中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Tower-based validation and improvement of modis gross primary production in an alpine swamp meadow on the tibetan plateau

文献类型:期刊论文

作者Niu, Ben1,2; He, Yongtao1; Zhang, Xianzhou1; Fu, Gang1; Shi, Peili1; Du, Mingyuan3; Zhang, Yangjian1; Zong, Ning1
刊名Remote sensing
出版日期2016-07-01
卷号8期号:7页码:19
关键词Alpine swamp meadow Mod17a2 algorithm Eddy covariance (ec) Light use efficiency (lue) Gross primary production (gpp) Tibetan plateau
ISSN号2072-4292
DOI10.3390/rs8070592
通讯作者Zhang, xianzhou(zhangxz@igsnrr.ac.cn)
英文摘要Alpine swamp meadow on the tibetan plateau is among the most sensitive areas to climate change. accurate quantification of the gpp in alpine swamp meadow can benefit our understanding of the global carbon cycle. the 8-day moderate resolution imaging spectroradiometer (modis) gross primary production (gpp) products (gpp_mod) provide a pathway to estimate gpp in this remote ecosystem. however, the accuracy of the gpp_mod estimation in this representative alpine swamp meadow is still unknown. here five years gpp_mod was validated using gpp derived from the eddy covariance flux measurements (gpp_ec) from 2009 to 2013. our results indicated that the gpp_ec was strongly underestimated by gpp_mod with a daily mean less than 40% of ec measurements. to reduce this error, the ground meteorological and vegetation leaf area index (lai(g)) measurements were used to revise the key inputs, the maximum light use efficiency (epsilon(max)) and the fractional photosynthetically active radiation (fpar(m)) in the mod17 algorithm. using two approaches to determine the site-specific epsilon(max) value, we suggested that the suitable epsilon(max) was about 1.61 g c mj (1) for this alpine swamp meadow which was considerably larger than the default 0.68 g c mj(-1) for grassland. the fpar(m) underestimated 22.2% of the actual fpar (fpar(g)) simulated from the lai(g) during the whole study period. model comparisons showed that the large inaccuracies of gpp_mod were mainly caused by the underestimation of the epsilon(max) and followed by that of the undervalued fpar. however, the dao meteorology data in the mod17 algorithm did not exert a significant affection in the modis gpp underestimations. therefore, site-specific optimized parameters inputs, especially the epsilon(max) and fpar(g), are necessary to improve the performance of the mod17 algorithm in gpp estimation, in which the calibrated mod17a2 algorithm (gpp_modr3) could explain 91.6% of gpp_ec variance for the alpine swamp meadow.
WOS关键词LIGHT-USE EFFICIENCY ; NET PRIMARY PRODUCTION ; ECOSYSTEM CO2 EXCHANGE ; TERRESTRIAL GROSS ; EDDY COVARIANCE ; CARBON-DIOXIDE ; SATELLITE MEASUREMENTS ; FLUX MEASUREMENTS ; ABSORBED PAR ; WATER-VAPOR
WOS研究方向Remote Sensing
WOS类目Remote Sensing
语种英语
WOS记录号WOS:000382224800062
出版者MDPI AG
URI标识http://www.irgrid.ac.cn/handle/1471x/2375461
专题中国科学院大学
通讯作者Zhang, Xianzhou
作者单位1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosystem Network Observat & Modeling, Lhasa Plateau Ecosystem Res Stn, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Natl Agr & Food Res Org, Inst Agroenvironm Sci, 3-1-3 Kannondai, Tsukuba, Ibaraki 3058604, Japan
推荐引用方式
GB/T 7714
Niu, Ben,He, Yongtao,Zhang, Xianzhou,et al. Tower-based validation and improvement of modis gross primary production in an alpine swamp meadow on the tibetan plateau[J]. Remote sensing,2016,8(7):19.
APA Niu, Ben.,He, Yongtao.,Zhang, Xianzhou.,Fu, Gang.,Shi, Peili.,...&Zong, Ning.(2016).Tower-based validation and improvement of modis gross primary production in an alpine swamp meadow on the tibetan plateau.Remote sensing,8(7),19.
MLA Niu, Ben,et al."Tower-based validation and improvement of modis gross primary production in an alpine swamp meadow on the tibetan plateau".Remote sensing 8.7(2016):19.

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来源:中国科学院大学

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