Reviving legacy population maps with object-oriented image processing techniques
Vast archives of legacy maps exist for most parts of the world, containing analog information on a variety of environmental and socioeconomic parameters, and often dating back to the nineteenth century. The information contained in those data, which is potentially of great utility in environmental c...
| Autores principales: | , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Institute of Electrical and Electronics Engineers
2009
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| Acceso en línea: | https://hdl.handle.net/10568/944 |
| _version_ | 1855528232337539072 |
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| author | Kerle, N. Leeuw, Jan de |
| author_browse | Kerle, N. Leeuw, Jan de |
| author_facet | Kerle, N. Leeuw, Jan de |
| author_sort | Kerle, N. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Vast archives of legacy maps exist for most parts of the world, containing analog information on a variety of environmental and socioeconomic parameters, and often dating back to the nineteenth century. The information contained in those data, which is potentially of great utility in environmental change or demographic studies, has traditionally only been accessible through digitizing or visual map analysis. In this paper, we show how object-oriented analysis can be used to unlock such information. We demonstrate this on a 1962 map of Kenya, which shows population distribution using differently sized dots. The procedure developed extracts those population signatures accurately, despite size and color variations, dot bleeding, and conglutination, as well as overlap with other map elements. Over 39 000 dots were automatically extracted, corresponding to 99.6% of the published population figure, with an accuracy between 94.6% and 98.5% for the different symbol sizes. We also discuss the utility of the derived geographic-information-system-ready information, for example, to assess malaria exposure and calculate population change figures, using the 1999 census data at a detailed sublocation level. |
| format | Journal Article |
| id | CGSpace944 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2009 |
| publishDateRange | 2009 |
| publishDateSort | 2009 |
| publisher | Institute of Electrical and Electronics Engineers |
| publisherStr | Institute of Electrical and Electronics Engineers |
| record_format | dspace |
| spelling | CGSpace9442024-04-25T06:01:05Z Reviving legacy population maps with object-oriented image processing techniques Kerle, N. Leeuw, Jan de Vast archives of legacy maps exist for most parts of the world, containing analog information on a variety of environmental and socioeconomic parameters, and often dating back to the nineteenth century. The information contained in those data, which is potentially of great utility in environmental change or demographic studies, has traditionally only been accessible through digitizing or visual map analysis. In this paper, we show how object-oriented analysis can be used to unlock such information. We demonstrate this on a 1962 map of Kenya, which shows population distribution using differently sized dots. The procedure developed extracts those population signatures accurately, despite size and color variations, dot bleeding, and conglutination, as well as overlap with other map elements. Over 39 000 dots were automatically extracted, corresponding to 99.6% of the published population figure, with an accuracy between 94.6% and 98.5% for the different symbol sizes. We also discuss the utility of the derived geographic-information-system-ready information, for example, to assess malaria exposure and calculate population change figures, using the 1999 census data at a detailed sublocation level. 2009-07 2010-03-28T10:17:42Z 2010-03-28T10:17:42Z Journal Article https://hdl.handle.net/10568/944 en Limited Access Institute of Electrical and Electronics Engineers Kerle, N.; Leeuw, J. de. 2009. Reviving legacy population maps with object-oriented image processing techniques. IEEE transactions on Geoscience and Remote Sensing. 47(7):2392-2402. |
| spellingShingle | Kerle, N. Leeuw, Jan de Reviving legacy population maps with object-oriented image processing techniques |
| title | Reviving legacy population maps with object-oriented image processing techniques |
| title_full | Reviving legacy population maps with object-oriented image processing techniques |
| title_fullStr | Reviving legacy population maps with object-oriented image processing techniques |
| title_full_unstemmed | Reviving legacy population maps with object-oriented image processing techniques |
| title_short | Reviving legacy population maps with object-oriented image processing techniques |
| title_sort | reviving legacy population maps with object oriented image processing techniques |
| url | https://hdl.handle.net/10568/944 |
| work_keys_str_mv | AT kerlen revivinglegacypopulationmapswithobjectorientedimageprocessingtechniques AT leeuwjande revivinglegacypopulationmapswithobjectorientedimageprocessingtechniques |