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Proceedings Paper

Estimation of gross primary production capacity from global satellite observations
Author(s): Kanako Muramatsu; Juthasinee Thanyapraneedkul; Shinobu Furumi; Noriko Soyama; Motomasa Daigo
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Paper Abstract

To estimate gross primary production (GPP), the process of photosynthesis was considered as two separate phases: capacity and reduction. The reduction phase is influenced by environmental conditions such as soil moisture and weather conditions such as vapor pressure differences. For a particular leaf, photosynthetic capacity mainly depends on the amount of chlorophyll and the RuBisCO enzyme. The chlorophyll content can be estimated by the color of the leaf, and leaf color can be detected by optical sensors. We used the chlorophyll content of leaves to estimate the level of GPP. A previously developed framework for GPP capacity estimation employs a chlorophyll index. The index is based on the linear relationship between the chlorophyll content of a leaf and the maximum photosynthesis at PAR =2000 (μmolm -2s-1) on a light-response curve under low stress conditions. As a first step, this study examined the global distribution of the index and found that regions with high chlorophyll index values in winter corresponded to tropical rainforest areas. The seasonal changes in the chlorophyll index differed from those shown by the normalized difference vegetation index. Next, the capacity of GPP was estimated from the light-response curve using the index. Most regions exhibited a higher GPP capacity than that estimated from Moderate Resolution Imaging Spectroradiometer (MODIS) observations, except in areas of tropical rainforest, where the GPP capacity and the MODIS GPP estimates were almost identical.

Paper Details

Date Published: 21 November 2012
PDF: 8 pages
Proc. SPIE 8524, Land Surface Remote Sensing, 852421 (21 November 2012); doi: 10.1117/12.977336
Show Author Affiliations
Kanako Muramatsu, Nara Women's Univ. (Japan)
Juthasinee Thanyapraneedkul, Nara Women's Univ. (Japan)
Shinobu Furumi, Nara Saho College (Japan)
Noriko Soyama, Tenri Univ. (Japan)
Motomasa Daigo, Doshisha Univ. (Japan)

Published in SPIE Proceedings Vol. 8524:
Land Surface Remote Sensing
Dara Entekhabi; Yoshiaki Honda; Haruo Sawada; Jiancheng Shi; Taikan Oki, Editor(s)

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