How to translate text using browser tools
10 July 2015 Spiking regional vis-NIR calibration models with local samples to predict soil organic carbon in two High Arctic polar deserts using a vis-NIR probe
Amanda L. Guy, Steven D. Siciliano, Eric G. Lamb
Author Affiliations +
Abstract

Guy, A. L., Siciliano, S. D. and Lamb, E. G. 2015. Spiking regional vis-NIR calibration models with local samples to predict soil organic carbon in two High Arctic polar deserts using a vis-NIR probe. Can. J. Soil Sci. 95: 237-249. In situ visible and near-infrared (vis-NIR) spectroscopy is a potential solution to the logistic constraints limiting the accuracy and spatial resolution of soil organic carbon (SOC) estimates for Arctic regions. The objective of our study was to develop a calibration model based on field-condition soils for in situ applications to predict SOC in High Arctic polar desert soils from vis-NIR spectra. Soils (n=240) for calibration models were collected from three regional Canadian Arctic sites in 2010 and two local target sites in 2013. Local and regional calibration models were developed using partial least squares regression (PLSR). We assessed whether spiking or spiking and extra-weighting, regional models with calibration samples from local sites improved prediction of the local sites. The local model yielded successful prediction of target sites (R2=0.91) whereas unspiked regional models had poor prediction accuracy (R2=0.07 to 0.36; n=4). Spiking regional models with as few as 12 local samples greatly improved the SOC prediction of target sites; the best spiked models had R2 between 0.69 and 0.86. Extra-weighting spiking subsets in regional models yielded limited improvements in prediction performance. These results suggest that regional vis-NIR calibration models can be successfully used to predict SOC in High Arctic polar desert soils. The in situ application of these calibration models using field-portable instruments in remote areas, relative to traditional laboratory methods, can achieve higher sample sizes and the ability to characterize the spatial variability of SOC.

Amanda L. Guy, Steven D. Siciliano, and Eric G. Lamb "Spiking regional vis-NIR calibration models with local samples to predict soil organic carbon in two High Arctic polar deserts using a vis-NIR probe," Canadian Journal of Soil Science 95(3), 237-249, (10 July 2015). https://doi.org/10.1139/CJSS-2015-004
Received: 9 January 2015; Accepted: 1 May 2015; Published: 10 July 2015
JOURNAL ARTICLE
13 PAGES

This article is only available to subscribers.
It is not available for individual sale.
+ SAVE TO MY LIBRARY

KEYWORDS
carbone organique du sol
diffuse reflectance spectroscopy
in situ measurements
mesures in situ
partial least squares regression
régression partielle des moindres carrés
soil organic carbon
RIGHTS & PERMISSIONS
Get copyright permission
Back to Top