Reed Wetland Extraction in the Yellow River Delta Nature ReserveBased on Knowledge Inference Technology

摘要

Based on Landsat TM images and 155 field survey points in 2001 , reed wetland is derived using knowledge inference technology. Six types of wetland are determined using supervised classification method. On account of the confusions between reed and other types of wetland , rules are established using methods as following steps reed wetland is extracted from mudflat wetland , rearing and shrimp pond and water body according to the value of normalized digital vegetation index ( NDVI) ( NDVI > 110 in the image of January and NDVI > 95 in the image of August) ; the reed is distinguished from paddy field only if the value of texture mean ( based on August image) is less than 10; the reed wetland is separated from the Chinese tamarisk, providing the value of band3 based on principal component analysis ( KL3 ) is more than 100. All these classification rules are built using knowledge engineer based on Erdas Image software ; then classification map is obtained by neighbor analysis technology. The accuracy estimation shows that knowledge — based classification gets total accuracy of 89. 02% and the kappa coefficient of 0. 893 , 2 , which is more effective than the traditional supervised classification ( the total accuracy is 81.60% and the kappa coefficient is 0. 793 ) .