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...
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| Format: | Article |
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Taylor & Francis
2019
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| _version_ | 1796980667632844800 |
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| author | Amirruddin, Amiratul Diyana Muharam, Farrah Melissa |
| author_facet | Amirruddin, Amiratul Diyana Muharam, Farrah Melissa |
| author_sort | Amirruddin, Amiratul Diyana |
| collection | UPM |
| description | 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 visible (Vis), near infrared (NIR) and a combination of visible and NIR (Vis + NIR) from the SPOT-6 satellite, and (ii) to compare the performance of linear discriminant analysis (LDA) and support vector machine (SVM) in discriminating foliar N content of mature oil palms. Nitrogen treatments varied from 0 to 2 kg per palm. The N-sensitive SIs tested in this study were age-dependent. The Vis index (BGRI1) (CVA = 79.55%) and Vis + NIR index (NDVI, NG, IPVI and GNDVI) (CVA = 81.82%) were the best indices to assess N status of young and prime mature palms through the SVM classifier. |
| first_indexed | 2024-03-06T10:26:26Z |
| format | Article |
| id | upm.eprints-79760 |
| institution | Universiti Putra Malaysia |
| last_indexed | 2024-03-06T10:26:26Z |
| publishDate | 2019 |
| publisher | Taylor & Francis |
| record_format | dspace |
| spelling | upm.eprints-797602022-11-01T07:05:08Z http://psasir.upm.edu.my/id/eprint/79760/ 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 Amirruddin, Amiratul Diyana Muharam, Farrah Melissa 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 visible (Vis), near infrared (NIR) and a combination of visible and NIR (Vis + NIR) from the SPOT-6 satellite, and (ii) to compare the performance of linear discriminant analysis (LDA) and support vector machine (SVM) in discriminating foliar N content of mature oil palms. Nitrogen treatments varied from 0 to 2 kg per palm. The N-sensitive SIs tested in this study were age-dependent. The Vis index (BGRI1) (CVA = 79.55%) and Vis + NIR index (NDVI, NG, IPVI and GNDVI) (CVA = 81.82%) were the best indices to assess N status of young and prime mature palms through the SVM classifier. Taylor & Francis 2019 Article PeerReviewed Amirruddin, Amiratul Diyana and Muharam, Farrah Melissa (2019) 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. Geocarto International, 34 (7). pp. 735-749. ISSN 1010-6049; ESSN: 1752-0762 https://www.tandfonline.com/doi/abs/10.1080/10106049.2018.1434687 10.1080/10106049.2018.1434687 |
| spellingShingle | Amirruddin, Amiratul Diyana Muharam, Farrah Melissa 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 |
| title | 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 |
| title_full | 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 |
| title_fullStr | 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 |
| title_full_unstemmed | 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 |
| title_short | 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 |
| title_sort | 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 |
| work_keys_str_mv | AT amirruddinamiratuldiyana evaluationoflineardiscriminantandsupportvectormachineclassifiersforclassificationofnitrogenstatusinmatureoilpalmfromspot6satelliteimagesanalysisofrawspectralbandsandspectralindices AT muharamfarrahmelissa evaluationoflineardiscriminantandsupportvectormachineclassifiersforclassificationofnitrogenstatusinmatureoilpalmfromspot6satelliteimagesanalysisofrawspectralbandsandspectralindices |