基于优化分割分类层次体系的土地覆被分类制图方法探讨

随着高分辨率卫星的广泛应用,基于对象的影像分析方法逐渐成为提取土地覆被信息的主要方法。分割优化是基于对象的影像分析方法中的一个基本步骤。不同土地覆被类型通常具有不同的优化分割参数,如何充分利用多尺度最优分割建立分割分类层次体系,从高分辨率影像中提取各种土地覆被类型,实现高精度土地覆被制图,是面向对象影像分析方法中有待解决的一个难题。在获取不同土地覆被类别各自最优的分割参数基础上,探索了一种基于参考数据集的最小分割单元与决策树的分割分类层次体系构建方法。实验表明:该方法可以有效地降低设置分割分类层次体系时对操作者个人经验的依赖,提高分类精度,满足自动制图要求。

Land Cover Classification and Mapping based on Segmentation Optimized Hierarchical Object Classification System

With the wide application of high-resolution satellite,Object based Image Analysis(OBIA) has gradually become main stream of extracting land cover information.Segmentation optimization is a fundamental step in OBIA.Different land cover types usually have different optimized segmentation parameters.How to make full use of the optimal Multi-Resolution Segmentation(MRS) to establish a segmentation classification hierarchy and to achieve high-precision land cover mapping,is a challenge in object-oriented image analysis.based on the optimal segmentation parameters of different land cover types,this paper explores a method to construct a segmentation optimized hierarchical classification system based on the minimum optimized segmentation unit.Experiments show that this method can effectively reduce the dependence on the operator’s personal experience when setting up the classification hierarchy system,improve the classification accuracy,and meet the requirements of automatic drawing.