Evaluation of linear discriminant and support vector machine classifiers for classification of nitrogen status in mature oil palm from SPOT-6 satellite images: analysis of raw spectral bands and spectral indices
Nitrogen (N) management is important in sustaining oil palm production. Remote sensing-based approaches via spectral index have promise in assessing the N nutrition content. The objectives of this study are; (i) to examine the N classification capability of three spectral indices (SI) such as visibl...
Main Authors: | Amirruddin, Amiratul Diyana, Muharam, Farrah Melissa |
---|---|
Format: | Article |
Published: |
Taylor & Francis
2019
|
Similar Items
-
Classification of oil palm nitrogen status from SPOT-6 satellite using support vector machine and spectral indices
by: Amirruddin, Amiratul Diyana, et al.
Published: (2017) -
Spectral and foliar analysis using multiple machine learning classifiers for mature oil palm treated with nitrogen fertilizer
by: Amirruddin, Amiratul Diyana
Published: (2021) -
Assessing leaf scale measurement for nitrogen content of oil palm: performance of discriminant analysis and support vector machine classifiers
by: Amirruddin, Amiratul Diyana, et al.
Published: (2017) -
Evaluation of vegetation index (VI) in estimating nitrogen nutrition status in oil palm
by: Amirruddin, Amiratul Diyana, et al.
Published: (2015) -
Evaluation of nitrogen nutrition status in oil palm based on spectral response and multi-sensor images
by: Amirruddin, Amiratul Diyana
Published: (2016)