Disaggregating statistical data at the field level: An entropy approach

Abstract

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.