Object-based classification of residential land use within Accra, Ghana based on QuickBird satellite data
Abstract: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.
Document Type: Research Article
Affiliations: Department of Geography, San Diego State University, San Diego, CA 92182-4493
Publication date: January 1, 2007