Urban land-cover classification: An object based perspective

被引：7

作者：

Darwish, A ^{[1
]}

Leukert, K ^{[1
]}

Reinhardt, W ^{[1
]}

机构：

[1] Univ Bundeswehr Munich, GIS Lab, AGIS, D-85577 Neubiberg, Germany

来源：

2ND GRSS/ISPRS JOINT WORKSHOP ON REMOTE SENSING AND DATA FUSION OVER URBAN AREAS | 2003年

关键词：

image analysis; object oriented methods; geographic information systems;

D O I：

10.1109/DFUA.2003.1220004

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Up to date and accurate urban land cover information is needed in a variety of applications, e.g. urban planning and management. However, depending on traditional surveying tools, especially in large metropolitan cities, to produce such data is a time consuming and expensive task. This has initiated the need to classify remotely sensed data to extract urban land cover information. A new classification approach (object based) has been recently proposed and is currently being investigated. In this research the classification accuracy of object-based classification is tested against statistical classifiers using two images (Landsat and IRS). Results have shown that object based classification yields better classification results.

引用

页码：278 / 282

页数：5