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中国沙漠 ›› 2015, Vol. 35 ›› Issue (2): 493-498.DOI: 10.7522/j.issn.1000-694X.2014.00036

• 生态与经济 • 上一篇    下一篇

绿洲植被覆盖度遥感信息提取——以敦煌绿洲为例

张号, 屈建军, 张克存   

  1. 中国科学院寒区旱区环境与工程研究所 沙漠与沙漠化重点实验室/敦煌戈壁荒漠生态与环境研究站, 甘肃 兰州 730000
  • 收稿日期:2014-02-20 修回日期:2014-03-28 出版日期:2015-03-20 发布日期:2015-03-20
  • 通讯作者: 张克存(Email: kecunzh@lzb.ac.cn)
  • 作者简介:张号(1988-), 男, 山东济南人, 硕士, 主要从事地理信息系统和遥感在环境监测中的应用。Email: zhanghaocas@163.com
  • 基金资助:

    国家自然科学基金项目(41371027,41271023)

Vegetation Cover Information Extraction Technology for Dunhuang Oasis Based on Remote Sensing Images

Zhang Hao, Qu Jianjun, Zhang Kecun   

  1. Dunhuang Gobi Research Station/Key Laboratory of Desert and Desertification, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China
  • Received:2014-02-20 Revised:2014-03-28 Online:2015-03-20 Published:2015-03-20

摘要:

以敦煌绿洲为研究区,利用Landsat TM遥感数据,通过归一化植被指数(NDVI)和混合像元分解两种方法,提取了敦煌绿洲的植被覆盖度信息。在基于NDVI提取植被覆盖度时,选取了基于NDVI的像元二分模型; 在混合像元分解过程中,对遥感影像进行波段反射率归一化处理和最小噪声变换(MNF),确定了3个类型端元:植被、不透水表面/土壤、水体/阴影; 最后利用高分辨率遥感影像验证对比了两种提取方法的精度。结果表明:混合像元分解更能准确地提取敦煌地区植被覆盖度信息,其线性相关系数为0.8915,均方根误差为0.0882,而且提取结果更符合实际情况,可以为敦煌植被状况监测及生态环境保护提供科学建议。

关键词: 敦煌绿洲, 植被覆盖度, 归一化植被指数, 混合像元分解

Abstract:

Taking Dunhuang oasis for example, Normalized Difference Vegetation Index (NDVI) and Spectral Mixture Analysis (SMA) were used to extract the vegetation coverage information from Landsat TM images. While extracting vegetation coverage based on NDVI, we selected a dimidiate pixel model; In the process of SMA, through reflectance normalization and minimum noise transform (MNF), three end members were identified: vegetation, impervious surface/soil, water/shadow. In the end, the results were tested by high resolution Quickbird images. The results showed that SMA could better extract vegetation cover information in arid area with the better accuracy(R=0.8915; RMSE=0.0882). This study could provide the reference for the protection of ecological environment in Dunhuang oasis.

Key words: Dunhuang oasis, vegetation coverage, NDVI, Spectral Mixture Analysis

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