To forecast the incidence of the common tick, Ixodes ricinus, the authors used the finding that some types of vegetation may indicate the presence of the tick. To obtain the necessary information in a scope which would enable its practical application in medicine to prevent populational exposure to ticks, remote sensing data were utilized as obtained from the Multispectral Scanner operating aboard Landsat 5. A file was selected from the full scene representing a territory which measured 41 by 41 kilometers and in the centre of which there was an area known to have consistently high tick numbers, as revealed in a 25-year continuous study of I. ricinus, and which proved to be a natural focus of tick-borne encephalitis. This area (Potepl) was taken as a model and was compared with its surroundings. Six landscape classes were examined (1--coniferous forest, 2--leaved forest, 3--mixed forest, 4--water basins, 5--glades, 6--housing developments), the former three being of crucial importance to evaluate the probability of tick presence. The 6th category is significant in assessing human exposure to ticks. Data processing was carried out by supervised classification using the Baye's decision rule of maximum likelihood. The findings were obtained both in a graphic form and in the form of statistical reviews as regards the presence of appropriate landscape categories.