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
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 fro...
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Veröffentlicht in: | Journal of Agricultural Meteorology 2021, Vol.77(4), pp.253-261 |
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creator | YOSHIKAWA, Kei TAKAGI, Kentaro YAZAKI, Tomotsugu HIRANO, Takashi HAYAKASHI, Shintaro IDE, Reiko OGUMA, Hiroyuki HIROSE, Yasuo KURIHARA, Junichi |
description | 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 (28×27) 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. |
doi_str_mv | 10.2480/agrmet.D-21-00005 |
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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 (28×27) 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.</description><identifier>ISSN: 0021-8588</identifier><identifier>EISSN: 1881-0136</identifier><identifier>DOI: 10.2480/agrmet.D-21-00005</identifier><language>eng</language><publisher>Tokyo: The Society of Agricultural Meteorology of Japan</publisher><subject>Agriculture ; Birch ; Cameras ; Chlorophyll ; Chlorophylls ; Flight ; Gross primary production ; Larch plantation ; Light ; Liquid crystals ; Microsatellites ; Normalized difference spectral index ; Photosynthesis ; Plantations ; Primary production ; Radiometers ; Reflectance ; Sasa ; Saturation ; Seasonal variation ; Seasonal variations ; Seasons ; Spectra ; Spectral reflectance ; Spectroradiometers ; Tunable filters ; Vegetation ; Vegetation index ; Vegetation type ; Wavelength</subject><ispartof>Journal of Agricultural Meteorology, 2021, Vol.77(4), pp.253-261</ispartof><rights>2021 The Society of Agricultural Meteorology of Japan</rights><rights>2021. 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Agric. Meteorol.</addtitle><description>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 (28×27) 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.</description><subject>Agriculture</subject><subject>Birch</subject><subject>Cameras</subject><subject>Chlorophyll</subject><subject>Chlorophylls</subject><subject>Flight</subject><subject>Gross primary production</subject><subject>Larch plantation</subject><subject>Light</subject><subject>Liquid crystals</subject><subject>Microsatellites</subject><subject>Normalized difference spectral index</subject><subject>Photosynthesis</subject><subject>Plantations</subject><subject>Primary production</subject><subject>Radiometers</subject><subject>Reflectance</subject><subject>Sasa</subject><subject>Saturation</subject><subject>Seasonal variation</subject><subject>Seasonal variations</subject><subject>Seasons</subject><subject>Spectra</subject><subject>Spectral reflectance</subject><subject>Spectroradiometers</subject><subject>Tunable filters</subject><subject>Vegetation</subject><subject>Vegetation index</subject><subject>Vegetation type</subject><subject>Wavelength</subject><issn>0021-8588</issn><issn>1881-0136</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNpFkU1u2zAQRomiBeK6OUB2BLJWyj9Z0rKIXbdAgGzaNUFRI4uGLMpDyrFv1GOWjpqUCxIDvjfAN0PIHWcPQpXsq9nhAeLDOhM8Y-nkH8iCl2UquFx9JAvG0keZl-UN-RzCnjEp85wtyJ_Neew9umFHDa0hRHqCHUQTnR-oGxo40-gpJMi4gcYOaAAT_GB6ejLoZs63SW49XvWx89GHy5DQ4AKdwty6u4yAWRjBRkyuNQdAQ-E4uXGEhr642NHepbKhFi8hJiZOg6l7oK3rI-AX8qk1fYDbf--S_P6--fX4I3t63v58_PaUWaVEzKCyteBWlIUEXok6b_lKNLUApSpuWVvWKy6kaqo6r0HJwq6YZJy3pjK5VKyQS3I_9x3RH6eUSO_9hClv0CKv0jAVY1Wi-ExZ9CEgtHpEdzB40Zzp60L0vBC91oLr14UkZzs7-xRvB--GwehsD29GUWh1vf6b74TtDGoY5F_-3Z2w</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>YOSHIKAWA, Kei</creator><creator>TAKAGI, Kentaro</creator><creator>YAZAKI, Tomotsugu</creator><creator>HIRANO, Takashi</creator><creator>HAYAKASHI, Shintaro</creator><creator>IDE, Reiko</creator><creator>OGUMA, Hiroyuki</creator><creator>HIROSE, Yasuo</creator><creator>KURIHARA, Junichi</creator><general>The