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地球科学进展  2010, Vol. 25 Issue (3): 317-326    DOI: 10.11867/j.issn.1001-8166.2010.03.0317
数字黑河     
基于时序MODIS NDVI的黑河流域土地覆盖分类研究
顾娟,李新,黄春林
中国科学院寒区旱区环境与工程研究所,甘肃  兰州  730000  
Land Cover Classification Based on Time-series MODIS NDVI Data in Heihe River Basin
Gu Juan,Li Xin, Huang Chunlin
Cold and Arid Region Environmental and Engineering Research Institute, CAS, Lanzhou  730000, China  
 全文: PDF(1750 KB)  
摘要:

 归一化植被指数(NDVI)是植被生长状态及植被覆盖度的最佳指示因子,其时序数据也已成为基于生物气候特征开展大区域植被和土地覆盖分类的基本手段。基于时序NDVI数据的土地覆盖分类,即通过提取NDVI时间信号所包含的植被生物学参数,构建起一个包含植被生物学信息的分类特征空间。利用2006年重建得到的MODIS NDVI 16天合成时间序列数据,并结合1 km分辨率的DEM数据、野外实地调查资料等辅助数据,综合分析了不同土地覆盖类型对应的时序NDVI谱线及其第一、二谐波的特征阈值,建立决策树对黑河流域的土地覆盖开展分类研究。结果表明,基于时序MODIS NDVI谱线特征的决策树分类精度为78%,Kappa系数为0.74。利用1 km时序MODIS NDVI时间序列获得较为准确的黑河流域土地覆盖类型是可行的。

关键词: MODIS NDVI时间序列土地覆盖分类黑河流域    
Abstract:

Temporal changes in the normalized difference vegetation index (NDVI) have been widely used in vegetation mapping due to the usefulness of NDVI datasets in distinguishing characteristic seasonal differences in the phenology of greenness of vegetation cover. The Timeseries Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI datasets hold considerable promise for large-area land cover classification given their global coverage, intermediate spatial resolution, high temporal resolution (16=day composite period), and cost-free status. This study focused on generating effective classification features from multi-temporal MODIS NDVI datasets to improve classification accuracy in the Heihe River Basin. Two types of features were derived from reconstructed multi-temporal MODIS NDVI datasets. The first are the basic parameters including the annual maximum NDVI, the mean NDVI during the growing season, the inter-annual variability of NDVI and the annual mean NDVI. The second are the amplitude and phase information of the first and second harmonic components derived from the shape of the time-series NDVI profile. Additionally, DEM with 1km resolution has also been used to simplify the current scheme. According to the validated results with 469 ground truth survey samples, the overall land cover classification accuracy using the decision tree was 78% and a Kappa coefficient is 0.74. The results support using decision tree classification based on 1km MODIS NDVI temporal and derived parameters to provide an up-to-date land cover mapping. However, the current decision tree does not work well in the downstream of  the Heihe River Basin since the NDVI of non-vegetation types can not represent the temporal feature of these types. Thus, new effort is necessary in the future in order to improve the overall performance on this issue.

Key words: MODIS NDVI    Time series    Land cover Classification    Heihe
收稿日期: 2009-04-21 出版日期: 2010-03-10
:  TP79  
基金资助:

国家自然科学基金项目“陆面数据同化中的贝叶斯滤波方法研究”(编号:40771036);国家自然科学基金面上项目“陆地碳循环遥感与模型模拟的融合方法研究”(编号:40871190);国家自然科学基金青年基金项目“基于数据同化方法的蒸散发遥感估算及时间尺度扩展研究”(编号:40801126)资助.

通讯作者: 顾娟     E-mail: guijuan@lzb.ac.cn
作者简介: 顾娟 (1982-), 女,甘肃白银人,博士,主要从事时间序列遥感应用研究.E-mail:guijuan@lzb.ac.cn
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引用本文:

顾娟,李新,黄春林. 基于时序MODIS NDVI的黑河流域土地覆盖分类研究[J]. 地球科学进展, 2010, 25(3): 317-326.

Gu Juan,Li Xin,Huang Chunlin. Land Cover Classification Based on Time-series MODIS NDVI Data in Heihe River Basin. Advances in Earth Science, 2010, 25(3): 317-326.

链接本文:

http://www.adearth.ac.cn/CN/10.11867/j.issn.1001-8166.2010.03.0317        http://www.adearth.ac.cn/CN/Y2010/V25/I3/317

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