In complex object oriented databases, the purpose of introducing class hierarchy is to express ISA sematics, to realize inheriting and to reuse schema definition codes. The schema definition and schema evolution, base...In complex object oriented databases, the purpose of introducing class hierarchy is to express ISA sematics, to realize inheriting and to reuse schema definition codes. The schema definition and schema evolution, based on the partial order of lattice, often cause the loss of information inheriting and the redundance of schema dedrition. Based on the fullness of the inheritance shownby class hierarchy three normal forms of class hierarchy are given in this paper, and a general algorithm of normalization of class hierarchy is presented,following the Boolean algebra model of class hierarchy The loss of information inheritance can be avoided when they are applied to schema design and schema evolution.展开更多
Normalized Difference Vegetation Index （NDVI） is a very useful feature for differentiating vegetation and non-vegetation in remote sensed imagery. In the light of the function of NDVI and the spatial patterns of the...Normalized Difference Vegetation Index （NDVI） is a very useful feature for differentiating vegetation and non-vegetation in remote sensed imagery. In the light of the function of NDVI and the spatial patterns of the vegetation landscapes, we proposed the lacunarity texture derived from NDVI to characterize the spatial patterns of vegetation landscapes concerning the ＂gappiness＂ or ＂emptiness＂ characteristics. The NDVI-based lacunarity texture was incorporated into object-oriented classification for improving the identification of vegetation categories, especially Torreya which was the targeted tree species in the present research. A three-level hierarchical network of image objects was defined and the proposed texture was integrated as potential sources of information in the rules base. A knowledge base of rules created by classifier C5.0 indicated that the texture could potentially be applied in object-oriented classification. It was found that the addition of such texture improved the identification of every vegetation category. The results demonstrated that the texture could characterize the spatial patterns of vegetation structures, which could be a promising approach for vegetation identification.展开更多
文摘In complex object oriented databases, the purpose of introducing class hierarchy is to express ISA sematics, to realize inheriting and to reuse schema definition codes. The schema definition and schema evolution, based on the partial order of lattice, often cause the loss of information inheriting and the redundance of schema dedrition. Based on the fullness of the inheritance shownby class hierarchy three normal forms of class hierarchy are given in this paper, and a general algorithm of normalization of class hierarchy is presented,following the Boolean algebra model of class hierarchy The loss of information inheritance can be avoided when they are applied to schema design and schema evolution.
基金supported by the National Natural Science Foundation of China (30671212)
文摘Normalized Difference Vegetation Index （NDVI） is a very useful feature for differentiating vegetation and non-vegetation in remote sensed imagery. In the light of the function of NDVI and the spatial patterns of the vegetation landscapes, we proposed the lacunarity texture derived from NDVI to characterize the spatial patterns of vegetation landscapes concerning the ＂gappiness＂ or ＂emptiness＂ characteristics. The NDVI-based lacunarity texture was incorporated into object-oriented classification for improving the identification of vegetation categories, especially Torreya which was the targeted tree species in the present research. A three-level hierarchical network of image objects was defined and the proposed texture was integrated as potential sources of information in the rules base. A knowledge base of rules created by classifier C5.0 indicated that the texture could potentially be applied in object-oriented classification. It was found that the addition of such texture improved the identification of every vegetation category. The results demonstrated that the texture could characterize the spatial patterns of vegetation structures, which could be a promising approach for vegetation identification.
