摘要
在地理信息系统支持下,文章以时间分辨率为植物一个完整生长周期、空间分辨率1km×1km的NOAA/AVHRR遥感影像的NDVI指标为数据源,采用目前较为流行的主成分变换法,结合气象资料和数字高程模型(DEM),参考相关的地理基础图件,对黄河流域地表植被覆盖的进行综合分类。与传统对单一NOAA/AVHRR图像NDVI数据进行分类的方法相比,综合分类方法获得了较高的分类精度,取得了较好的效果。
With the support of Geography Information System (GIS), a multidimension classification method was adopted to classify vegetation cover of Yellow River basin synthetically. Taking the NDVI data of NOAA/AVHRR remote sensing image as data source with spatial and temporal resolution at 1 km×1 km and a whole vegetation growth cycle, the method employed the presently popular principal component analysis technique with combination of climate information, Digital Elevation Model (DEM), and relevant geographical ancillary maps. Compared with traditional single NDVI data classification method, the complex classification method acquires better classification resolution, which will be more benefit for study on increasing prominent ecologicalenvironmental problems, hydrology and water resources of Yellow River basin.
出处
《水土保持研究》
CSCD
2003年第4期88-91,共4页
Research of Soil and Water Conservation
基金
国家重点基础发展规划项目[黄河流域水资源演化与可再生性维持机理
编号:G1999043601(973)]资助。
关键词
黄河流域
地表植被覆盖
NDVI
主成分变换
Yellow River basin
vegetation cover
NDVI
principal component analysis