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| You, Liangzhi; Wood, Stanley; Wood-Sichra, Ulrike. |
| In order to evaluate food security, technology potential and the environmental impacts of production in a strategic and regional context, it is critical to have reliable information on the spatial distribution and coincidence of people, agricultural production, and environmental services. This paper proposes a spatial allocation model for generating highly disaggregated, crop-specific production data by a triangulation of any and all relevant background and partial information. This includes national or sub-national crop production statistics, satellite data on land cover, maps of irrigated areas, biophysical crop suitability assessments, population density, secondary data on irrigation and rainfed production systems, cropping intensity, and crop prices.... |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Global; Cross entropy; Satellite image; Spatial allocation; Agricultural production; Crop suitability; Crop Production/Industries; C6; Q15; Q24. |
| Ano: 2006 |
URL: http://purl.umn.edu/25737 |
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| Lock, Kelly; Hendy, Joanna; Kerr, Suzi. |
| Motu is currently developing a dataset of production costs relating to different rural land uses, which we can use to help explain historical land-use trends at a Territorial Authority level. The Meat and Wool Economic Service farm survey provides a rich database containing physical and financial data for New Zealand sheep and beef farms including detailed information on average farm expenditure, from at least 1980. But while this dataset provides extensive information for 8 farm classes and 5 regions, the actual location of the farms within each class is not known. So, we have developed an algorithm that generates a map of potential farm classes utilising supplementary information on farm location from QVNZ and a land productivity map developed by Baisden... |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Spatial allocation; Production costs; Sheep and beef farming; Production Economics. |
| Ano: 2006 |
URL: http://purl.umn.edu/31952 |
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| You, Liangzhi; Wood, Stanley. |
| While agricultural production statistics are reported on a geopolitical – often national - basis we often need to know the status of production or productivity within specific sub-regions, watersheds, or agro-ecological zones. Such re-aggregations are typically made using expert judgments or simple area-weighting rules. We describe a new, entropy-based approach to making spatially disaggregated assessments of the distribution of crop production. Using this approach tabular crop production statistics are blended judiciously with an array of other secondary data to assess the production of specific crops within individual ‘pixels’ – typically 25 to 100 square kilometers in size. The information utilized includes crop production statistics, farming system... |
| Tipo: Working or Discussion Paper |
Palavras-chave: Entropy; Cross entropy; Remote sensing; Spatial allocation; Production; Crop distribution; Crop Production/Industries. |
| Ano: 2004 |
URL: http://purl.umn.edu/60324 |
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