It is difficult to distinguish mangrove from terrestrial vegetation or the mixed pixels of water and terrestrial vegetation due to the coastal wetland habit of mangrove.Moreover,the tide change also causes the change in spatial distribution characteristics of mangrove in remotely sensed imagery.Therefore,it is very difficult to precisely extract the spatial mangrove information by means of the remote sensing imagery of single tide,which was usually adopted yet.Nevertheless the mangrove resides in coastal wetland,where the tide level varies periodically.In order to solve the problem,it was attempted to make good use of the unique habit characteristics of mangrove based on Landsat TM remote sensing images of both high tide level and low tide level.The analysis results show that the separability between mangrove and the other objects are very good through WI_L+WI_H,GVI_L and GVI_L-GVI_H,which are developed by the tidal range information and tasseled cap transformation.Note that WI and GVI stand for wetness index and greenness vegetation index,respectively;while the subscripted L and H stand for low tide and high tide,respectively.The maximum likelihood classifier,an unsupervised classification method,was used to identify mangrove.The classification features based on the tidal range information,greenness index and wetness index can accurately map mangrove forest,and the producer's accuracy and user's accuracy of mangrove are 94.57% and 98.8%,respectively.