Part 1

1. Insight into the application and use of Geotechnology for National Statistics Organizations in Africa Part 1 Produced in Collaboration between World Bank Institute and the Development Data Group (DECDG)

2. Spatial statistics in Africa The usefulness of spatial and statistical data when not being linked to each other is severely limited • Census data and statistics linked to small geographic areas forms the backbone of many development initiatives The creation of a geo-statistical database which drives development planning, implementation and monitoring is imperative. • The information collected by NSOs is important for: • Land information management • Poverty reduction and economic empowerment • The development of basic transport and tele-communications infrastructure • The provision of electricity, water and sanitation • The effective and accurate provision of primary health care to especially rural communities • Fighting the HIV/Aids pandemic, malaria and tuberculoses (TB) • Implementing sustainable agricultural methods in order to curb food insecurity • Granting disadvantaged individuals access to land, markets, welfare and social services • Maintenance of democracy through better planned and more transparent elections

3. Challenges faced by NSOs regarding Geotechnology The increased demand for developmental statistics has exposed current data collection, integration, analysis and dissemination techniques Geotechnology in Africa still a novel concept – full potential still not reached • Typical challenges faced by African NSOs regarding Geotechnology: • Inadequate awareness within the organization as a whole regarding the potential and use of Geotechnology • Lack of institutional support regarding the on going maintenance and sustainability of Geotechnology • Inadequately integrated and properly designed data warehouse and databases • Inadequate spatial base, primary and secondary data • Available data lacking in accuracy and currency • Inadequate equipment • Lack of skilled staff • Lack of capacity building • Inadequate funding and operational assistance

4. How GIS can answer these challenges • Increase in the accuracy of spatial base data leads to increased accuracy in data collection, analysis and statistics results • Which will lead to an increased demand for and profile of statistics in the user community Added analysis and dissemination possibilities enhances decision-making Institutional capacity are increased Master sampling frames and updated survey methodology are created and implemented increasing the accuracy of data collection and analysis Time savings on planning, sample drawing, fieldwork activities, logistics management are realised More cost effective field data collection needing fewer resources Improved IT infrastructure and knowledge base

5. The use of GIS for NSOs The use and impact of GIS on NSOs is aptly described by the graphic below. Source: Statistics South Africa, 2007

6. The use of GIS for Census and Survey Operations Using Remote Sensing (RS) and Digital Aerial Photography (DAP) for census mapping purposes: Nationwide coverage (Lesotho) From sketch mapping………… to imagery based mapping NSOs are always asking the “Where” question – with imagery that becomes very easy to answer

7. The use of GIS for Census and Survey Operations Integration of imagery, GPS captured data into GIS leads to accurate imagery based map creation. Examples of A3 size EA field maps Lesotho 2006 These maps act as a base for all field data collection and verification activities for both census and survey operations

8. The use of GIS for Census and Survey Operations Examples of A3 size EA field maps Namibia 2001

9. The use of GIS for Census and Survey Operations Examples of A3 size EA field maps Tanzania 2002

10. The use of GIS for Small Area Statistics creation Small area statistics creation through spatial analysis – can form a base layer for all developmental and intervention planning and implementation Census data in South Africa aggregated and linked to newly created place name polygons

11. The use of GIS for Dwelling Frame creation Dwelling frame creation – moving from EA level to dwelling level. Adapted from Statistics South Africa, 2007 Having accurate base spatial and attribute information for every dwelling

12. The use of GIS for Dwelling Frame creation A spatial point for every dwelling in the country Note the spatial points captured next to each stand Adapted from Statistics South Africa, 2007

13. The use of GIS for Dwelling Frame creation Attribute information linked to every spatial dwelling point City / Town / Traditional Authority: Mutale Village name / Sub place: Masisi Unique ID: 90600196_00077 Geo-referenced Coordinates Head of Household: Manoli, Amosi Feature use: Du (Dwelling Unit) Adapted from Statistics South Africa, 2007 Dwelling type: Dwelling or Brick structure on a stand or yard or on a farm

14. The use of GIS for Analysis and Dissemination Often, the potential use of GIS for spatial data analysis, census product creation and dissemination is ignored or implemented incorrectly • Reasons: • Lack of sustained funding • Lack of skills • Lack of sustained training • Lack of institutional support • Lack of data sharing among NSO departments GIS should stand central in all analysis and dissemination of data with a spatial component Internet based data dissemination the way of the future – users will demand it Web GIS allows users to interact with the data – view, query, create maps and tables – while also keeping data secure and access regulated

15. The use of GIS for Analysis and Dissemination Example of education statistics disseminated and accessed via a web based GIS School specific data aggregated to district level

16. The use of GIS for Master Sample implementation • The use of Master Samples for survey implementation is beneficial because: • Time is saved since a new sample need not be drawn for every survey • Fieldworkers become familiar with the EAs selected for the master sample which makes fieldwork more accurate • Changes in the selected EAs can be consistently updated • The master sample frame provides a constant spatial reference for the data collected across various surveys Master Sample of 1000 EAs created for the Human Sciences Research Council (HSRC) in South Africa. This Master Sample has a five year life span

17. The use of GIS for Master Sample implementation • Using GIS and imagery integration for Master Sample creation provides the following advantages: Individual dwelling units (DUs) can be identified and sampled on screen in the office – minimises fieldwork for DU identification and listing . Sampling is more accurate than traditional methods – fieldworker bias removed Cost savings due to increased speed and effectiveness of fieldwork Quality control is improved due to the use of imagery and image based field maps EA boundary in blue 11 Dwelling Units have been selected in the office for this survey

18. The use of GIS for Master Sample implementation Data collection errors due to fieldworker error is minimised Same imagery base used for subsequent surveys – new cluster samples created for each survey – minimises respondent contamination and fatigue Use of GPS and DU coordinates allows for accurate navigation Updating of settlement and infrastructure changes now possible Sample EA survey map – sourced from the Human Sciences Research Council EA Boundary Selected dwelling units

19. The use of GIS for Poverty Mapping • The quest to eliminate poverty one of the great human endeavours of our time • Spatial information is key – lack of income, material goods and opportunity takes place in and is influenced by your spatial environment • Poverty maps can be used by international, national, and local decision-makers to direct investments in human development: • Pinpoints places where development lags • Highlights the location and condition of infrastructure and natural resource assets that are critical to poverty reduction Policymakers can deploy highly targeted antipoverty expenditures and interventions For statistical agencies, poverty mapping is an essential, long-term capacity development and institutional strengthening exercise

20. What are poverty maps? • Definition • The spatial representation and analysis of indicators of human wellbeing and poverty • Poverty maps are spatial representations of poverty assessments. Poverty maps used when planning public investment, identify areas in need of development or intervention programmes • Assessment information comes from many sources and can be presented at various levels. Typical indicators are: • GDP per capita • Daily subsistence levels • Life expectancy • Child mortality • Literacy…….from census and household survey data Indexes of poverty and human development – combine various indicators

21. The need for GIS when mapping poverty GIS references features in space as well as the attributes of those features. Poverty indicators are similarly linked and referenced to features/areas/elements in space and analysed within the spatial context

22. Examples of poverty mapping Mapping poverty over time

23. Examples of poverty mapping Mapping poverty and infrastructure Fewer roads means less access to markets, employment, etc. Note the correlation between higher poverty and the lack of road infrastructure

24. Examples of poverty mapping Mapping poverty and health