×ばつ27) of two reflectances was NDSI[770, 720] for the maximum gross primary production at light saturation and NDSI[530, 600] for the initial slope of the light-response curve, which reflect the red edge shift owing to the change in the chlorophyll content and relative strength of the light absorbance in the visible red wavelength region compared with that in the green wavelength region, respectively. Predicted daily gross primary production of the plantation using these NDSI agreed well with the observed values. NDSI[530, 600] was better to distinguish each vegetation type of the studied plantation." /> Exploring a best vegetation index to explain the seasonal variation of a forest photosynthesis using a hyper-spectral camera equipped with liquid crystal tunable filter
Journal of Agricultural Meteorology
Online ISSN : 1881-0136
Print ISSN : 0021-8588
ISSN-L : 0021-8588
Full Paper
Exploring a best vegetation index to explain the seasonal variation of a forest photosynthesis using a hyper-spectral camera equipped with liquid crystal tunable filter
Kei YOSHIKAWA, Kentaro TAKAGI, Tomotsugu YAZAKI, Takashi HIRANO, Shintaro HAYAKASHI, Reiko IDE, Hiroyuki OGUMA, Yasuo HIROSE, Junichi KURIHARA
Author information
  • Kei YOSHIKAWA

    Graduate School of Agriculture, Hokkaido University

  • Kentaro TAKAGI

    Teshio Experimental Forest, Field Science Center for Northern Biosphere, Hokkaido University

  • Tomotsugu YAZAKI

    Research Faculty of Agriculture, Hokkaido University
    School of Agriculture, Meiji University

  • Takashi HIRANO

    Research Faculty of Agriculture, Hokkaido University

  • Shintaro HAYAKASHI

    Teshio Experimental Forest, Field Science Center for Northern Biosphere, Hokkaido University

  • Reiko IDE

    Earth System Division, National Institute for Environmental Studies

  • Hiroyuki OGUMA

    Biodiversity Division, National Institute for Environmental Studies

  • Yasuo HIROSE

    Earth System Division, National Institute for Environmental Studies

  • Junichi KURIHARA

    Faculty of Science, Hokkaido University

Corresponding author

ORCID
Keywords: Birch, Gross primary production, Larch plantation, Normalized difference spectral index, Sasa
JOURNAL OPEN ACCESS

2021 Volume 77 Issue 4 Pages 253-261

Details
  • Published: 2021 Received: January 19, 2021 Released on J-STAGE: October 10, 2021 Accepted: July 16, 2021 Advance online publication: - Revised: -
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Abstract
Liquid crystal tunable filter (LCTF) can change the transmissible wavelength by changing the applied voltage to the filter, which enables the drastic increase in the observable wavelength resolution in a small size system and is considered to be a powerful tool for the spectral earth observation from flying units or microsatellites. However, there is limited knowledge about its season-long application for the vegetation monitoring and the prediction of the ecosystem photosynthetic capacity. We compared the seasonal variation of spectral reflectance obtained by a LCTF camera with that obtained by a popular spectral radiometer in a cool-temperate young larch plantation in northern Hokkaido, Japan. Then we tried to find the best normalized difference spectral index (NDSI) to explain the seasonal variation of the ecosystem photosynthetic capacity using all pairs of two reflectances observed in the range of wavelength between 500 and 770 nm with 10-nm intervals (28 wavelength bands) by the LCTF. The best NDSI among all combinations (×ばつ27) of two reflectances was NDSI[770, 720] for the maximum gross primary production at light saturation and NDSI[530, 600] for the initial slope of the light-response curve, which reflect the red edge shift owing to the change in the chlorophyll content and relative strength of the light absorbance in the visible red wavelength region compared with that in the green wavelength region, respectively. Predicted daily gross primary production of the plantation using these NDSI agreed well with the observed values. NDSI[530, 600] was better to distinguish each vegetation type of the studied plantation.
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This article is licensed under a Creative Commons [Attribution 4.0 International] license.
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