Wspólnotowy Serwis Informacyjny Badan i Rozwoju - CORDIS

Semantical / statistical approach of the land-cover change

Identifying inconsistency between ontologically discordant data by combining semantics and metadata

The issue of dataset inconsistency is endemic to resource inventory because:
- different surveys at the same instance in time may record nominally similar features (such as land cover), but may do so in completely different ways due to their particular institutional or national perspectives;
- different surveys at different points in time would not be expected to record objects of interest (such as areas of land cover) in the same way because of scientific developments and new policy objectives (Comber et al., 2002; 2003a).

The effect of changing methodologies is that much of the value of the previous land resource inventories is lost with each successive survey; each inventory becomes the new baseline against which future changes are theoretically to be measured, but in reality never are. Ideally each successive methodological evolution would be accommodated in a multi-layered derived dataset, presenting the previous and the new approaches alongside each other.

We have developed an approach for integrating ontologically discordant spatial data that combines expert descriptions of how the semantics of different land cover datasets relate with object level spectral meta-data. This approach is applied to two satellite derived land cover surveys of the UK in order to identify inconsistency between the datasets, a subset of which is locales of actual land cover change.

Data description
In Britain, the only national land cover datasets are the LCM2000 and its predecessor the LCM1990. Yet because of the problems of semantic and methodological difference, the 2000 dataset is accompanied with a "health warning" against comparing it to its predecessor (Fuller et al., 2002). In the research reported here we are interested in identifying those locations where the land covers are inconsistent between the two dates of classification, 1990 and 2000 as a first step in identifying change.

Initial Work
Therefore we define inconsistency in this context as whether the information for a particular land-cover object (in this case a LCM2000 parcel) is inconsistent with the cover types within that parcel in 1990 when viewed through the lens of the Spectral and Semantic LUTs. If the semantic definition of the land cover types at a location in the 1990 map are inconsistent with those present in 2000, we can identify two possible causes of the change. Either the cover type at one time or the other is in error, or else the cover type on the ground has changed.

Previous analyses used a Euclidian distance calculated between 2 characterisations of the parcel based on the Spectral and Semantic LUTs. Parcels with the greatest distance (by proportion of the parcel area and in absolute terms) were identified. The pattern of vector directions was found to be related to the level of ontological change. This methodology is reported in full in Comber et al. (2003b, 2003c). Field visits showed that 26% of the parcels identified as inconsistent were believed to have actually changed since 1990. We also identified situations with meta-data inconsistencies (e.g. empty attribution fields) and small parcels that bore no relation to landscape objects on the ground. Filters were developed to eliminate such artefacts from analysis (Comber et al., 2003d). A second tranche of analyses considered the filtered data and identified a second set of inconsistent parcels based on absolute vector distance (not proportion). Again a sample of these was visited in the field. The results showed 41% of these parcels were believed to have actually changed since 1990. The remainder (59%) were due to inconsistencies (errors of classification) in either the 1990 or the 2000 dataset. This work is reported in Comber et al. (submitted).

Future Work
The information provided by a single expert to describe relations between land-cover class concepts under a scenario of idealised semantics has been used. There are LUTs from two other experts, both familiar with LCM19990 and LCM2000, and LUTs for all three under two other scenarios "change" (the expected transitions between land cover classes) and "technical" (how different land cover class concepts relate based on heuristic knowledge of where spectral confusion may occur). Evidence from these might be supportive or contradictory, which in turn might allow stronger or weaker inferences about change to be made. Future Work will be directed in a number of areas. Firstly, the use of different expressions of expert opinion. Secondly, these multiple statements of Expectedness and Unexpectedness from different experts, under different scenarios would be suitable for combination using uncertainty formalisms such as Dempster-Shafer or Rough Sets. Thirdly we hope to develop a "Cook Book" for users of LCM2000.

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