CENSUS CARTOGRAPHY: THE KENYAN EXPERIENCE

1. CENSUS CARTOGRAPHY: THE KENYAN EXPERIENCE UN EXPERT GROUP MEETING ON CONTEMPORARY PRACTICES IN CENSUS MAPPING AND USE OF GEOGRAPHIC INFORMATION SYSTEMS UN HEADQUARTERS NEW YORK 29TH MAY TO 1ST JUNE 2007

2. PRESENTED by EMMA A.ODHIAMBO KENYA NATIONAL BUREAU OF STATISTICS Nairobi emma.odhiambo@gmail.com

3. INTRODUCTION • The first census was conducted in 1948, followed by others in 1962, 1979, 1989 and the most recent in 1999. • Kenya has been able to conduct censuses after every ten years. • In the last three censuses Kenya has been able to carry out cartographic census mapping of the whole country.

4. INTRODUCTION CONT’D • The information collected includes: • Demographic • Education • Labour Force • Housing and Sanitation

5. OBJECTIVES OF MAPS IN A CENSUS EA identification Assist in the delineation of the country into units known as Enumeration Area (EA) Assist enumerator to identify and plan how to logically move within the EA Omission and Duplication Maps ensure that errors of omission and duplication are avoided

6. OBJECTIVES CONT’D Budgeting • Budgeting for other census related requirements e.g personnel and materials. Data Dissemination • Maps make it easier to analyze, present and disseminate census results

7. 1969, 1979 and 1989 Censuses • 1969 CENSUS • Mapping activities done by Survey Department, Ministry of Lands and Settlement and Geography department, University of Nairobi. • Topographic maps cuttings used (Scale 1:50,000) • Very little field work done.

8. 1979 CENSUS • Efforts made to improve on the 1969 census • Creation of cartography unit in 1976 • Enumeration Areas were delineated in the office. • Attempt made to use satellite imageries ( not successful)

9. 1989 Census • Mapping drew heavily from 1979 experience and was considered a great success • The officers were trained locally and abroad • New concepts were introduced:- • Villages • Household listing

10. 1999 CENSUS MAPPING • Geographic frame • Administrative structure • Intercensal changes • In Administrative units and number of EAs

11. Number of Administrative Units Administrative Units Administrator 19692 19793 19894 19995 Kenya President 1  1 1   1 Province Provincial Commissioner 8 8 8 8 Districts District Commissioner  41 41 41 69 Divisions District Officer  154 184  260 497 Locations Chief  567 618  1,099 2,427 Sub-Locations Assistant Chief  2410 3,111  3,553 6,612 Enumeration Areas 20,000 25,000  36,979 61,921 Table: 1 Changes in the number of Administrative units between the last four Censuses

12. FIELDWORK • Training workshops (cartography,DSO & Provincial Administration) • Mapping teams • Mapping

13. EA Delineation and EA size • Dense rural settlements(Agricultural areas) • Arid/ Semi Arid areas (Sparse population) • Urban ( High population density) • EA size:- recommended is100 household (500 persons) • Composite EAs

14. Scales • Rural Areas • Dense rural settlments1:10,000, 1:20,000 • Sparsely populated areas 1:50,000, 1:100,000, 1:250,000 • Urban 1:1000,1:2,500 and 1:5,000 • District Maps • 1:100,000, 1:200,000

16. GEOCODING • Coding:- • Admin Unit No Digits Sample code • EA Type • EAs - 4 3010101010011 • Sub location 2 301010101 • Locations 2 3010101 • Divisions 2 30101 • Districts 2 301 • Provinces 1 3 • EA TYPE CODE • Rural 1 Urban 2 Peri Urban 3

17. Numbering of EAS

18. Ground Verification • Checking of maps on the ground before the census • In the history of census taking in Kenya this was achieved in 1989

19. Constraints • Digital Mapping • Late and erratic disbursement of funds which results to shortage of time for mapping • Problem of urban slum mapping • Use of sketch maps especially in urban areas • Shortage of skilled manpower • Lack of up to date topographic maps

20. RECOMMENDATIONS • Early training of personnel in GIS/CAC • Timely disbursement of funds • Acquisition and use of satellite imageries for urban areas (Quick Bird) • Use of Geographic Positioning System (GPS)

21. GEOGRAPHIC INFORMATION SYSTEM (GIS) • The 2009 census will be the second to be undertaken using computer assisted cartography (CAC.) • The UNFPA provided support for the establishment of a GIS facility which was commissioned in 1998 and envisaged to culminate into a fully fledged Kenya Census Geographic Information System

22. GIS Cont’d • However the implementation of the project experienced a number of setbacks that led to a slow pace in the process of preparing the enumeration area maps. • As a result of the slackened pace, maps for 26 districts were prepared using the GIS whereas the rest of the districts (43) were prepared using the conventional cartography.

