Seasonal Changes of a Spectral Reflectance Index, PRI (Photochemical Reflectance Index) in a Temperate Japanese Cypress Forest

理絵, 中西; 緑子, 小杉; 晋治郎, 大久保; 顕郎, 西田; 宏之, 小熊; 聡, 高梨

doi:10.3178/jjshwr.19.475

Cited by 3 publications

(2 citation statements)

References 27 publications

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“…In short-term (diurnal) variation, the PRI-ɛ relationship has been explained empirically as both linear (Filella et al, 1996;Trotter et al, 2002) and non-linear (Barton & North, 2001;Peñuelas et al, 1995). Although a few reports deal with both seasonal and short-term variations in the PRI-ɛ relationship (Nakaji et al, 2005(Nakaji et al, , 2006Nakanishi et al, 2006), our results indicate that the relationship could be expressed as nonlinear regression function when the data in all sky conditions and both time-scales are analyzed.…”

Section: Relationship Of ɛ and Single Indexmentioning

confidence: 45%

Utility of spectral vegetation index for estimation of gross CO2 flux under varied sky conditions

Nakaji

Ide

Oguma

et al. 2007

Remote Sensing of Environment

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Section: Relationship Of ɛ and Single Indexmentioning

confidence: 45%

Utility of spectral vegetation index for estimation of gross CO2 flux under varied sky conditions

Nakaji

Ide

Oguma

et al. 2007

Remote Sensing of Environment

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“…The photochemical reflectance index (PRI; Gamon et al 1992) is one main indices used for this purpose. Nakanishi et al (2006) investigated the relationship between the PRI and LUE using HSSR data and flux data collected at the KEW site (Japanese cypress forest), and revealed the effects of phenology and light intensity. Nakaji et al (2008Nakaji et al ( , 2014 also investigated relationships between several vegetation indices (including PRI) and LUE using HSSR data and flux data collected at the TMK, KEW, and TSE sites, and the Pasoh site in Malaysia.…”

Section: Estimation Of Gppmentioning

confidence: 99%

Review: Development of an in situ observation network for terrestrial ecological remote sensing: the Phenological Eyes Network (PEN)

Nasahara

Nagai

2015

Ecological Research

106

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The Phenological Eyes Network (PEN), which was established in 2003, is a network of long‐term ground observation sites. The aim of the PEN is to validate terrestrial ecological remote sensing, with a particular focus on seasonal changes (phenology) in vegetation. There are three types of core sensors at PEN sites: an Automatic Digital Fish‐eye Camera, a HemiSpherical SpectroRadiometer, and a Sun Photometer. As of 2014, there are approximately 30 PEN sites, among which many are also FluxNet and/or International Long Term Ecological Research sites. The PEN is now part of a biodiversity observation framework. Collaborations between remote sensing scientists and ecologists working on PEN data have produced various outcomes about remote sensing and long‐term in situ monitoring of ecosystem features, such as phenology, gross primary production, and leaf area index. This article reviews the design concept and the outcomes of the PEN, and discusses its future strategy.

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Utility of spectral vegetation indices for estimation of light conversion efficiency in coniferous forests in Japan

Nakaji

Ide

Takagi

et al. 2008

Agricultural and Forest Meteorology

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1To clarify the utility of spectral vegetation indices (VIs) for estimating light conversion 2 efficiency () in Japanese coniferous forests, we investigated the relationships between six 3 VIs (NDVI, EVI, SAVI, PRI, CI, and CCI) and  in two mature monospecific forests of 4 deciduous conifer (Japanese larch) and evergreen conifer (Japanese cypress) and one young 5 mixed stand of deciduous conifer with evergreen undergrowth (hybrid larch and dwarf 6 bamboo). In each forest canopy, we measured seasonal variations in CO 2 flux, radiation 7 environment, and visible-near-infrared spectral reflectance during 1 or 2 growing seasons. 8We calculated  as gross primary production (GPP) divided by the difference between 9 incoming and reflected photosynthetically active radiation (PAR). VIs and  under clear skies 10 were averaged between 11:00 and 13:00 JST and their relationships were analyzed. 11In the larch forest, all calculated VIs were positively correlated with , and the highest 12 correlation was that with CCI. Because of effects of extreme reduction in PRI in autumn with 13 needle yellowing, the correlation of  and PRI was relatively small in this forest. In the 14 cypress forest, on the other hand, no significant correlation was found except with PRI and 15 CCI. The highest correlation in this forest was that with PRI, suggesting that the leaf biomass-16 related VIs based on near-infrared reflectance are not sufficient for estimating  of evergreen 17 forest. In the mixed forest, with relatively sparse vegetation cover, all VIs were significantly 18 correlated with , but the best correlation was that with SAVI, possibly owing to the reduction 19 in the effect of the reflectance from background soil. Correlation analysis of the pooled data 20 3 from all forests showed the highest correlation between  and PRI. These results indicate that 1 PRI is an effective VI in the remote estimation of  in both deciduous and evergreen forests, 2 although there are some sensitivity differences between vegetation types. 3 4

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Seasonal Changes of a Spectral Reflectance Index, PRI (Photochemical Reflectance Index) in a Temperate Japanese Cypress Forest

Cited by 3 publications

References 27 publications

Utility of spectral vegetation index for estimation of gross CO2 flux under varied sky conditions

Utility of spectral vegetation index for estimation of gross CO2 flux under varied sky conditions

Review: Development of an in situ observation network for terrestrial ecological remote sensing: the Phenological Eyes Network (PEN)

Utility of spectral vegetation indices for estimation of light conversion efficiency in coniferous forests in Japan

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