基于高分遥感的一种新的面向对象城市建筑物信息提取的方法研究

摘要:目的]为了提高城市建筑物信息提取精度，本文在前人研究的基础上，针对下垫面结构复杂的城市区，提出了多尺度分割和规则数据库结合的面向对象方法，对城市区建筑物信息进行提取。方法]该方法首先采用Full Lambda-Schedule算法对QuickBird多波段和全波段数据融合数据进行尺度分割，获取尺度分割结果；再根据光谱特征、形状特征、几何特征和纹理特征等指标建立规则知识库，利用规则数据库对尺度分割结果进行建筑物信息的提取。以广州市白云区为研究区，利用尺度分割和规则数据库结合的方法提取建筑物信息，提取结果与其它分类结果进行了比较。结果和结论]结果表明:基于规则的面向对象的分类方法可以有效地避免传统的基于像素分类时出现的椒盐现象，避免一些错分、漏分的情况分类（如:道路和阴影），结果更加符合人类的思维方式，与实际值更接近，总体分类精度达到87.0154%，Kappa系数为0.8714，比一般面向对象分类方法更适合作为城市建筑物专题数据库更新的有效方法。

A new object-oriented method research of city building information extraction based on the high-resolution remote sensing

Abstract :Objective]To increase the accuracy of urban building extraction from high-resolution satellite image, this paper proposed anew object-oriented extraction method based on the traditional building extraction approaches, which combined multiple scale segmentation and rules database according to complex urban surface. Method]The method firstly conducted scale segment using Full Lambda-Schedule algorithm for QuickBird multi-band and full-band merged data. Then, the knowledge rules was established according to the spectral characteristics, shape features, geometric features and texture features and other indicators, which was used for extracting building information from the scale segment result. This article put Baiyun District of Guangzhou City as the study area, and extracted building information utilizing a combination of scale segmentation and rules database.Result and conclusion]The studied results showed that the new object-oriented classification method based on rules can effectively avoid the appearance of phenomenon of salt and pepper in a traditional classification based on pixel, and decrease misclassification (such as roads and shadow), which are more consistent with human way of thinking and closer to the actual value. And, comparing to the traditional pixel-based classification and object-oriented classification, the new classified method produced the highest accuracy with overall accuracy of 87.0154%% and a Kappa of 0.8714, which tested that this new classified method for updating city building thematic database would be more suitable than the general object-oriented classification.