Abstract. Although land cover mapping is one of the earliest applications of remote sensing technology, routine mapping over large areas has only relatively recently come under consideration. This change has resulted from new information requirements as well as from new developments in remote sensing science and technology. In the near future, new data types will become available that will enable marked progress to be made in land cover mapping over large areas at a range of spatial resolutions. This paper is concerned with mapping strategies based on 'coarse' and ' ne' resolution satellite data as well as their combinations. The status of land cover mapping is discussed in relation to requirements, data sources and analysis methodologies-including pixel or scene compositing, radiometric corrections, classi cation and accuracy assessment. The overview sets the stage for identifying research priorities in data pre-processingand classi cation in relation to forthcoming improvements in data sources as well as new requirements for land cover information. Introduction and objectiveLand cover, i.e. the composition and characteristics of land surface elements, is key environmental information. It is important for many scienti c, resource management and policy purposes and for a range of human activities. It is an important determinant of land use and thus of value of land to the society. Land cover varies at a range of spatial scales from local to global, and at temporal frequencies of days to millennia. As the need for environmental planning and management became important, an accompanying call for land cover information emerged in parallel.Land cover mapping is a product of the development of remote sensing, initially through aerial photography (Colwell 1960 ). This is because 'viewing' large areas repeatedly is necessary for acquiring information about land cover. For the same reason, land cover mapping has been perhaps the most widely studied problem employing satellite data, beginning with Landsat 1. However, most of the studies using ' ne' resolution data (i.e. 20-100 m) were methodological in nature, exploring various information extraction techniques and applying these over limited areas. Applications over large areas were hampered by the lack of suitable technology, an absence of a user community with a strong need for such information, a lack of appropriate analysis methodologies, and the cost of data. Thus, at the global level, land cover data sets compiled from ground surveys or various national sources (Mathews 1983, Olson et al. 1983 were, for a number of years, the major source of information.