Factor analysis and classification of remotely sensed data for monitoring tidal flats

Abstract

Interest in using remote sensing techniques, principally those involving satellite, in Wadden Sea research has centred on attempting a classification of the various sediment surface types present. Unlike most recent studies which have used mainly Landsat Multispectral Scanner data, we have assessed the feasibility of using Landsat Thematic Mapper data, which in conjunction with time series aerial photography, forms the basis of a strategy for remotely sensing the Wadden Sea. This paper focusses on an approach for extracting potentially “hidden” within-pixel information from multispectral data sets. A hierarchical (unsupervised) classification of a Thematic Mapper image successfully classified five different classes, including land, saltmarsh, water, cloud and tidal flat areas. This procedure thus enabled a “masking-out” of all classes other than those classified as tidal flat, following which a factor analysis was used to determine the minimum number of independent factors necessary to explain the observed variation in the signal received by the satellite. Three factors accounted for a total of 82% of the variation in all seven TM channels. Preliminary studies of the primary factor (score) image shows a good correlation with existing latterday cartographic data. Considering the proximate relationship between topography and other important biotic and abiotic sedimentary characteristics, this approach may prove valuable for future applications of satellite data for monitoring long-term change in physical and thus biological Wadden Sea characteristics. Ongoing research efforts are focussing on a classification and quantification of sub-pixel patchiness using aerial photography and ground surveys. The approaches taken and results obtained to date are discussed.