A Vegetation Index to Estimate Terrestrial Gross Primary Production Capacity for the Global Change Observation Mission-Climate (GCOM-C)/Second-Generation Global Imager (SGLI) Satellite Sensor
| Autor: | Shin Nagai, Juthasinee Thanyapraneedkul, Kanako Muramatsu, Kenlo Nishida Nasahara, Noriko Soyama, Hiroyuki Muraoka, Shinobu Furumi, Hibiki M Noda, Yasuko Mizoguchi, Motomasa Daigo, Takahisa Maeda, Masayoshi Mano |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Canopy
Gross primary production Science Primary production Light-response curve Vegetation Photosynthesis Photosynthetic capacity FluxNet chemistry.chemical_compound Vegetation index chemistry Chlorophyll GCOM-C/SGLI General Earth and Planetary Sciences Environmental science Satellite Chlorophyll content Remote sensing |
| Zdroj: | Remote Sensing, Vol 4, Iss 12, Pp 3689-3720 (2012) Remote Sensing Volume 4 Issue 12 Pages: 3689-3720 |
| ISSN: | 2072-4292 |
| Popis: | To estimate global gross primary production (GPP), which is an important parameter for studies of vegetation productivity and the carbon cycle, satellite data are useful. In 2014, the Japan Aerospace Exploration Agency (JAXA) plans to launch the Global Change Observation Mission-Climate (GCOM-C) satellite carrying the second-generation global imager (SGLI). The data obtained will be used to estimate global GPP. The rate of photosynthesis depends on photosynthesis reduction and photosynthetic capacity, which is the maximum photosynthetic velocity at light saturation under adequate environmental conditions. Photosynthesis reduction is influenced by weather conditions, and photosynthetic capacity is influenced by chlorophyll and RuBisCo content. To develop the GPP estimation algorithm, we focus on photosynthetic capacity because chlorophyll content can be detected by optical sensors. We hypothesized that the maximum rate of low-stress GPP (called “GPP capacity”) is mainly dependent on the chlorophyll content that can be detected by a vegetation index (VI). The objective of this study was to select an appropriate VI with which to estimate global GPP capacity with the GCOM-C/SGLI. We analyzed reflectance data to select the VI that has the best linear correlation with chlorophyll content at the leaf scale and with GPP capacity at canopy and satellite scales. At the satellite scale, flux data of seven dominant plant functional types and reflectance data obtained by the Moderate-resolution Imaging Spectroradiometer (MODIS) were used because SGLI data were not available. The results indicated that the green chlorophyll index, CIgreen(ρNIR/ρgreen-1), had a strong linear correlation with chlorophyll content at the leaf scale (R2 = 0.87, p < 0.001) and with GPP capacity at the canopy (R2 = 0.78, p < 0.001) and satellite scales (R2 = 0.72, p < 0.01). Therefore, CIgreen is a robust and suitable vegetation index for estimating global GPP capacity. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|