IMHE OpenIR  > 数字山地与遥感应用中心
湿地植被净初级生产力估算模型研究综述
Alternative TitleA Review on Research Advances in Estimation Models for Net Primary Production of Vegetation inWetlands
王继燕1,2; 李爱农1; 靳华安1
Corresponding Author李爱农
2015
Source Publication湿地科学
ISSN1672-5948
Volume13Issue:5Pages:636-644
Other Abstract湿地植被净初级生产力(net primary productivity,NPP)作为湿地生态系统物质与能量循环的基础,是陆地生态系统碳循环的重要研究内容之一。估算湿地植被NPP的方法经历了站点实测和模型方法两个发展阶段,其中估算模型可以分为统计模型、参数模型和过程模型。随着计算机和遥感技术的发展,一些利用遥感信息估算NPP的新方法得到了广泛应用。简单地沿袭传统模型分类方法,不能完全涵盖所有估算湿地植被NPP的方法。回顾了湿地植被NPP估算模型,在传统模型分类的基础上,补充了遥感在湿地植被NPP估算模型中的应用,进一步将统计模型分为气候相关和遥感相关模型,将生态系统过程模型分为过程模型、过程耦合模型和遥感-过程耦合模型。在此基础上,评述了各类模型在湿地植被NPP中的研究现状,探讨了湿地植被NPP估算研究中存在的问题,指出湿地植被NPP估算的工作重点可以从提高地面实测精度、减少模型模拟不确定性、使用多源数据等方面入手,其中引入数据同化的方法实现湿地植被NPP预测将是湿地植被NPP估算模型的重要发展方向。 
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As the foundation of material and energy flows in wetland ecosystems, the net primary productivity (NPP) is one of the most important research hotpots in the terrestrial ecosystems carbon cycle. The estimation methods of vegetation NPP in the wetlands have been developed from the sampling observation to model simulation. The models could be usually classified into statistical models, light utilization efficiency models and process models. With the development of computers and remote sensing technologies, remote sensing data have been widely applied in estimating regional vegetation productivity. As shown in some existing review papers, however, the traditional classification could not completely contain all the estimation models of vegetation NPP, especially for the simulation models using remote sensing technique. This paper reviewed the NPP estimation models of almost all kinds of the vegetation in the wetlands, and especially introduced some most popular remote sensing models. The statistical models were classified into climate-productivity relationship models and remote-sensing-productivity relationship models, and the process models consisted of single process models, multiple process coupled models and remote sensing-process coupled models. In the paper, the research advances in the models for estimating NPP in the wetlands were summarized, and the limitations of these models were also discussed comprehensively and systematically. The future perspective on models research could focus on improving the accuracy of the field measurements, reducing the uncertainties of simulation, and using the multi-sources data. It is remarkable that coupling remote sensing data with process models by the data assimilation methods would become one of most important development aspects for NPP estimation of the wetlandvegetation.

Keyword湿地植被 净初级生产力 估算模型 遥感
Subject AreaQ948 ; Tp79
DOI10.13248/j.cnki.wetlandsci.2015.05.018
Indexed ByCSCD ; 北大中文核心
Language中文
CSCD IDCSCD:5574689
Funding Organization国家自然科学基金项目(41271433和41571373) ; 国家科技支撑计划项目(2012BAC19B05) ; 中国科学院委托研究与专项咨询项目(KFJ-EW-STS-020-02) ; 中国科学院“百人计划”项目(110900K242)
Citation statistics
Cited Times:5[CSCD]   [CSCD Record]
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/17236
Collection数字山地与遥感应用中心
Affiliation1.中国科学院水利部成都山地灾害与环境研究所
2.中国科学院大学
First Author Affilication中国科学院水利部成都山地灾害与环境研究所
Recommended Citation
GB/T 7714
王继燕,李爱农,靳华安. 湿地植被净初级生产力估算模型研究综述[J]. 湿地科学,2015,13(5):636-644.
APA 王继燕,李爱农,&靳华安.(2015).湿地植被净初级生产力估算模型研究综述.湿地科学,13(5),636-644.
MLA 王继燕,et al."湿地植被净初级生产力估算模型研究综述".湿地科学 13.5(2015):636-644.
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