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遥感技术与应用  2019, Vol. 34 Issue (2): 303-312    DOI: 10.11873/j.issn.1004-0323.2019.2.0303
模型与反演     
基于植被指数季节变化曲线的年总初级生产力估算
张赫林1,2,彭代亮1,张肖1,范海生3,徐富宝1,叶回春1,王大成1
(1.中国科学院遥感与数字地球研究所数字地球重点实验室,北京 100094;
2.重庆交通大学建筑与城市规划学院,重庆 400074;
3.珠海欧比特宇航科技股份有限公司卫星大数据事业部,广东 珠海 519080)
Annual Total Gross Primary Production Estimation based on Vegetation Indices Seasonal Variation Curve
Zhang Helin1,2,Peng Dailiang1,Zhang Xiao1,Fan Haisheng3,Xu Fubao1,Ye Huichun1,Wang Dacheng1
(1.Key Laboratory of Digital Earth Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100094,China;
2.College of Architecture and Urban Planning,Chongqing Jiaotong University,Chongqing 400074,China;
3.Department of Satellite Big Data Business,Zhuhai Orbita Aerospace Science &Technology Co.,ltd.,Zhuhai 519080,China)
 全文: PDF(13782 KB)  
Abstract: For the estimation of annual Gross Primary Productivity(GPP),it is proposed an estimation method with simple parameters and small errors.By taking each type of vegetation in the area of Three-North Shelterbelt Program(TNSP) as the research subject,the MODIS vegetation indices were obtained,and the seasonal variation curve of vegetation indices were built.Then,the fitting relation between the integral of time series vegetation indices(ΣVIs) and GPP products of MODIS was established,so as to realize a simple GPP estimation method and study the applicable ΣVIs for estimating the GPP of all vegetation types.The results show that:(1) ΣVIs is suitable for estimating the annual total GPP in research area and significantly correlated with MODIS GPP at the confidence level of p<0.01;(2) ΣEVI2 is applicable to estimate the GPP of evergreen needleleaf forest,decidious needleleaf forest,decidious broadleaf forest,mixed forest,woody savannas,savannas,permanent wetlands,croplands,croplands/natural vegetation mosaic,while the effect of ΣNDVI for estimating the GPP of closed shrublands,open shrublands,grasslands,croplands,and barren or sparsely vegetated is superior to ΣEVI andΣEVI2;(3) Since the NDVI itself is saturated in the area of high Leaf Area Index(LAI),the error of estimating the GPP of high LAI vegetation type by ΣNDVI is larger,while using ΣEVI and ΣEVI2 to estimate them has better accuracy,and the limitation from blue band of EVI2 reduces compared with EVI,which can be applied to the GPP research of long time series better.


Key words: GPP    Three-North Shelterbelt    NDVI    EVI    EVI2    Time Series Curve Integral
收稿日期: 2018-04-17 出版日期: 2019-05-10
ZTFLH:  TP79  
基金资助: 国家自然科学基金项目(41571423),中国科学院战略性先导科技专项(XDA19080304、XDA19070203),国网经研院自主投入科技项目(ZZKJ-2018-10)。
作者简介: 张赫林(1994-),男,内蒙古呼伦贝尔人,硕士研究生,主要从事遥感监测方面的研究。E-mail:1656227412@qq.com。
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引用本文:

张赫林, 彭代亮, 张肖, 范海生, 徐富宝, 叶回春, 王大成. 基于植被指数季节变化曲线的年总初级生产力估算[J]. 遥感技术与应用, 2019, 34(2): 303-312.

Zhang Helin, Peng Dailiang, Zhang Xiao, Fan Haisheng, Xu Fubao, Ye Huichun. Annual Total Gross Primary Production Estimation based on Vegetation Indices Seasonal Variation Curve. Remote Sensing Technology and Application, 2019, 34(2): 303-312.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2019.2.0303        http://www.rsta.ac.cn/CN/Y2019/V34/I2/303

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