Exploring the potential of in situ hyperspectral data and multivariate techniques in discriminating different fertilizer treatments in grasslands

Mbulisi Sibanda; Onisimo Mutanga; Mathieu Rouget; John Odindi

doi:10.1117/1.JRS.9.096033

2 July 2015 Exploring the potential of in situ hyperspectral data and multivariate techniques in discriminating different fertilizer treatments in grasslands

Mbulisi Sibanda, Onisimo Mutanga, Mathieu Rouget, John Odindi

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 9, Issue 1, 096033 (July 2015). https://doi.org/10.1117/1.JRS.9.096033

Abstract

Optimizing the productivity of native rangelands has received considerable attention in range management. Rangeland fertilizer application has emerged as a popular intervention for improving rangeland quality. To achieve optimal range quality from such intervention, there is a need for quick and accurate methods of assessing the effects of different fertilizer combinations. The utility of in situ hyperspectral data and multivariate techniques in distinguishing 12 complex ammonium nitrate, ammonium sulfate, lime, and phosphorus fertilizer combinations on a grassland is assessed. Partial least squares regression discriminant analysis (PLS-DA) and discriminant analysis (DA) classification results derived using hyperspectral grass reflectance that were (1) fertilized using 11 combinations of ammonium sulfate, ammonium nitrate, phosphorus, and lime and (2) unfertilized experimental plots were compared. Results illustrate the strength of in situ hyperspectral data and multivariate techniques in detecting and discriminating grasses with different fertilizer treatments. Specifically, four bands within the red edge (731 and 737 nm) and the shortwave infrared (1310 and 1777 nm) regions of the electromagnetic spectrum demonstrated a high potential for discriminating the effects of fertilizer treatments on grasslands. DA outperformed PLS-DA in discriminating complex combinations of ammonium nitrate, ammonium sulfate combined with lime and phosphorus, as well as unfertilized grasses. Overall, spectroscopy and DA offer great potential for discriminating complex fertilizer combinations.

Citation Download Citation

Mbulisi Sibanda, Onisimo Mutanga, Mathieu Rouget, and John Odindi "Exploring the potential of in situ hyperspectral data and multivariate techniques in discriminating different fertilizer treatments in grasslands," Journal of Applied Remote Sensing 9(1), 096033 (2 July 2015). https://doi.org/10.1117/1.JRS.9.096033

Published: 2 July 2015

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available