Object-based classification of residential land use within Accra, Ghana based on QuickBird satellite data

被引：78

作者：

Stow, D. ^{[1
]}

Lopez, A. ^{[1
]}

Lippitt, C. ^{[1
]}

Hinton, S. ^{[1
]}

Weeks, J. ^{[1
]}

机构：

[1] San Diego State Univ, Dept Geog, San Diego, CA 92182 USA

来源：

INTERNATIONAL JOURNAL OF REMOTE SENSING | 2007年 / 28卷 / 22期

关键词：

Image segmentation - Land use - Object recognition - Satellite imagery - Spectrum analysis;

D O I：

10.1080/01431160701604703

中图分类号：

TP7 [遥感技术];

学科分类号：

081102 ; 0816 ; 081602 ; 083002 ; 1404 ;

摘要：

A segmentation and hierarchical classification approach applied to QuickBird multispectral satellite data was implemented, with the goal of delineating residential land use polygons and identifying low and high socio-economic status of neighbourhoods within Accra,Ghana. Two types of object-based classification strategies were tested, one based on spatial frequency characteristics of multispectral data, and the other based on proportions of Vegetation Impervious-Soil sub-objects. Both approaches yielded residential land-use maps with similar overall percentage accuracy (75%) and kappa index of agreement (0.62) values, based on test objects from visual interpretation of QuickBird panchromatic imagery.

引用

页码：5167 / 5173

页数：7

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