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Estimation of global soil respiration by accounting for land-use changes derived from remote sensing data
http://hdl.handle.net/2241/00147523
http://hdl.handle.net/2241/0014752378adb609-3378-4b95-b0c3-4ff4e54be4d8
名前 / ファイル | ライセンス | アクション |
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JEM_200 (1.6 MB)
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Item type | Journal Article(1) | |||||
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公開日 | 2017-09-12 | |||||
タイトル | ||||||
タイトル | Estimation of global soil respiration by accounting for land-use changes derived from remote sensing data | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源 | http://purl.org/coar/resource_type/c_6501 | |||||
タイプ | journal article | |||||
著者 |
Adachi, Minaco
× Adachi, Minaco× Ito, Akihiko× Yonemura, Seiichiro× Takeuchi, Wataru |
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著者別名 |
安立, 美奈子
× 安立, 美奈子 |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Soil respiration is one of the largest carbon fluxes from terrestrial ecosystems. Estimating global soil respiration is difficult because of its high spatiotemporal variability and sensitivity to land-use change. Satellite monitoring provides useful data for estimating the global carbon budget, but few studies have estimated global soil respiration using satellite data. We provide preliminary insights into the estimation of global soil respiration in 2001 and 2009 using empirically derived soil temperature equations for 17 ecosystems obtained by field studies, as well as MODIS climate data and land-use maps at a 4-km resolution. The daytime surface temperature from winter to early summer based on the MODIS data tended to be higher than the field-observed soil temperatures in subarctic and temperate ecosystems. The estimated global soil respiration was 94.8 and 93.8 Pg C yr−1 in 2001 and 2009, respectively. However, the MODIS land-use maps had insufficient spatial resolution to evaluate the effect of land-use change on soil respiration. The spatial variation of soil respiration (Q10) values was higher but its spatial variation was lower in high-latitude areas than in other areas. However, Q10 in tropical areas was more variable and was not accurately estimated (the values were >7.5 or <1.0) because of the low seasonal variation in soil respiration in tropical ecosystems. To solve these problems, it will be necessary to validate our results using a combination of remote sensing data at higher spatial resolution and field observations for many different ecosystems, and it will be necessary to account for the effects of more soil factors in the predictive equations. | |||||
書誌情報 |
Journal of environmental management 巻 200, p. 97-104, 発行日 2017-09 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 0301-4797 | |||||
書誌レコードID | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA00251899 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1016/j.jenvman.2017.05.076 | |||||
権利 | ||||||
権利情報 | © 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ | |||||
著者版フラグ | ||||||
値 | author | |||||
出版者 | ||||||
出版者 | Elsevier |