Modelling net primary productivity of terrestrial ecosystems in East Asia based on an improved CASA ecosystem model
Yu, Deyong1; Shi, Peijun1; Shao, Hongbo2,3,4; Zhu, Wenquan1; Pan, Yaozhong1
发表期刊INTERNATIONAL JOURNAL OF REMOTE SENSING
ISSN0143-1161
2009
卷号30期号:18页码:4851-4866
关键词Satellite Ndvi
产权排序Beijing Normal Univ, MOE Acad Disaster Reduct & Emergency Management, Key Lab Environm Change & Nat Disaster, State Key Lab Earth Surface Proc & Resource Ecol;Chinese Acad Sci, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P;Chinese Acad Sci, Yantai Inst Coastal Zone Res Sustainable Dev;Qingdao Univ Sci & Technol, Inst Life Sci
通讯作者Yu, DY, Beijing Normal Univ, MOE Acad Disaster Reduct & Emergency Management, Key Lab Environm Change & Nat Disaster, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China
作者部门滨海湿地实验室
英文摘要By using a land cover map, normalized difference vegetation index (NDVI) data sets, monthly meteorological data and observed net primary productivity (NPP) data, we have improved the method of estimating light use efficiency (LUE) for different biomes and soil moisture coefficients in the Carnegie-Ames-Stanford Approach ( CASA) ecosystem model. Based on this improved model we produced an annual NPP map ( in 1999) for the East Asia region located at 10-70 degrees N, 70-170 degrees E ( about 19.66% of the terrestrial surface of the Earth). The results show that the mean NPP for the study area in 1999 was 374.12 g carbon ( C) m(-2) year(-1) and the total NPP was 1.096 x 10(14) kg C year(-1), making up 17.51-18.39% of the global NPP. Comparison between the estimated NPP obtained from this improved CASA ecosystem model and the observed NPP obtained from two NPP databases indicates that the estimated NPP is close to the observed NPP, with an average error of 5.15% for the study region. We used two different land cover maps of China to drive the improved CASA model by keeping other inputs unchanged to determine how the classification accuracy of the land cover map affects the estimated NPP, and the results indicate that an accurate land cover map is important for obtaining an accurate and reliable estimate of NPP for some regions, especially for a particular biome.; By using a land cover map, normalized difference vegetation index (NDVI) data sets, monthly meteorological data and observed net primary productivity (NPP) data, we have improved the method of estimating light use efficiency (LUE) for different biomes and soil moisture coefficients in the Carnegie-Ames-Stanford Approach ( CASA) ecosystem model. Based on this improved model we produced an annual NPP map ( in 1999) for the East Asia region located at 10-70 degrees N, 70-170 degrees E ( about 19.66% of the terrestrial surface of the Earth). The results show that the mean NPP for the study area in 1999 was 374.12 g carbon ( C) m(-2) year(-1) and the total NPP was 1.096 x 10(14) kg C year(-1), making up 17.51-18.39% of the global NPP. Comparison between the estimated NPP obtained from this improved CASA ecosystem model and the observed NPP obtained from two NPP databases indicates that the estimated NPP is close to the observed NPP, with an average error of 5.15% for the study region. We used two different land cover maps of China to drive the improved CASA model by keeping other inputs unchanged to determine how the classification accuracy of the land cover map affects the estimated NPP, and the results indicate that an accurate land cover map is important for obtaining an accurate and reliable estimate of NPP for some regions, especially for a particular biome.
文章类型Article
资助机构National Natural Science Foundation of China [40801211, 40425008]; Project of State Key Laboratory of Earth Surface Processes and Resources Ecology [070106]
收录类别SCI
语种英语
关键词[WOS]SATELLITE ; NDVI
研究领域[WOS]Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号WOS:000270299300012
引用统计
被引频次:105[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.yic.ac.cn/handle/133337/3407
专题中国科学院海岸带环境过程与生态修复重点实验室_滨海湿地实验室
作者单位1.Beijing Normal Univ, MOE Acad Disaster Reduct & Emergency Management, Key Lab Environm Change & Nat Disaster, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China
2.Chinese Acad Sci, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Peoples R China
3.Chinese Acad Sci, Yantai Inst Coastal Zone Res Sustainable Dev, Yantai 264003, Peoples R China
4.Qingdao Univ Sci & Technol, Inst Life Sci, Qingdao 266042, Peoples R China
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Yu, Deyong,Shi, Peijun,Shao, Hongbo,et al. Modelling net primary productivity of terrestrial ecosystems in East Asia based on an improved CASA ecosystem model[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2009,30(18):4851-4866.
APA Yu, Deyong,Shi, Peijun,Shao, Hongbo,Zhu, Wenquan,&Pan, Yaozhong.(2009).Modelling net primary productivity of terrestrial ecosystems in East Asia based on an improved CASA ecosystem model.INTERNATIONAL JOURNAL OF REMOTE SENSING,30(18),4851-4866.
MLA Yu, Deyong,et al."Modelling net primary productivity of terrestrial ecosystems in East Asia based on an improved CASA ecosystem model".INTERNATIONAL JOURNAL OF REMOTE SENSING 30.18(2009):4851-4866.
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