THE ITE LAND CLASSIFICATION - PROVIDING AN ENVIRONMENTAL STRATIFICATION OF GREAT-BRITAIN

Citation
Rgh. Bunce et al., THE ITE LAND CLASSIFICATION - PROVIDING AN ENVIRONMENTAL STRATIFICATION OF GREAT-BRITAIN, Environmental monitoring and assessment, 39(1-3), 1996, pp. 39-46
Citations number
16
Categorie Soggetti
Environmental Sciences
ISSN journal
01676369
Volume
39
Issue
1-3
Year of publication
1996
Pages
39 - 46
Database
ISI
SICI code
0167-6369(1996)39:1-3<39:TILC-P>2.0.ZU;2-4
Abstract
The surface of Great Britain (GB) varies continuously in land cover fr om one area to another. The objective of any environmentally based lan d classification is to produce classes that match the patterns that ar e present by helping to define clear boundaries. The more appropriate the analysis and data used, the better the classes will fit the natura l patterns. The observation of inter-correlations between ecological f actors is the basis for interpreting ecological patterns in the field, and the Institute of Terrestrial Ecology (ITE) Land Classification fo rmalises such subjective ideas. The data inevitably comprise a large n umber of factors in order to describe the environment adequately. Sing le factors, such as altitude, would only be useful on a national basis if they were the only dominant causative agent of ecological variatio n. The ITE Land Classification has defined 32 environmental categories called 'land classes', initially based on a sample of 1-km squares in Great Britain but subsequently extended to all 240 000 1-km squares. The original classification was produced using multivariate analysis o f 75 environmental variables. The extension to all squares in GB was p erformed using a combination of logistic discrimination and discrimina nt functions. The classes have provided a stratification for successiv e ecological surveys, the results of which have characterised the clas ses in terms of botanical, zoological and landscape features. The clas sification has also been applied to integrate diverse datasets includi ng satellite imagery, soils and socio-economic information. A variety of models have used the structure of the classification, for example t o show potential land use change under different economic conditions. The principal data sets relevant for planning purposes have been incor porated into a user-friendly computer package, called the 'Countryside Information System'.