基于NDVI数据的黄河流域地表植被覆盖综合分类研究

NDVI Data Based Study on Complex Classification of Vegetation Cover of Yellow River Basin

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 multidimension 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 ecologicalenvironmental problems, hydrology and water resources of Yellow River basin.