面向对象的土地利用遥感分类方法研究

Research of Object-oriented Land Use Remote Sensing Classification Method

以重庆市忠县为研究区,以LANDSAT-5 TM影像为数据源,利用TM及其衍生指数、DEM及其衍生数据,借助ENVI4.8、ArcGIS10.0以及eCognition软件,进行土地利用遥感信息提取方法研究,通过综合利用基于知识的决策树分类和基于样本的最近邻分类,对研究区进行土地利用遥感信息提取,并与监督分类和非监督分类方法相比进行精度评价。研究结果表明,与传统分类方法相比较,面向对象分类方法精度更高。

Taking Zhongxian in Chongqing as study area, LANDSAT 5 TM images as data sources, using TM and its derivative index, DEM and its derived data, with the help of ENVI4.8, ArcGIS10.0 and eCognition software, the land use remote sensing information extraction methods were studied. Through the comprehensive utilization of rule set based on the knowledge decision tree classification and the nearest neighbor classi- fication based on the samples, the land use remote sensing information extraction of the study area was conducted, and compared with the super- vised classification and unsupervised classification method for precision evaluation. The results show that compared with the traditional classifica- tion method, the accuracy of object-oriented classification is higher.