自然资源学报

自然资源学报 ›› 2015, Vol. 30 ›› Issue (6): 917-927.doi: 10.11849/zrzyxb.2015.06.003

• 资源生态 • 上一篇    下一篇

南方红壤典型水土流失区植被覆盖度变化及其生态效应评估——以福建省长汀县为例

张灿, 徐涵秋, 张好, 唐菲, 林中立   

  1. 福州大学环境与资源学院, 福州大学遥感信息工程研究所, 福建省水土流失遥感监测评估与灾难防治重点实验室, 福州350108
  • 收稿日期:2014-04-17 修回日期:2014-07-13 出版日期:2015-06-20 发布日期:2015-06-20
  • 通讯作者: 徐涵秋(1955-),男,江苏盐城人,博士(爱尔兰国立大学),教授,博导,主要从事环境与资源遥感研究.E-mail:hxu@fzu.edu.cn E-mail:hxu@fzu.edu.cn
  • 作者简介:张灿(1990-),女,河南邓州人,硕士研究生,研究方向为环境与资源遥感.E-mail:1721374724@qq.com
  • 基金资助:

    国家科技支撑计划项目(2013BAC0801-05).

Fractional Vegetation Cover Change and Its Ecological Effect Assessment in a Typical Reddish Soil Region of Southeastern China: Changting County, Fujian Province

ZHANG Can, XU Han-qiu, ZHANG Hao, TANG Fei, LIN Zhong-li   

  1. College of Environment and Resources, Institute of Remote Sensing Information Engineering, Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Protection, Fuzhou University, Fuzhou 350108, China
  • Received:2014-04-17 Revised:2014-07-13 Online:2015-06-20 Published:2015-06-20

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被引次数

41

摘要：

南方红壤典型水土流失区——福建省长汀县曾因生态破坏导致严重的水土流失.经过多年以植树为主的生态修复,该县生态面貌有了明显的改观.论文首先采用线性光谱混合分析模型计算植被覆盖度,并在此原始模型的基础上提出了对地形阴影进行修正的方法来获取植被覆盖度.精度验证表明,在线性光谱混合分析模型中加入山地指数(NDMVI)波段能够削弱地形阴影问题,提高植被覆盖度反演精度.在此基础上利用多时相遥感影像分析了长汀2001—2013 年植被覆盖度的时空变化,并利用遥感生态指数(RSEI)定量评价了长汀水土流失生态修复的效果.结果表明,经过13 a 的水土流失治理,长汀的植被覆盖度有了明显的升高,从2001 年的75.1%上升到2013 年的86.5%.RSEI 生态指数值也随之上升,生态等级为优良的面积比例从85.83%增加到90.59%,反映了长汀县生态质量整体有了明显的提高.植被的生态效应定量研究表明,长汀县的植被覆盖度每增加10%,RSEI 生态指数值至少提高10%,植被覆盖度的生态提升效应显著.

关键词: 植被覆盖度, 长汀, 遥感, 遥感生态指数(RSEI), 线性光谱混合分析

Abstract:

Changting County in Fujian Province is a typical reddish soil erosion region in southeastern China. The county has been called the flame mountains area due to severe soil erosion on barren terrains. After years of ecological restoration, the local ecosystem has been improved remarkably and the barren lands are now covered with forests. This paper used remote sensing techniques to study the fractional vegetation cover (FVC) changes and quantitatively evaluated the effects of ecological restoration in Changting during the period from 2001 to 2013 by using the remote sensing ecological index (RSEI). Two remote-sensing based models for estimating FVC have been compared in order to select a suitable model for the retrieval of the FVC in the study area. One is the commonly-used Linear Spectral Mixture Analysis (LSMA) model, and the other is the LSMAM model. The LSMAM is based on the LSMA but with a Normalized Difference Mountain Vegetation Index (NDMVI) derived band added into the model. The comparative analysis confirms that the LSMAM model has higher accuracy than the LSMA model, indicated by its lower root mean square error and higher correlation with referenced FVC data because the addition of the NDMVI band into the model could eliminate shadow problem caused by topographic relief in the mountainous areas. Therefore, the LSMAM model was selected to retrieve the FVC in this study. The result indicates that the 13-year effort for treatment of the soil loss in the county has led to a notable increase in county's FVC from 75.1% (2001) to 86.5% (2013). Meanwhile, the RSEI- based analysis also indicates a significant improvement of the county's ecological quality during the same period, because of the increase in RSEI value from 0.750 to 0.787, along with an increase in high-RSEI-level area from 85.83% to 90.59%. Regression analysis between FVC and RSEI suggests that each 10% increment in FVC could raise the RSEI by 10%. This clearly indicates a significant effect of FVC on county's ecological quality.

Key words: fractional vegetation cover, RSEI, Linear Spectral Mixture Analysis, remote sensing, Changting

中图分类号: 

  • TP79Q948