The multidimensional poverty index (MPI) is generally credited for better capturing the various components of poverty. Where such indexes have a spatial component, opportunity arises for analyzing changes in the spatial concentration of multidimensional poverty over given periods across space. Using current available MPI data for Gauteng province, South Africa, we apply spatial statistical analysis techniques to measure the degree of spatial concentration, spread and orientation of poverty across the various wards. Results reveal distinct variations in concentration, spatial spread and orientation of poverty across the province. These results open up possibilities of spatially targeted state interventions for reducing poverty.

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Abstract:With the increasing use of geographical information and technology in a variety of knowledge domains and disciplines, the need to discover and access suitable geospatial data is imperative. Most spatial data infrastructures (SDI) provide geoportals as entry points to the SDI through which geospatial data are disseminated and shared. Geoportals are often known in geoinformation communities only, and they present technological challenges for indexing by web search engines. To overcome these challenges, we identified and categorized search terms typically employed by users when looking for geospatial resources on the Web. Guided by these terms, we published metadata about geospatial sources "directly" on the Web and performed empirical tests with search engine optimization (SEO) techniques. Two sets of HTML pages were prepared and registered with Google and Bing respectively. The metadata in one set was marked up with Dublin Core, the other with Schema.org. Analysis of the results shows that Google was more effective than Bing in retrieving the pages. Pages marked up with Schema.org were more effectively retrieved than those marked up with Dublin Core. The statistical results were significant in most of the tests performed. This research confirms that pages marked up with Schema.org and Dublin Core are a novel alternative for improving the visibility and facilitating the discovery of geospatial resources on the Web.