An evaluation of per-parcel land cover mapping using maximum likelihood class probabilities

Dean, A.M.; Smith, G.M.. 2003 An evaluation of per-parcel land cover mapping using maximum likelihood class probabilities. International Journal of Remote Sensing, 24 (14). 2905-2920. 10.1080/01431160210155910

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Abstract/Summary

The Centre for Ecology and Hydrology (CEH) has recently developed a per-parcel classification procedure which integrates remotely sensed imagery with digital cartography. The aim of the work reported here was to compare the per-parcel approach with a conventional per-pixel classification through examination of maximum likelihood class probabilities. An Airborne Thematic Mapper (ATM) image with 1.25 m spatial resolution was used as a source of training data. The ATM image was spatially degraded to 10 m resolution to form the remotely sensed input and the study area was subdivided into land parcels by manual digitizing. The per-parcel approach extracted raster data from a core area described by a shrunken version of a land parcel, thus eliminating mixed boundary pixels. Boundary pixels were shown to be more variable than the core pixels and their removal improved classification confidence. The per-parcel approach calculated the mean spectral response of the extracted core pixels. This was shown to remove within-parcel variation and improve classification confidence in comparison to per-pixel class allocations. A parcel-based representation was shown to be most appropriate for mapping agricultural land cover in comparison to semi-natural areas, because agricultural landscapes have an inherent parcel structure. When land cover is heterogeneous, as in many semi-natural areas, a per-pixel classification would appear to be more appropriate. A hybrid classifier, which could switch between per-parcel and per-pixel mapping, was suggested as a powerful land cover mapping tool.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1080/01431160210155910
Programmes:	CEH Programmes pre-2009 publications > Biodiversity > SE01A Sustainable Monitoring and Management of Land Resources > SE01.1 An Improved Land Cover Map (LCM)
UKCEH and CEH Sections/Science Areas:	_ Earth Observation
ISSN:	0143-1161
Additional Keywords:	Land Cover Map, LCM2000
NORA Subject Terms:	Ecology and Environment Data and Information
Date made live:	28 Jul 2014 09:22 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/507925

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