This　paper　develops　a　new　representation　to　detect　the　edge　features　on　multispectral　remotely　sensed　imagery　which　is　based　on　the　concept　of　combining　dyadic　wavelet　transform　of　Mallat　with　first　fundamental　form.　The　dyadic　wavelet　transform　can　be　applied　to　produce　the　multiscale　edge　detection,　and　making　use　of　the　first　fundamental　form　is　for　edge　detection　of　multispectral　images.　The　representation　provides　a　local　measure　for　the　contrast　of　a　multispectral　image　at　different　scales.　A　variety　of　experiments　by　using　the　IKONOS　images　and　Quick　Bird　images　of　Nanjing　area　are　presented　to　demonstrate　the　representation　efficient　It　is　shown　from　the　results　that　the　edge　information　of　the　objects,　i.e.　road,　factory,　paddy,　can　be　detected　clearly　from　coarse　to　fine　at　different　scale　levels.　The　technique　of　detecting　edge　information　on　the　multispectral　image　is　demonstrated　to　be　beneficial　to　using　the　numerous　data　of　multispectral　remotely　sensed　imagery.　And　the　multiscale　edge　detection　method　paves　the　way　for　developing　the　applications　of　object-oriented　method　in　remote　sensing.