Cover Image

Classification of oil palm nitrogen status from SPOT-6 satellite using support vector machine and spectral indices

Nitrogen (N) management is important in sustaining oil palm production. Remote sensing based approaches such as spectral index has promise in assessing the N nutrition content of many crops. The objectives of this study are to examine the N classification capability of three spectral indexes (SI): v...

Full description

Saved in:
Bibliographic Details
Main Authors: Amirruddin, Amiratul Diyana, Muharam, Farrah Melissa
Format: Conference or Workshop Item
Language:English
Published: Institute of Plantation Studies, Universiti Putra Malaysia 2017
Online Access:http://psasir.upm.edu.my/id/eprint/58870/1/Technical_Paper_7.pdf
http://psasir.upm.edu.my/id/eprint/58870/
http://spel2.upm.edu.my/webupm/upload/dokumen/penerbitan/20180101231126ICBAA2017_Technical_Paper_7.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.upm.eprints.58870
record_format eprints
spelling my.upm.eprints.588702018-02-07T08:42:55Z http://psasir.upm.edu.my/id/eprint/58870/ Classification of oil palm nitrogen status from SPOT-6 satellite using support vector machine and spectral indices Amirruddin, Amiratul Diyana Muharam, Farrah Melissa Nitrogen (N) management is important in sustaining oil palm production. Remote sensing based approaches such as spectral index has promise in assessing the N nutrition content of many crops. The objectives of this study are to examine the N classification capability of three spectral indexes (SI): visible (Vis), near infrared (NIR) and a combination of visible and NIR (Vis+NIR) using data from the SPOT-6 satellite. N treatments varied from 0 to 2 kg per palm and were applied to both mature palms. The N-sensitive SIs tested in this study were age-dependent. The Vis index such as BGRI1 (CVA= 79.55%) and the Vis+NIR indices such as 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. Nonetheless, the SVM classifier showed promising potential in classifying foliar N content of mature palms that can possibly be used further for developing a new index in assessing N content of oil palms. Institute of Plantation Studies, Universiti Putra Malaysia 2017 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/58870/1/Technical_Paper_7.pdf Amirruddin, Amiratul Diyana and Muharam, Farrah Melissa (2017) Classification of oil palm nitrogen status from SPOT-6 satellite using support vector machine and spectral indices. In: International Conference on Big Data Applications in Agriculture (ICBAA2017), 5-6 Dec. 2017, Auditorium Putra, TNCPI Building, Universiti Putra Malaysia. (pp. 107-117). http://spel2.upm.edu.my/webupm/upload/dokumen/penerbitan/20180101231126ICBAA2017_Technical_Paper_7.pdf
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Nitrogen (N) management is important in sustaining oil palm production. Remote sensing based approaches such as spectral index has promise in assessing the N nutrition content of many crops. The objectives of this study are to examine the N classification capability of three spectral indexes (SI): visible (Vis), near infrared (NIR) and a combination of visible and NIR (Vis+NIR) using data from the SPOT-6 satellite. N treatments varied from 0 to 2 kg per palm and were applied to both mature palms. The N-sensitive SIs tested in this study were age-dependent. The Vis index such as BGRI1 (CVA= 79.55%) and the Vis+NIR indices such as 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. Nonetheless, the SVM classifier showed promising potential in classifying foliar N content of mature palms that can possibly be used further for developing a new index in assessing N content of oil palms.
format Conference or Workshop Item
author Amirruddin, Amiratul Diyana
Muharam, Farrah Melissa
spellingShingle Amirruddin, Amiratul Diyana
Muharam, Farrah Melissa
Classification of oil palm nitrogen status from SPOT-6 satellite using support vector machine and spectral indices
author_facet Amirruddin, Amiratul Diyana
Muharam, Farrah Melissa
author_sort Amirruddin, Amiratul Diyana
title Classification of oil palm nitrogen status from SPOT-6 satellite using support vector machine and spectral indices
title_short Classification of oil palm nitrogen status from SPOT-6 satellite using support vector machine and spectral indices
title_full Classification of oil palm nitrogen status from SPOT-6 satellite using support vector machine and spectral indices
title_fullStr Classification of oil palm nitrogen status from SPOT-6 satellite using support vector machine and spectral indices
title_full_unstemmed Classification of oil palm nitrogen status from SPOT-6 satellite using support vector machine and spectral indices
title_sort classification of oil palm nitrogen status from spot-6 satellite using support vector machine and spectral indices
publisher Institute of Plantation Studies, Universiti Putra Malaysia
publishDate 2017
url http://psasir.upm.edu.my/id/eprint/58870/1/Technical_Paper_7.pdf
http://psasir.upm.edu.my/id/eprint/58870/
http://spel2.upm.edu.my/webupm/upload/dokumen/penerbitan/20180101231126ICBAA2017_Technical_Paper_7.pdf
_version_ 1643836910763769856
score 13.211869

Similar Items