at different sites to determine if this could quantify frost damage. Spectral libraries were assembled from canopy components collected from local field sites to generate spectral libraries for SMA from which a series of fraction sets was derived. The frost (Fr) fraction was then used to estimate final yield as a means of measuring frost damage. The best-fitting Fr fractions to yield were derived from the same data set as the source Fr spectra, and these ranged over R2 = 0.58-0.75 at the canopy scale. It was clear that spectral signatures need to be collected at scale to assess frost damage. While Fr fractions were able to estimate yield there was no "universal" endmember set from which a Fr fraction could be derived. The normalized difference vegetation index (NDVI) was not able to estimate frost damage consistently. Future work requires determining whether there is a "universal" set of endmembers and a minimum set of targeted wavebands that could lead to multispectral instruments for frost assessment for use in ground and aerial sensors.

KW - Abiotic stress

KW - Hyperspectral

KW - Scaling

KW - Spectral signature

UR - http://www.scopus.com/inward/record.url?scp=85074665183&partnerID=8YFLogxK

U2 - 10.3390/rs11212476

DO - 10.3390/rs11212476

M3 - Article

VL - 11

JO - Default journal

JF - Default journal

SN - 2072-4292

IS - 21

M1 - 2476

ER -

Fitzgerald GJ, Perry EM, Flower KC, Nikolaus Callow J, Boruff B, Delahunty A et al. Frost damage assessment in wheat using spectral mixture analysis. Remote Sensing. 2019 Nov 1;11(21). 2476. https://doi.org/10.3390/rs11212476