Cellular automata emerged in the field of computer science to be used mainly by proponents of complexity theory to demonstrate the relation between the micro and macro behaviour of complex systems. The cellular automata are based on rather strong assumptions of the autonomy of individual automata behaviour, homogeneity of their characteristics and transition rules. This paper claims that those features make cellular automata suitable for the study of general processes of urban growth, spread of diseases or propagation of innovations, but less for study of land use change processes in general. The main reason is the artificiality of cellular automata that makes them ignore many aspect of the physical, economic and legal reality causing the important drivers and agents of land use change being improperly represented. Several decades of effort to implement cellular automata for land use simulation have brought many interesting innovations that made the usability of cellular automata for land use studies much more acceptable. The most significant adaptations of cellular automata are described in the background of several existing, well known simulation models.