24. CONSTRAINTS • Late acquisition and installation of the GIS facility. • Lack of adequate skilled staff in Computer assisted cartography • Inadequate software user licences • Poor maintenance of the GIS facility

25. CONSTRAINTS Cont’d • Servicing of equipment was not adequate • Upgrading of software was tied to maintenance service contract • The cost of maintenance service contract was and still is very high. If not on this contract you can not get any upgrade on the new software release

26. USE OF SATELLITE IMAGES IN MAPPING FOR THE 2009 KENYA POPULATION AND HOUSING CENSUS. • One of the biggest challenges facing census mapping in the heavily settled and un planned areas in Kenya is lack of suitable base maps in terms of scale and currency. • The heavily settled areas which are mainly in urban areas are associated with slums where the settlements patterns are very dynamic with rapid changes taking place

27. USE OF SATELLITE IMAGES/AERIAL PHOTOGRAPHS IN CENSUS MAPPING Cont’d • Current and very large scale maps are therefore compulsory to enable proper mapping and the creation of suitable Enumeration Areas. • Unfortunately, those responsible are not able to provide such maps when required.

28. USE OF SATELLITE IMAGES IN CENSUS MAPPING Cont’d • Such challenges are quite serious in countries such as Kenya where about 60% of the urban populations live in these heavily settled areas (Slums). • There is hardily any town in Kenya which does not have slum settlements and this underlines the seriousness of the problem.

29. USE OF SATELLITE IMAGES IN CENSUS MAPPING Cont’d • The above mentioned challenges are quite serious in Kenya where a high percentage of the population lives in the slum areas.

30. USE OF SATELLITE IMAGES/AERIAL PHOTOGRAPHS IN CENSUS MAPPING Cont’d • Such challenges are quite serious in countries such as Kenya where about 60% of the urban populations live in these heavily settled areas (Slums). • There is hardily any town in Kenya which does not have slum settlements and this underlines the seriousness of the problem.

31. USE OF SATELLITE IMAGES/AERIAL PHOTOGRAPHS IN CENSUS MAPPING Cont’d • In the censuses of 1989 and 1999, an attempt was made to solve this problem by relying on the preparation of sketches. • But after the censuses, the sketches could not be relied on during the design of NASSEP programs and in the conversion of the EA maps into digital formats especially after the 1999 census.

32. USE OF SATELLITE IMAGES/AERIAL PHOTOGRAPHS IN CENSUS MAPPING Cont’d • During the cartographic mapping for the 2009 Census, satellite images and aerial photographs are being used so as to address this problem. • These products were used in Kisumu during the pilot mapping and they have also been used during the phase one mapping covering a lager part of Nyanza province and which was concluded recently

33. USE OF SATELLITE IMAGES/AERIAL PHOTOGRAPHS IN CENSUS MAPPING Cont’d • The products have proved to be very useful. They have enabled the preparation of excellent maps of the covered towns • Indeed they offer a complete solution to the problem sited above because the products are very current and therefore enabling the mapping of every part of any urban area and at any desired map scale.

34. USE OF SATELLITE IMAGES IN CENSUS MAPPING Cont’d • The maps produced are of very high quality and accurate and therefore they will ensure a complete and accurate coverage of the census. • Further, because of their high quality and accuracy, they will enable a better sampling frame to be put in place since the urban population can be demarcated precisely from the rural population. This was not possible in the last census as it later led into a gross under quotation of the urban population

37. CONSTRAINTS • The cost of the images and shape files is too high • The satellite images are usually not current hence not giving the true picture on the ground • The time taken to access the images and to create shape file from them is also too long