地球信息科学学报

地球信息科学学报 ›› 2014, Vol. 16 ›› Issue (2): 335-340.doi: 10.3724/SP.J.1047.2014.00335

• 遥感科学与应用技术 • 上一篇    

干旱区草原地上植被生物量估算——以乌图美仁大草原芦苇植被为例

行敏锋, 何彬彬   

  1. 电子科技大学资源与环境学院, 成都 611731
  • 收稿日期:2013-04-02 修回日期:2013-04-23 出版日期:2014-03-10 发布日期:2014-03-10
  • 通讯作者: 何彬彬（1972- ），男，教授，博导，研究方向为定量遥感及数据挖掘。E-mail：binbinhe@uestc.edu.cn E-mail:binbinhe@uestc.edu.cn
  • 作者简介:行敏锋（1982- ），男，博士生，研究方向为定量遥感。E-mail：xingminfeng@163.com
  • 基金资助:

    中央高校基本科研业务费（ZYGX2012Z005）资助。

Estimation of Aboveground Biomass in Arid Region with ASAR Data and TM Data：A Case Study over the Reed Vegetation of Wutumeiren Prairie, Qinghai Province

XING Minfeng, HE Binbin   

  1. School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China
  • Received:2013-04-02 Revised:2013-04-23 Online:2014-03-10 Published:2014-03-10
  • Contact: 10.3724/SP.J.1047.2014.00335 E-mail:binbinhe@uestc.edu.cn

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摘要：

草原是干旱区生态系统中重要的可再生资源。本文基于草本植被的结构特征，利用ASAR和TM数据，结合MIMICS模型，提出了一种估算干旱区草原地上植被生物量的方法。该方法将光学遥感数据容易反演的叶面积指数（LAI）作为反演生物量模型的参数之一，并利用LAI成功估算了单位面积内的草本植被密度。将地上生物量作为输入变量代入改进的MIMICS模型，利用查找表方法，计算出地上植被生物量。然后，将该方法应用于乌图美仁草原的地上植被生物量的反演。结果表明，该方法能够成功地反演干旱区草原草本植被地上生物量，精度达到R2=0.8562，RMSD=0.6263。最后，分析了该方法估算植被生物量的误差来源。

关键词: MIMICS模型, 后向散射系数, 生物量, 干旱区草原

Abstract:

Grasslands are important renewable resources in ecosystems of arid areas. As one of the important components of prairie ecosystems, aboveground biomass is the key indicator of health status of the prairie ecosystems. Comparing to the significant limitations of the traditional method of biomass, the satellite remote sensing provides a unique effective and efficient means in biomass monitoring and assessment. In this paper, we proposed a retrieval methodology for herbaceous vegetation biomass based on the vegetation structure characteristic and Michigan Microwave Canopy Scattering (MIMICS) model using the ASAR and TM data. A two-layer canopy reflectance model (ACRM) was used to inverse the Leaf Area Index (LAI) which can be easily retrieved from the optical remote sensing data. Then LAI was used to get the number of plants per unit area. The aboveground biomass served as an input parameter was input into the adaption of MIMICS model which adopted for characterizing the backscatter from herbaceous vegetation by deleting the scatter component associated with ground-trunks. Then, based on established equations which used the dual-polarized radar data, the aboveground biomass was calculated using the lookup table. The method was applied to retrieve the biomass of Wutumeiren prairie, Qinghai Province. Results indicated that the method was of the operational potential in aboveground biomass of the herbaceous vegetation in arid region. And a good accuracy of the biomass retrieval was achieved (R2=0.8562, RMSD=0.6263). Finally, we analyzed the error sources of biomass estimation using this method. The sources of error might be come from two aspects, i.e. error of the input model parameters, and the ill-posed inversion problem, for which, the mean value was used as the inverse results when the solution is not unique.

Key words: prairie of arid regions, MIMICS model, biomass, backscattering coefficient