Disaggregating statistical data at the field level: An entropy approach
This paper provides an alternative approach to disaggregating agricultural data concerning land-use at the detailed pixel level. The proposed approach combines several techniques, such as Hj-Biplot, cluster analysis, dasymetric mapping and cross-entropy, and it is implemented in two steps. First, pr...
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| Other Authors: | , , |
| Format: | article |
| Language: | por |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10174/22123 |
| Country: | Portugal |
| Oai: | oai:dspace.uevora.pt:10174/22123 |
| Summary: | This paper provides an alternative approach to disaggregating agricultural data concerning land-use at the detailed pixel level. The proposed approach combines several techniques, such as Hj-Biplot, cluster analysis, dasymetric mapping and cross-entropy, and it is implemented in two steps. First, prior information is estimated based on the application of a HJ-Biplot and cluster analysis and using a dasymetric mapping methodology. Then, the estimated prior information is used in a cross-entropy model to disaggregate data at the pixel level in a context of incomplete information. This approach is applied to the Algarve region in southern Portugal. The results show a significant correlation between observed and estimated land-uses and are relevant in terms of information gains. |
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