Generating plausible crop distribution maps for Sub-Saharan Africa using a spatial allocation model
Agricultural production statistics are fundamental parameters for agriculture policy research. Information on acreage and yields of important crops is critical for understanding trends within what is the most important economic sector of many developing countries. Sub-national data — i.e. data organ...
| Autores principales: | , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
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SAGE Publications
2007
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| Acceso en línea: | https://hdl.handle.net/10568/171849 |
| _version_ | 1855523723888558080 |
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| author | You, Liangzhi Wood, Stanley Wood-Sichra, Ulrike Chamberlin, Jordan |
| author_browse | Chamberlin, Jordan Wood, Stanley Wood-Sichra, Ulrike You, Liangzhi |
| author_facet | You, Liangzhi Wood, Stanley Wood-Sichra, Ulrike Chamberlin, Jordan |
| author_sort | You, Liangzhi |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Agricultural production statistics are fundamental parameters for agriculture policy research. Information on acreage and yields of important crops is critical for understanding trends within what is the most important economic sector of many developing countries. Sub-national data — i.e. data organized by administrative units such as regions or districts — enable the analysis of patterns within countries that may highlight important policy issues, such as the need to allocate resources to underproductive areas. However, collecting sub-national data is difficult for developing countries with limited resources. Even with great effort, and often only on broad regional scales, enormous data gaps exist and are unlikely to be filled. As a result, information is often only available at national or very broad sub-national levels (such as provinces). Such geographically coarse data are unable to reflect important variations within countries and are insufficient for the spatial analysis of production patterns and trends. To fill these spatial data gaps we developed a model to disaggregate production data from coarser to finer spatial units. Using a cross-entropy approach, our spatial allocation model attempts to make plausible allocations of crop production from large reporting units such as a country or state, into smaller spatial units organized as cells of a regularly-spaced grid. In addition to more detailed information, the organization of production information in geographic grids allows for greater analytical possibilities through geographic information systems. The allocation model works on the basis of available evidence of mapped indicators of agricultural production, which include farming systems, land cover, crop biophysical suitability surfaces, commodity prices and local market access. This article describes the generation of crop distribution maps for Sub-Saharan Africa for the year 2000 using the spatial allocation model and discusses the importance of such maps for development analysis and planning. |
| format | Journal Article |
| id | CGSpace171849 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2007 |
| publishDateRange | 2007 |
| publishDateSort | 2007 |
| publisher | SAGE Publications |
| publisherStr | SAGE Publications |
| record_format | dspace |
| spelling | CGSpace1718492025-02-24T06:47:51Z Generating plausible crop distribution maps for Sub-Saharan Africa using a spatial allocation model You, Liangzhi Wood, Stanley Wood-Sichra, Ulrike Chamberlin, Jordan agricultural production geographical information systems Agricultural production statistics are fundamental parameters for agriculture policy research. Information on acreage and yields of important crops is critical for understanding trends within what is the most important economic sector of many developing countries. Sub-national data — i.e. data organized by administrative units such as regions or districts — enable the analysis of patterns within countries that may highlight important policy issues, such as the need to allocate resources to underproductive areas. However, collecting sub-national data is difficult for developing countries with limited resources. Even with great effort, and often only on broad regional scales, enormous data gaps exist and are unlikely to be filled. As a result, information is often only available at national or very broad sub-national levels (such as provinces). Such geographically coarse data are unable to reflect important variations within countries and are insufficient for the spatial analysis of production patterns and trends. To fill these spatial data gaps we developed a model to disaggregate production data from coarser to finer spatial units. Using a cross-entropy approach, our spatial allocation model attempts to make plausible allocations of crop production from large reporting units such as a country or state, into smaller spatial units organized as cells of a regularly-spaced grid. In addition to more detailed information, the organization of production information in geographic grids allows for greater analytical possibilities through geographic information systems. The allocation model works on the basis of available evidence of mapped indicators of agricultural production, which include farming systems, land cover, crop biophysical suitability surfaces, commodity prices and local market access. This article describes the generation of crop distribution maps for Sub-Saharan Africa for the year 2000 using the spatial allocation model and discusses the importance of such maps for development analysis and planning. 2007-05 2025-01-29T12:58:51Z 2025-01-29T12:58:51Z Journal Article https://hdl.handle.net/10568/171849 en Limited Access SAGE Publications You, Liangzhi; Wood, Stanley; Wood-Sichra, Ulrike; Chamberlin, Jordan. 2007. Generating plausible crop distribution maps for Sub-Saharan Africa using a spatial allocation model. Information Development 23(2-3): 151-159. https://doi.org/10.1177/0266666907078670 |
| spellingShingle | agricultural production geographical information systems You, Liangzhi Wood, Stanley Wood-Sichra, Ulrike Chamberlin, Jordan Generating plausible crop distribution maps for Sub-Saharan Africa using a spatial allocation model |
| title | Generating plausible crop distribution maps for Sub-Saharan Africa using a spatial allocation model |
| title_full | Generating plausible crop distribution maps for Sub-Saharan Africa using a spatial allocation model |
| title_fullStr | Generating plausible crop distribution maps for Sub-Saharan Africa using a spatial allocation model |
| title_full_unstemmed | Generating plausible crop distribution maps for Sub-Saharan Africa using a spatial allocation model |
| title_short | Generating plausible crop distribution maps for Sub-Saharan Africa using a spatial allocation model |
| title_sort | generating plausible crop distribution maps for sub saharan africa using a spatial allocation model |
| topic | agricultural production geographical information systems |
| url | https://hdl.handle.net/10568/171849 |
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