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Wildlife studies increasingly employ thematic information, such as habitat classes, extracted from remotely sensed image data. Thematic information allows researchers to characterize biological processes of interest at various spatial scales. In and around Ikh Nart Nature Reserve of Mongolia, few large-scale habitat and landscape maps exist. Such maps are needed to support several long-term biological studies. Here we report the results of a maximum likelihood supervised classi fi cation of a fi ve-band multispectral composite Landsat 7ETM+ image of the Dalanjargalan Soum section of the reserve and surrounding areas in Dornogobi and Dundgobi Aimags. We classi fi ed the image into seven habitat classes: dense rock, low-density shrub, high-density shrub-rock mix, semi-shrub steppe, forb- dominated short grass steppe, tall vegetation, and ephemeral standing water bodies. Overall classi fi cation accuracy was 90.5% with a K hat statistic of 88.8%, and a user’s accuracy of >85% per class, suggesting strong agreement between map and ground reference information. As such, the map presents a detailed distribution of habitats that may be suitable for a variety of research applications including the analysis of wildlife ranging behavior and the identi fi cation of priority areas for conservation.