The analysis of net primary productivity in China based on GEOLUE model

Zhiqiang Gao; Wei Gao; Cao Xiaoming; Maosi Chen

doi:10.1117/12.928296

The analysis of net primary productivity in China based on GEOLUE model

Zhiqiang Gao^*
, Wei Gao
, Cao Xiaoming
, Maosi Chen

^*此作品的通讯作者

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

GEOLUE model was designed with Light Use Efficiency (LUE) mechanism and was validated with observed data and models comparison (GLOPEM, CASA, and CEVSA). We found that: GEOLUE model correctly simulates monthly, quarterly and annual variation of Net Primary Product (NPP) in different vegetation communities under monsoon climate. The spatial distribution of NPP simulated by GEOLUE matched up to 96.67% with that of forest and shrub land. The GEOLUE model perfectly simulated the seasonal characteristics and spatial pattern of biomass in different types of vegetation. The total amount NPP of China simulated by GEOLUE is 0.667GtC in spring, 1.365GtC in summer, 0.587GtC in autumn and 0.221GtC in winter. The average total NPP of China for 5 years is 2.84GtC / year.

源语言	英语
主期刊名	Remote Sensing and Modeling of Ecosystems for Sustainability IX
DOI	https://doi.org/10.1117/12.928296
出版状态	已出版 - 2012
已对外发布	是
活动	Remote Sensing and Modeling of Ecosystems for Sustainability IX - San Diego, CA, 美国期限: 16 8月 2012 → 16 8月 2012

出版系列

姓名	Proceedings of SPIE - The International Society for Optical Engineering
卷	8513
ISSN（印刷版）	0277-786X

会议

会议	Remote Sensing and Modeling of Ecosystems for Sustainability IX
国家/地区	美国
市	San Diego, CA
时期	16/08/12 → 16/08/12

联合国可持续发展目标

此成果有助于实现下列可持续发展目标：

可持续发展目标 15 陆地生物

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10.1117/12.928296

其它文件与链接

链接到 Scopus 的出版物

引用此

@inproceedings{117a8cdaa7af4692b9927d500c790b56,

title = "The analysis of net primary productivity in China based on GEOLUE model",

abstract = "GEOLUE model was designed with Light Use Efficiency (LUE) mechanism and was validated with observed data and models comparison (GLOPEM, CASA, and CEVSA). We found that: GEOLUE model correctly simulates monthly, quarterly and annual variation of Net Primary Product (NPP) in different vegetation communities under monsoon climate. The spatial distribution of NPP simulated by GEOLUE matched up to 96.67\% with that of forest and shrub land. The GEOLUE model perfectly simulated the seasonal characteristics and spatial pattern of biomass in different types of vegetation. The total amount NPP of China simulated by GEOLUE is 0.667GtC in spring, 1.365GtC in summer, 0.587GtC in autumn and 0.221GtC in winter. The average total NPP of China for 5 years is 2.84GtC / year.",

keywords = "China, Model of Light Use Efficiency, Net Primary Product (NPP), Simulation",

author = "Zhiqiang Gao and Wei Gao and Cao Xiaoming and Maosi Chen",

year = "2012",

doi = "10.1117/12.928296",

language = "英语",

isbn = "9780819492302",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

booktitle = "Remote Sensing and Modeling of Ecosystems for Sustainability IX",

note = "Remote Sensing and Modeling of Ecosystems for Sustainability IX ; Conference date: 16-08-2012 Through 16-08-2012",

}

Gao, Z, Gao, W, Xiaoming, C & Chen, M 2012, The analysis of net primary productivity in China based on GEOLUE model. 在 Remote Sensing and Modeling of Ecosystems for Sustainability IX., 85130R, Proceedings of SPIE - The International Society for Optical Engineering, 卷 8513, Remote Sensing and Modeling of Ecosystems for Sustainability IX, San Diego, CA, 美国, 16/08/12. https://doi.org/10.1117/12.928296

TY - GEN

T1 - The analysis of net primary productivity in China based on GEOLUE model

AU - Gao, Zhiqiang

AU - Gao, Wei

AU - Xiaoming, Cao

AU - Chen, Maosi

PY - 2012

Y1 - 2012

N2 - GEOLUE model was designed with Light Use Efficiency (LUE) mechanism and was validated with observed data and models comparison (GLOPEM, CASA, and CEVSA). We found that: GEOLUE model correctly simulates monthly, quarterly and annual variation of Net Primary Product (NPP) in different vegetation communities under monsoon climate. The spatial distribution of NPP simulated by GEOLUE matched up to 96.67% with that of forest and shrub land. The GEOLUE model perfectly simulated the seasonal characteristics and spatial pattern of biomass in different types of vegetation. The total amount NPP of China simulated by GEOLUE is 0.667GtC in spring, 1.365GtC in summer, 0.587GtC in autumn and 0.221GtC in winter. The average total NPP of China for 5 years is 2.84GtC / year.

AB - GEOLUE model was designed with Light Use Efficiency (LUE) mechanism and was validated with observed data and models comparison (GLOPEM, CASA, and CEVSA). We found that: GEOLUE model correctly simulates monthly, quarterly and annual variation of Net Primary Product (NPP) in different vegetation communities under monsoon climate. The spatial distribution of NPP simulated by GEOLUE matched up to 96.67% with that of forest and shrub land. The GEOLUE model perfectly simulated the seasonal characteristics and spatial pattern of biomass in different types of vegetation. The total amount NPP of China simulated by GEOLUE is 0.667GtC in spring, 1.365GtC in summer, 0.587GtC in autumn and 0.221GtC in winter. The average total NPP of China for 5 years is 2.84GtC / year.

KW - China

KW - Model of Light Use Efficiency

KW - Net Primary Product (NPP)

KW - Simulation

UR - https://www.scopus.com/pages/publications/84872538724

U2 - 10.1117/12.928296

DO - 10.1117/12.928296

M3 - 会议稿件

AN - SCOPUS:84872538724

SN - 9780819492302

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Remote Sensing and Modeling of Ecosystems for Sustainability IX

T2 - Remote Sensing and Modeling of Ecosystems for Sustainability IX

Y2 - 16 August 2012 through 16 August 2012

ER -

The analysis of net primary productivity in China based on GEOLUE model

摘要

出版系列

会议

联合国可持续发展目标

访问文件

其它文件与链接

指纹

引用此