Characterizing differences between categorical maps as functions of composition and configuration
Subtitle: a hierarchical spectra approach.
Published: 2005
Language: eng
Number of pages: 221
Description: Extending beyond these existing frameworks, a new method is presented, founded in a measurement scheme that decomposes differences in multidimensional coincidence tables along hierarchies of spatial partitioning, categories, and map groupings. These tables reflect three types of variables by counting occurrence frequencies of categories (Z) at levels of spatial aggregation (Y) and on maps (X). Computed conditional entropy sequences characterize the correspondence between X, Y, and Z variables in bits of mutual information and relate to questions regarding the coincidence between colours and locations under the multinomial distribution. These sequences, as continua from coarse to fine detail, are plotted and provide meaningful characterization of the similarities/differences between categorical maps. Implementation is demonstrated between two Canadian land cover products in central British Columbia, clearly indicating regional trends in the agreement characteristics between the two data products.The comparison of categorical maps (nominal data presented on a regular grid) poses numerous challenges, especially within a computer environment implementing an inferential framework. Explored are realizations of spatial stochastic processes whose composition and configuration together characterizes their spatial patterns and several techniques for their comparison to decide whether two maps could have resulted from a common process. Traditional map comparison techniques relying on the coincidence matrix are shown to have potentially serious limitations, but their popularity in the GIS and remote sensing literature justified due consideration in this research. Lacking explicit information regarding configuration, the coincidence matrix summaries of map agreement use incomplete information regarding map pattern and can lead to potentially weak comparisons. Demonstrated is the long anticipated but never unequivocally published potential for multiple maps that deviate from a common map based on a variety of processes to share an identical coincidence matrix with the same original map. This restriction of the coincidence matrix leads to the consideration of landscape pattern indices, which aim to capture specific elements of spatial pattern with very simple summaries. Given that distributions for these measures are unknown as composition and spatial autocorrelation vary, a method for making inference based on computed values is provided but common application remains difficult and suspect.
Notes: Thesis (Ph.D.)--University of Toronto, 2005.

Electronic version licensed for access by U. of T. users.

Source: Dissertation Abstracts International, Volume: 66-06, Section: A, page: 2341.