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.
Download ReportTranscript 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.
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 PRESENTED by EMMA A.ODHIAMBO KENYA NATIONAL BUREAU OF STATISTICS Nairobi [email protected] 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. INTRODUCTION CONT’D The information collected includes: Demographic Education Labour Force Housing and Sanitation 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 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 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. 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) 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 1999 CENSUS MAPPING Geographic frame Administrative structure Intercensal changes In Administrative units and number of EAs Number of Administrative Units Administrator 19692 19793 19894 19995 Administrative Units President Kenya Province 1 1 1 8 Provincial Commissioner 8 Districts Locations Sub-Locations Enumeration Areas 8 8 District Commissioner 41 41 69 184 260 497 567 618 1,099 2,427 2410 3,111 3,553 6,612 20,000 25,000 36,979 61,921 41 Divisions 1 District Officer 154 Chief Assistant Chief Table: 1 Changes in the number of Administrative units between the last four Censuses FIELDWORK Training workshops (cartography,DSO & Provincial Administration) Mapping teams Mapping 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 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 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 Numbering of EAS Ground Verification Checking of maps on the ground before the census In the history of census taking in Kenya this was achieved in 1989 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 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) 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 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. 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 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 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 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. 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. 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. 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. 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. 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 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. 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 Legend Part of Nyalenda B Sub-Location Roads Village boundary Enumeration Area boundary Buildings KASIYUYU EA name 315 Structure number Joseph Msoba 318 Israel Church 194 ± 195 196 F. G. Church 305 314 317 308 197 313 Kiosk 304 198 315 307 316 312 303 199 311 310 306 KASIYUYU 604010401047 300 200 251 M. Jobito 309 249 201 George Onyango 248 302 269 301 253 250 252 KASIYUYU 604010401049 202 247 268 270 272 245 267 273 244 207 209 211 218 212 213 219 278 208 221 604010401048 KASIYUYU 275 220 208 256 265 274 216 210 266 299 297 215 204 205 254 277 214 206 246 255 276 Kinyozi 298 203 243 257 264 242 237 223 236 275 294 279 235 228 280 293 296 281 292 232 259 262 285 235 258 231 234 239 289 288 230 260 291 290 229 238 240 0 295 227 0 241 263 226 222 284 282 233 261 283 287 0 0.03 0.06 0.12 Kilometers Part of Nyalenda B Sub-Location 318 Joseph Msoba Legend 194 Israel Church ± Roads 195 Village boundary Enumeration Area boundary Buildings 196 F. G. Church 305 KASIYUYU EA name 604010401049 EA number 314 317 308 197 313 Kiosk 304 198 315 307 316 312 303 199 311 310 200 251 306 309 M. Jobito KASIYUYU 604010401047 249 201 George Onyango 248 302 269 301 253 KASIYUYU 604010401049 202 247 268 270 272 250 252 300 245 267 273 216 211 210 244 218 212 207 209 213 219 266 274 275 278 220 208 256 265 208 221 604010401048 KASIYUYU 297 215 204 205 254 277 299 214 206 246 255 276 Kinyozi 298 203 243 257 264 242 237 223 236 275 294 263 235 228 280 293 296 281 292 232 259 262 285 235 258 239 289 288 231 234 230 260 291 290 229 238 240 0 295 227 0 241 279 226 222 233 261 284 282 283 287 0 0.03 0.06 0.12 Kilometers 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