Nitrogen prediction in grasses: effect of bandwidth and plant material state on absorption feature selection

We analysed stability and predictive capabilities of known nitrogen absorption features between plant material prepared for NIRS (dried) and RS (fresh) studies. Grass spectra were taken of the plant canopy, and again after the grass sample was dried and ground. Models were derived using stepwise mul...

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Veröffentlicht in:	International journal of remote sensing Jg. 31; H. 3; S. 691 - 704
Hauptverfasser:	Knox, N. M., Skidmore, A. K., Schlerf, M., de Boer, W. F., van Wieren, S. E., van der Waal, C., Prins, H. H. T., Slotow, R.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Abingdon Taylor & Francis 01.01.2010
Schlagworte:	Animal, plant and microbial ecology Applied geophysics aviris data Biological and medical sciences canopy chemistry Earth sciences Earth, ocean, space Exact sciences and technology forest ecosystems Fundamental and applied biological sciences. Psychology General aspects. Techniques heterogeneous grassland hyperspectral data Internal geophysics leaf biochemistry multiple linear-regression oregon transect reflectance spectroscopy Teledetection and vegetation maps vegetation lai spectra Spectral band Multiple linear regression variability Modeling Biological material Reflection spectrometry Instrument error Gramineae Selection criterion Chemical concentration stability models Linear regression absorption nitrogen Plantae Prediction utilization samples angiosperms materials State Monocotyledoneae Plant origin Spermatophyta near infrared spectroscopy Widening Canopy(vegetation)
ISSN:	0143-1161, 1366-5901
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Abstract	We analysed stability and predictive capabilities of known nitrogen absorption features between plant material prepared for NIRS (dried) and RS (fresh) studies. Grass spectra were taken of the plant canopy, and again after the grass sample was dried and ground. Models were derived using stepwise multiple linear regression (sMLR). Regression values (adj.r 2 ) produced using the dried material were greater than those produced using canopy material. For dried material only wavebands from the SWIR region were selected. Wavebands selected by sMLR on canopy material were located in both the VNIR and SWIR regions. Using wavebands selected for dried material models produced low adj.r 2 values when applied to canopy plant material; differences in adj.r 2 values are smaller when wavebands selected in canopy material models are applied to dried material. Widening of nitrogen features produced higher adj.r 2 values for both dried and canopy material. This work shows that obtaining models with high predictive capabilities for nitrogen concentration is possible, but waveband selection should not be limited to features identified by NIRS studies. To accommodate for variability in absorption features, and instrument errors, absorption features should be widened.
AbstractList	We analysed stability and predictive capabilities of known nitrogen absorption features between plant material prepared for NIRS (dried) and RS (fresh) studies. Grass spectra were taken of the plant canopy, and again after the grass sample was dried and ground. Models were derived using stepwise multiple linear regression (sMLR). Regression values (adj.r 2 ) produced using the dried material were greater than those produced using canopy material. For dried material only wavebands from the SWIR region were selected. Wavebands selected by sMLR on canopy material were located in both the VNIR and SWIR regions. Using wavebands selected for dried material models produced low adj.r 2 values when applied to canopy plant material; differences in adj.r 2 values are smaller when wavebands selected in canopy material models are applied to dried material. Widening of nitrogen features produced higher adj.r 2 values for both dried and canopy material. This work shows that obtaining models with high predictive capabilities for nitrogen concentration is possible, but waveband selection should not be limited to features identified by NIRS studies. To accommodate for variability in absorption features, and instrument errors, absorption features should be widened. We analysed stability and predictive capabilities of known nitrogen absorption features between plant material prepared for NIRS (dried) and RS (fresh) studies. Grass spectra were taken of the plant canopy, and again after the grass sample was dried and ground. Models were derived using stepwise multiple linear regression (sMLR). Regression values (adj.r2) produced using the dried material were greater than those produced using canopy material. For dried material only wavebands from the SWIR region were selected. Wavebands selected by sMLR on canopy material were located in both the VNIR and SWIR regions. Using wavebands selected for dried material models produced low adj.r2 values when applied to canopy plant material; differences in adj.r2 values are smaller when wavebands selected in canopy material models are applied to dried material. Widening of nitrogen features produced higher adj.r2 values for both dried and canopy material. This work shows that obtaining models with high predictive capabilities for nitrogen concentration is possible, but waveband selection should not be limited to features identified by NIRS studies. To accommodate for variability in absorption features, and instrument errors, absorption features should be widened.
Author	Prins, H. H. T. Schlerf, M. Knox, N. M. Slotow, R. Skidmore, A. K. de Boer, W. F. van der Waal, C. van Wieren, S. E.
Author_xml	– sequence: 1 givenname: N. M. surname: Knox fullname: Knox, N. M. email: knox@itc.nl organization: International Institute for Geo-information Science and Earth Observation – sequence: 2 givenname: A. K. surname: Skidmore fullname: Skidmore, A. K. organization: International Institute for Geo-information Science and Earth Observation – sequence: 3 givenname: M. surname: Schlerf fullname: Schlerf, M. organization: International Institute for Geo-information Science and Earth Observation – sequence: 4 givenname: W. F. surname: de Boer fullname: de Boer, W. F. organization: Resource Ecology Group, Wageningen University – sequence: 5 givenname: S. E. surname: van Wieren fullname: van Wieren, S. E. organization: Resource Ecology Group, Wageningen University – sequence: 6 givenname: C. surname: van der Waal fullname: van der Waal, C. organization: Resource Ecology Group, Wageningen University – sequence: 7 givenname: H. H. T. surname: Prins fullname: Prins, H. H. T. organization: Resource Ecology Group, Wageningen University – sequence: 8 givenname: R. surname: Slotow fullname: Slotow, R. organization: Amarula Elephant Research Programme, Biological and Conservation Sciences, Westville Campus, University of KwaZulu-Natal
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Keywords	spectra Spectral band Multiple linear regression variability Modeling Biological material Reflection spectrometry Instrument error Gramineae Selection criterion Chemical concentration stability models Linear regression absorption nitrogen Plantae Prediction utilization samples angiosperms materials State Monocotyledoneae Plant origin Spermatophyta near infrared spectroscopy Widening Canopy(vegetation)
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SubjectTerms	Animal, plant and microbial ecology Applied geophysics aviris data Biological and medical sciences canopy chemistry Earth sciences Earth, ocean, space Exact sciences and technology forest ecosystems Fundamental and applied biological sciences. Psychology General aspects. Techniques heterogeneous grassland hyperspectral data Internal geophysics leaf biochemistry multiple linear-regression oregon transect reflectance spectroscopy Teledetection and vegetation maps vegetation lai
Title	Nitrogen prediction in grasses: effect of bandwidth and plant material state on absorption feature selection
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