The use of remotely-sensed satellite imagery for landscape classification in Wales (U.K.)

Remotely-sensed satellite data from Landsat TM and MSS were processed digitally to make landscape classifications of three study areas of south east Wales. The classifications were constructed by classifying major variations in land cover mosaics within the areas, and using these data to group the 1 km × 1 km cells of the National Grid into landscape classes according to the combination of cover types found within them. The TWINSPAN algorithm, which is a polythetic, divisive classification method, was used as the basis of the study.The results showed that while satellite imagery could only be used to extract information about land cover, the close association betwen landscape, land cover and terrain meant that the major physical divisions in the study area could also be detected in the landscape classification. The landscape types recognised in the study were found to be consistent with those indicated in other independent data which relate to the areas. These data included the ITE Land Classes for Great Britain, and the Agricultural (June) Census statistics for England and Wales.The approach to landscape classification described allows landscape classifications to be made rapidly. These classifications can provide a sampling frameworks for landscape survey in areas where basic map data are lacking or resources for field survey are limited. The landscape classifications can also assist in making landscape evaluations since they allow different landscape types to be compared in respect of such properties such as their typicalness, rarity, naturalness and position on a geographical or ecological gradient.