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
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
收藏
页码:5167 / 5173
页数:7
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