The use of geo tags in recording the location at which a picture was taken is becoming part of image metadata . Therefore , studying approaches to image classification that can favorably exploit both geo tags and the underlying geo context has become an emerging topic. This paper contributes to geo-aware image classification by studying how to encode geo information into image representation. Given a geo-tagged image, we propose to extract geo-aware tag features by tag propagation from the geo and visual neighbors of the given image. Depending on what neighbors are used and how they are weighted, we present and compare eight variants of geo-aware tag features. Using millions of Flickr images as source data for tag feature extraction, experiments on a popular benchmark set justify the effectiveness and robustness of the proposed tag features for geo-aware image classification.