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In this study, Landsat 5-TM data were used to map urban land classes and the changes that occurred within them over a period of six years. The land classes were identified by Landsat 5-TM scenes taken in the same season in 1988 and 1994. The phenomena of land class changes were evaluated by adopting two remote sensing approaches, namely mapping and modelling, in a case study of the Bangkok Metropolitan area of Thailand. The quantitative results of changes, which were computed from a post-classification method, were used to analyse the pattern of changes in the urban land classes. The change-detection analysis indicated that 2% of agricultural land was lost, and there was a 14% increase in the commercial areas. The results demonstrated that the pattern of change in the urban land classes in Bangkok was that of agriculture lands to open lands; open lands to residential, and residential to commercial. The highest commercial land growth was observed in the high-density residential areas along main roads and the railway line. Data were generated from the two dates of TM images for the vegetationimpervious-soil (V-I-S) composition model. The trends of changes in the urban land classes and the anatomy of the study area were presented quantitatively through the V-I-S model. Good agreement was obtained between the values of changes computed for the impervious surfaces from the V-I-S model (which showed 6% changes) and the change-detection map (which showed 5.6% changes). The results of changes in the spatial pattern of commercial and residential areas (high, medium and low) emphasize that remote sensing data can be used for V-I-S modelling and mapping of urban surface features.
Madhavan et al. (Mon,) studied this question.