Towards the development of a regional version of MOD17 for the determination of gross and net primary productivity of oil palm trees

Conducting quantitative studies on the carbon balance or productivity of oil palm is important for understanding the role of this ecosystem in global climate change. The MOD17 algorithm is used for processing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to generate the values...

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主要な著者: Arthur, Philip Cracknell, Kanniah, Kasturi Devi, Tan, Kianpang, Wang, Lei
フォーマット: 論文
出版事項: Taylor and Francis Ltd. 2015
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オンライン・アクセス:http://eprints.utm.my/id/eprint/59037/
http://dx.doi.org/10.1080/01431161.2014.995278
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spelling my.utm.590372017-02-01T09:00:19Z http://eprints.utm.my/id/eprint/59037/ Towards the development of a regional version of MOD17 for the determination of gross and net primary productivity of oil palm trees Arthur, Philip Cracknell Kanniah, Kasturi Devi Tan, Kianpang Wang, Lei QK Botany Conducting quantitative studies on the carbon balance or productivity of oil palm is important for understanding the role of this ecosystem in global climate change. The MOD17 algorithm is used for processing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to generate the values of gross primary productivity (GPP) and net primary productivity for input to global carbon cycle modelling. In view of the increasing importance of data on carbon sequestration at regional and national levels, we have studied one important factor affecting the accuracy of the implementation of MOD17 at the sub-global level, namely the database of MODIS land cover (MOD12Q1) used by MOD17. By using a study area of approximately 7 km × 7 km (49 MODIS pixels) in semi-rural Johor in Peninsular Malaysia and using Google Earth 0.75 m resolution images as ground data, we found that the land-cover type for only 16 of these 49 MODIS pixels was correctly identified by MOD12Q1 using its 1 km resolution land-cover database. This leads to errors of 24% to 50% in the maximum light use efficiency, leading to corresponding errors of 24% to 50% in the GPP. We show that by using the Finer Resolution Observation and Monitoring – Global Land Cover (FROM-GLC) land-cover database developed by Gong et al., this particular error can be essentially eliminated, but at the cost of using extra computing resources. © 2015, © 2015 The Author(s). Published by Taylor & Francis. Taylor and Francis Ltd. 2015-01 Article PeerReviewed Arthur, Philip Cracknell and Kanniah, Kasturi Devi and Tan, Kianpang and Wang, Lei (2015) Towards the development of a regional version of MOD17 for the determination of gross and net primary productivity of oil palm trees. International Journal of Remote Sensing, 36 (1). pp. 262-289. ISSN 1431-161 http://dx.doi.org/10.1080/01431161.2014.995278 DOI:10.1080/01431161.2014.995278
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QK Botany
spellingShingle QK Botany
Arthur, Philip Cracknell
Kanniah, Kasturi Devi
Tan, Kianpang
Wang, Lei
Towards the development of a regional version of MOD17 for the determination of gross and net primary productivity of oil palm trees
description Conducting quantitative studies on the carbon balance or productivity of oil palm is important for understanding the role of this ecosystem in global climate change. The MOD17 algorithm is used for processing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to generate the values of gross primary productivity (GPP) and net primary productivity for input to global carbon cycle modelling. In view of the increasing importance of data on carbon sequestration at regional and national levels, we have studied one important factor affecting the accuracy of the implementation of MOD17 at the sub-global level, namely the database of MODIS land cover (MOD12Q1) used by MOD17. By using a study area of approximately 7 km × 7 km (49 MODIS pixels) in semi-rural Johor in Peninsular Malaysia and using Google Earth 0.75 m resolution images as ground data, we found that the land-cover type for only 16 of these 49 MODIS pixels was correctly identified by MOD12Q1 using its 1 km resolution land-cover database. This leads to errors of 24% to 50% in the maximum light use efficiency, leading to corresponding errors of 24% to 50% in the GPP. We show that by using the Finer Resolution Observation and Monitoring – Global Land Cover (FROM-GLC) land-cover database developed by Gong et al., this particular error can be essentially eliminated, but at the cost of using extra computing resources. © 2015, © 2015 The Author(s). Published by Taylor & Francis.
format Article
author Arthur, Philip Cracknell
Kanniah, Kasturi Devi
Tan, Kianpang
Wang, Lei
author_facet Arthur, Philip Cracknell
Kanniah, Kasturi Devi
Tan, Kianpang
Wang, Lei
author_sort Arthur, Philip Cracknell
title Towards the development of a regional version of MOD17 for the determination of gross and net primary productivity of oil palm trees
title_short Towards the development of a regional version of MOD17 for the determination of gross and net primary productivity of oil palm trees
title_full Towards the development of a regional version of MOD17 for the determination of gross and net primary productivity of oil palm trees
title_fullStr Towards the development of a regional version of MOD17 for the determination of gross and net primary productivity of oil palm trees
title_full_unstemmed Towards the development of a regional version of MOD17 for the determination of gross and net primary productivity of oil palm trees
title_sort towards the development of a regional version of mod17 for the determination of gross and net primary productivity of oil palm trees
publisher Taylor and Francis Ltd.
publishDate 2015
url http://eprints.utm.my/id/eprint/59037/
http://dx.doi.org/10.1080/01431161.2014.995278
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