Automatic　building　rooftop　extraction　is　of　great　importance　to　many　applications　including　building　reconstruction,　solar　energy　supply,　and　disaster　management.　This　study　proposes　a　building　rooftop　extraction　method　using　DSM　data　generated　from　aerial　stereo　images　and　vegetation　cover　vector　data.　The　method　consists　of　five　steps:　noise　filtering,　dilation　reconstruction,　vegetation　and　terrain　region　removal,　region　growing　and　merging,　and　post-processing.　We　applied　the　proposed　method　to　the　centre　of　Shanghai,　China,　a　typical　urban　area.　Experimental　results　show　that　the　proposed　method　can　successfully　extract　building　rooftops,　with　an　approximately　82.6%　quality　percentage　and　96.2%　matched　overlay.