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遥感技术与应用  2021, Vol. 36 Issue (4): 742-750    DOI: 10.11873/j.issn.1004-0323.2021.4.0742
湿地遥感专栏     
芦苇湿地植被NPP估算方法探索与应用
罗玲1(),毛德华1,2(),张柏1,王宗明1,3,杨桄4
1.中国科学院东北地理与农业生态研究所,吉林 长春 130102
2.中国科学院长春净月潭遥感实验站,吉林 长春 130102
3.国家地球系统科学数据中心,北京 100101
4.空军航空航天大学,吉林 长春 130022
Exploration and Application of NPP Estimation Model for Phragmites Australis Wetlands
Ling Luo1(),Dehua Mao1,2(),Bai Zhang1,Zongming Wang1,3,Guang Yang4
1.Key Laboratory of Wetland Ecology and Environment,Northeast Institute of Geography and Agroecology,Chinese Academy of Sciences,Changchun 130102,China
2.Changchun Jingyuetan Remote Sensing Experiment Station,Chinese Academy of Sciences,Changchun 130102,China
3.National Earth System Science Data Center,Beijing 100101,China
4.Air Force Aviation University,Changchun 130022,China
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摘要:

作为表征湿地生态系统健康的重要指标,湿地植被净初级生产力(NPP)的精准估算对于理解全球变化以及区域碳循环具有重要的支撑作用。基于Landsat 8 OLI遥感影像和大量实测数据,以光能利用率模型基本结构式为基础,构建和评价了芦苇湿地植被NPP估算的不同遥感驱动模型,并以东北3个典型芦苇湿地保护区为例进行了验证与应用。结果表明:以NPP = ff(VI1)) × f(VI2) 结构与NDVI和MSAVI两个植被指数作为自变量的模型最优,模型精度为89.2%,明显高于NPP低空间分辨率产品和CASA模型的模拟结果。根据该模型估算的东北地区七星河、查干湖和双台河口芦苇湿地的NPP均值分别为3 001、3 050和3 621 gC·m–2·a–1。受水文条件和人类活动影响,各湿地样区间NPP具有典型的空间分布异质性。实验提出的框架模型可为小尺度上湿地生态系统健康评估或湿地生态系统恢复效果评价等指标获取提供方法借鉴。

关键词: 净初级生产力植被指数Landsat芦苇湿地光能利用率模型    
Abstract:

Researches on Net Primary Productivity (NPP) of wetland vegetation are of great significance to the study of global change and carbon cycle. Taking three typical wetland samples in Northeast China as study area, based on Landsat 8 OLI and a large number of field data, this paper contrasted the combination forms of the basic structural formula of light utilization model. Results show that the model based on structure of NPP = ffVI1))×fVI2) and two vegetation indices (NDVI and MSAVI) are optimal, with an accuracy of 89%, which was higher than those ofMODIS BIO-BGC and CASA model. In 2014, mean NPP of Phragmites australis for Qixinghe, Chaganhu and Shuangtaihekou wetland was 3 001, 3 050 and 3 621 gC·m–2·yr–1, respectively. NPP is obvious different spatially in three wetland samples, which is mainly influenced by hydrological conditions and human activities. For Phragmites australis wetland with small spatial scale, remote sensing method can be used to estimate NPP conveniently and efficiently. This study can provide a reference and guide for the study of wetland vegetation NPP regionally.

Key words: Net Primary Productivity (NPP)    Vegetation index    Landsat    Phragmites australis wetland    Light utilization model
收稿日期: 2021-02-03 出版日期: 2021-09-26
ZTFLH:  TP79  
基金资助: 中国科学院战略性先导科技专项(XDA19040500);国家自然科学基金项目(41771383)
通讯作者: 毛德华     E-mail: luoling@iga.ac.cn;maodehua@iga.ac.cn
作者简介: 罗玲(1984-),女,黑龙江哈尔滨人,博士,主要从事资源环境遥感研究。E?mail: luoling@iga.ac.cn
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引用本文:

罗玲,毛德华,张柏,王宗明,杨桄. 芦苇湿地植被NPP估算方法探索与应用[J]. 遥感技术与应用, 2021, 36(4): 742-750.

Ling Luo,Dehua Mao,Bai Zhang,Zongming Wang,Guang Yang. Exploration and Application of NPP Estimation Model for Phragmites Australis Wetlands. Remote Sensing Technology and Application, 2021, 36(4): 742-750.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2021.4.0742        http://www.rsta.ac.cn/CN/Y2021/V36/I4/742

图1  研究区在东北地区位置及样区范围示意图
植被指数NDVICIgreenMSAVIRVIWDVI
相关系数0.490**0.2570.633**0.476**0.273*
表1  芦苇湿地植被NPP与不同植被指数的相关系数
图2  东北地区典型芦苇湿地APAR与最优植被指数MSAVI间的关系
图3  东北地区典型芦苇湿地植被光能利用率(LUE)与冠层叶绿素含量间的关系
数据源

MODIS BIO-BGC

(500 m)

CASA[13]

(250 m)

本研究结果

(30 m)

实测

NPP

芦苇NPP (gC·m–2·a–1388.0745.03 439.03 104.0
精度/%12.524.189.2
表2  不同模型不同分辨率遥感影像的芦苇植被NPP估算结果对比
图4  利用本文构建模型模拟的东北地区典型湿地芦苇植被NPP空间分布格局
图5  3个典型芦苇湿地样区NPP及气候因子对比
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