Spatial　heterogeneity　of　airborne　remote　sensing　images　is　critical　for　surface　character　delineation.　The　purpose　of　this　paper　is　to　quantify　and　evaluate　the　spatial　variability　and　characteristic　scales　of　Coniferous　trees　from　multi-sensor　airborne　images　by　applying　variogram　modelling.　The　Airborne　Thematic　Mapper　(ATM),　Compact　Airborne　Spectrographic　Imager　(CASI-2),　Specim　AISA　Eagle　airborne　images　at　Harwood,　Northumberland,　UK,　were　utilized,　with　spatial　resolutions　of　9m,　7.2m　and　2.5m　respectively.　We　demonstrate　that　variogram　properties　provide　a　robust　assessment　of　the　differences　in　spatial　variability　and　characteristic　scale　between　multi-sensor　airborne　datasets.　Spatial　variability　of　Coniferous　trees　in　ATM　airborne　imagery　is　consistently　larger　than　CASI　airborne　imagery　in　blue,　green,　red　and　infrared　bands.　The　spatial　variability　of　Eagle　airborne　images　is　strongest　in　red　and　near　infrared　bands　but　weakest　in　the　blue　band.　For　the　blue,　green,　red　and　near　infrared　bands　utilized,　results　indicate　that　the　total　within-scene　variation　of　multi-sensor　airborne　images　increases　with　wavelength.　Moreover,　the　mean　characteristic　length　scale　consistently　decreases　with　the　nominal　spatial　resolution　and　spectral　bands.　It　is　recommended　that　applications　of　one　type　of　tree　development　observations　could　take　advantage　of　Eagle　images　in　the　near　infrared　band　to　gain　more　within-species　information　of　spatial　structure　and　its　variability.　Other　applications　like　mapping　tree　species　might　exploit　ATM　images　to　obtain　more　information　about　spatial　structure　and　its　variability　between　different　tree　species.　©　2011　IEEE.