地理本体驱动的遥感影像面向对象分析方法  

A Geographic Object-Based Image Analysis Methodology Based on Geo-ontology

作　　者：顾海燕 李海涛[1] 闫利[2] 韩颜顺[1] 余凡[1] 杨懿[1] 刘正军[1] 

机构地区：[1]中国测绘科学研究院摄影测量与遥感所,北京100830 [2]武汉大学测绘学院,湖北武汉430079

出　　处：《武汉大学学报（信息科学版）》2018年第1期31-36,共6页Geomatics and Information Science of Wuhan University

基　　金：国家自然科学基金(41371406);中央级公益性科研院所基本科研业务费专项资金(7771712)~~

摘　　要：针对遥感影像面向对象分析技术存在的＂分类过程中专家分析不同带来的分类结果不一致＂问题,提出地理本体驱动的＂地理实体描述-模型构建-影像对象分类＂解译框架。首先,利用地理本体建立影像对象客观特征与地理专家知识的联系,实现对地理实体的描述与表达;其次,利用知识工程方法以及计算机可操作的形式化本体语言构建影像对象特征、分类器的本体模型,形成语义网络模型;最后,联合语义网络模型与专家规则实现影像对象的语义分类。地表覆盖分类实验结果表明,该方法不仅能够得到反映真实地理对象的遥感影像分类结果,而且能够掌握地理实体的语义信息,实现地表覆盖分类知识的共享与语义网络模型的复用,为遥感影像面向对象分析提供了一种全局性的解译分析框架及其方法。One of the unsolved problems of geographic object-based image analysis（GEOBIA）is＂the classification results may be inconsistent by different expert in the process of image analysis＂.Based on geo-ontology theory,this paper presents a novel framework ＂geo-graphical entity descriptionmodel building-object classification＂to improve the interpretation of GEOBIA results.A geographical entity is expressed formally from the perspective of geo-ontology based on the characteristics of remote sensing image and expert knowledge.The semantic network model is built by using knowledge engineering methods and computer-actionable formal ontology languages.The image objects are classified based on semantic network model and expert rule.In the case of Land-cover classification,results show that,this method can not only obtain the classification results which reflect the geographical objects,but also grasp the semantic information of the geographical entities,and realize the sharing of land-cover classification knowledge and the reusing of the semantic network model.This new approach provides a holistic framework and method for GEOBIA.

关 键 词：遥感影像面向对象分析 地理本体 语义网络模型 网络本体语言 语义网规则语言 地表覆盖分类 

分 类 号：P237[天文地球—摄影测量与遥感]