Application of knowledge for automated land cover change monitoring

Abstract

This paper outlines an approach for updating baseline land cover datasets. Knowledge about land cover, as used during manual mapping, is combined with simple remote sensing analyses to determine land cover change direction. The philosophy is to treat reflectance data as one source of information about land cover features. Applying expert knowledge with reflectance and biogeographical data allows generic solutions to the problem. The approach is demonstrated in areas of semi-natural vegetation and shown to differentiate ecologically subtle but spectrally similar land cover classes. Further, the advantages of manual mapping techniques and of high resolution remotely sensed imagery are combined. This approach is suitable for incorporation into automated approaches: it makes no assumption about the distribution of land cover features, can be applied to different remotely sensed data and is not classification specific. It has been incorporated into SYMOLAC, an expert system for monitoring land cover change.