Integrating land-cover data with different ontologies: identifying change from inconsistency

Alexis Comber,Peter Fisher,Richard Wadsworth

doi:10.1080/13658810410001705316

Abstract

Spatially coincident land-cover information frequently varies due to technological and political variations. This is especially problematic for time-series analyses. We present an approach using expert expressions of how the semantics of different datasets relate to integrating temporal time series land-cover information where the classification classes have fundamentally changed. We use land-cover mapping in the UK (LCMGB and LCM2000) as example data sets because of the extensive object-based meta-data in the LCM2000. Inconsistencies between the two datasets can arise from random, gross and systematic error and from an actual change in land cover. Locales of possible land-cover change are inferred by comparing characterizations derived from the semantic relations and meta-data. Field visits showed errors of omission to be 21% and errors of commission to be 28%, despite the accuracy limitations of the land-cover information when compared with the field survey component of the Countryside Survey 2000.

Highlights

The process of natural resource inventory takes place against a background of change which may result in inconsistency
The results of field visits undertaken between December 2002 and March 2003, which are described in section 2.3, assessed whether the 1990 and 2000 classes could have been correct, and whether there had been any land cover change in the period
6.2 Abstracting from Field Data – identifying change The thresholds were applied to the Land Cover Map 2000 (LCM2000) data to identify possible change parcels

Summary

Introduction

The process of natural resource inventory takes place against a background of change which may result in inconsistency. Changes in methodology make it difficult to separate changes in the phenomenon being measured (such as land cover) from changes that are the result of the revised methodology; that is to say ontological inconsistency may be a problem for change detection This discord causes problems for research that seeks to develop time-series of land cover or land use to monitor environmental change and for initiatives that aim to react to environmental change. One of the LCM2000 attributes (‘PerPixList’) provides a description of the parcel spectral heterogeneity, listing the top 5 spectral subclasses within the parcel This metadata was the result of a production stream that was completely separate to and independent of the process by which the parcel was identified and classified. Accompanying the release of the standard Level 3 LCM2000 product was information about the expected overlap of the spectral subclasses of PerPixList with the Broad Habitat classification

Methods

Results

Discussion

Conclusion