Rough set is a new approach to uncertainties in spatial analysis.In this paper,rough set symbols are simplified and standardized in terms of rough interpretation and specialized indication.Rough spatial entities and t...Rough set is a new approach to uncertainties in spatial analysis.In this paper,rough set symbols are simplified and standardized in terms of rough interpretation and specialized indication.Rough spatial entities and their topological relationships are also proposed in rough space,thus a universal intersected equation is developed,and rough membership function is further extended with the gray scale in our case study.We complete three works.First,a set of simplified rough symbols is advanced on the basis of existing rough symbols.Second,rough spatial entity is put forward to study the real world as it is,without forcing uncertainties into crisp set.Third,rough spatial topological relationships are studied by using rough matrix and their figures.The relationships are divided into three types,crisp entity and crisp entity (CC),rough entity and crisp entity (RC),and rough entity and rough entity (RR).A universal intersected equation is further proposed.Finally,the maximum and minimum maps of river thematic classification are generated via rough membership function and rough relationships in our case study.展开更多
The essential of feature matching technology lies in how to measure the similarity of spatial entities.Among all the possible similarity measures,the shape similarity measure is one of the most important measures beca...The essential of feature matching technology lies in how to measure the similarity of spatial entities.Among all the possible similarity measures,the shape similarity measure is one of the most important measures because it is easy to collect the necessary parameters and it is also well matched with the human intuition.In this paper a new shape similarity measure of linear entities based on the differences of direction change along each line is presented and its effectiveness is illustrated.展开更多
文摘Rough set is a new approach to uncertainties in spatial analysis.In this paper,rough set symbols are simplified and standardized in terms of rough interpretation and specialized indication.Rough spatial entities and their topological relationships are also proposed in rough space,thus a universal intersected equation is developed,and rough membership function is further extended with the gray scale in our case study.We complete three works.First,a set of simplified rough symbols is advanced on the basis of existing rough symbols.Second,rough spatial entity is put forward to study the real world as it is,without forcing uncertainties into crisp set.Third,rough spatial topological relationships are studied by using rough matrix and their figures.The relationships are divided into three types,crisp entity and crisp entity (CC),rough entity and crisp entity (RC),and rough entity and rough entity (RR).A universal intersected equation is further proposed.Finally,the maximum and minimum maps of river thematic classification are generated via rough membership function and rough relationships in our case study.
文摘The essential of feature matching technology lies in how to measure the similarity of spatial entities.Among all the possible similarity measures,the shape similarity measure is one of the most important measures because it is easy to collect the necessary parameters and it is also well matched with the human intuition.In this paper a new shape similarity measure of linear entities based on the differences of direction change along each line is presented and its effectiveness is illustrated.
