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Evaluating uncertainty in classification within the land cover map 2000

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thesis
posted on 2014-12-15, 10:38 authored by Paul Robinson
The specific aim of this thesis is to explore the use of object-based metadata regarding data quality within the specific example of attribute uncertainty in the LCM2000. There are three constituent parts to the work. These are using the metadata to identify and describe uncertainty, validating the metadata to ensure that it is informing the user in the way anticipated and exploring what new information can be generated from the metadata. A review of the state of the art in spatial uncertainty is presented as well as introductions to data quality metadata, land cover mapping and the Land Cover Map 2000 itself. Metadata within Land Cover Map 2000 is explored with respect to identifying, describing and visualising attribute uncertainty. It is demonstrated to be extremely useful and relatively simple to use, allowing comparison between different landscape types and between different geographical areas. The metadata is shown to be valid in that they provide a reliable indication of attribute uncertainty. This is achieved by comparing the map with cumulative evidence from other existing databases that give the extent of particular land cover types. The new information generated from the metadata gives further insight into the uncertainty, providing a simple description of heterogeneity within parcels using indices of dominance. As the metadata is object-based it also allows the spatial limits of the map to be broken down and the impact of impurities within the parcel and its neighbour to be examined. This work provides a strong argument for the inclusion of object-based data quality metadata within digital classified map products, allowing users of the data to assess whether or not the data is fit for the purpose to which they intend to put it.

History

Date of award

2006-01-01

Author affiliation

Geography

Awarding institution

University of Leicester

Qualification level

  • Doctoral

Qualification name

  • PhD

Language

en

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