Society of Agricultural Meteorology of Japan</general><general>Japan Science and Technology Agency</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope></search><sort><creationdate>2021</creationdate><title>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</title><author>YOSHIKAWA, Kei ; TAKAGI, Kentaro ; YAZAKI, Tomotsugu ; HIRANO, Takashi ; HAYAKASHI, Shintaro ; IDE, Reiko ; OGUMA, Hiroyuki ; HIROSE, Yasuo ; KURIHARA, Junichi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c442t-e9cb21c2873e192b5f162db2e4491c0f8b61234d9b5be437c603011fa9a534073</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Agriculture</topic><topic>Birch</topic><topic>Cameras</topic><topic>Chlorophyll</topic><topic>Chlorophylls</topic><topic>Flight</topic><topic>Gross primary production</topic><topic>Larch plantation</topic><topic>Light</topic><topic>Liquid crystals</topic><topic>Microsatellites</topic><topic>Normalized difference spectral index</topic><topic>Photosynthesis</topic><topic>Plantations</topic><topic>Primary production</topic><topic>Radiometers</topic><topic>Reflectance</topic><topic>Sasa</topic><topic>Saturation</topic><topic>Seasonal variation</topic><topic>Seasonal variations</topic><topic>Seasons</topic><topic>Spectra</topic><topic>Spectral reflectance</topic><topic>Spectroradiometers</topic><topic>Tunable filters</topic><topic>Vegetation</topic><topic>Vegetation index</topic><topic>Vegetation type</topic><topic>Wavelength</topic><toplevel>online_resources</toplevel><creatorcontrib>YOSHIKAWA, Kei</creatorcontrib><creatorcontrib>TAKAGI, Kentaro</creatorcontrib><creatorcontrib>YAZAKI, Tomotsugu</creatorcontrib><creatorcontrib>HIRANO, Takashi</creatorcontrib><creatorcontrib>HAYAKASHI, Shintaro</creatorcontrib><creatorcontrib>IDE, Reiko</creatorcontrib><creatorcontrib>OGUMA, Hiroyuki</creatorcontrib><creatorcontrib>HIROSE, Yasuo</creatorcontrib><creatorcontrib>KURIHARA, Junichi</creatorcontrib><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Journal of Agricultural Meteorology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>YOSHIKAWA, Kei</au><au>TAKAGI, Kentaro</au><au>YAZAKI, Tomotsugu</au><au>HIRANO, Takashi</au><au>HAYAKASHI, Shintaro</au><au>IDE, Reiko</au><au>OGUMA, Hiroyuki</au><au>HIROSE, Yasuo</au><au>KURIHARA, Junichi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>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</atitle><jtitle>Journal of Agricultural Meteorology</jtitle><addtitle>J. Agric. Meteorol.</addtitle><date>2021</date><risdate>2021</risdate><volume>77</volume><issue>4</issue><spage>253</spage><epage>261</epage><pages>253-261</pages><artnum>D-21-00005</artnum><issn>0021-8588</issn><eissn>1881-0136</eissn><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 (28×27) 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.</abstract><cop>Tokyo</cop><pub>The Society of Agricultural Meteorology of Japan</pub><doi>10.2480/agrmet.D-21-00005</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Agriculture Birch Cameras Chlorophyll Chlorophylls Flight Gross primary production Larch plantation Light Liquid crystals Microsatellites Normalized difference spectral index Photosynthesis Plantations Primary production Radiometers Reflectance Sasa Saturation Seasonal variation Seasonal variations Seasons Spectra Spectral reflectance Spectroradiometers Tunable filters Vegetation Vegetation index Vegetation type Wavelength |
title | 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 |
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