This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of glo...This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of global Moran Coefficient, Local Moran and Local Geary. Furthermore, a user-friendly statistical module, combining spatial statistical analysis methods with GIS visual techniques, is developed in Arcview using Avenue. An example is also given to show the usefulness of this module in identifying and quantifying the underlying spatial association patterns between economic units.展开更多
This paper discusses and sums up the basic criterions of guaranteeing the labeling quality and abstracts the four basic factors including the conflict for a label with a label, overlay for label with the features, pos...This paper discusses and sums up the basic criterions of guaranteeing the labeling quality and abstracts the four basic factors including the conflict for a label with a label, overlay for label with the features, position’s priority and the association for a label with its feature. By establishing the scoring system, a formalized four-factors quality evaluation model is constructed. Last, this paper introduces the experimental result of the quality evaluation model applied to the automatic map labeling system-MapLabel.展开更多
This paper presents a method of adding label to the map especially for the point feature. This method overcomes the shortcoming of traditional methods, e.g. Conflict\|Backtracking method. Its kernel algorithm use the ...This paper presents a method of adding label to the map especially for the point feature. This method overcomes the shortcoming of traditional methods, e.g. Conflict\|Backtracking method. Its kernel algorithm use the hopfield neural network to find the best label position for point feature. The experimental results proves that this algorithm has good permanence and high speed.展开更多
文摘This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of global Moran Coefficient, Local Moran and Local Geary. Furthermore, a user-friendly statistical module, combining spatial statistical analysis methods with GIS visual techniques, is developed in Arcview using Avenue. An example is also given to show the usefulness of this module in identifying and quantifying the underlying spatial association patterns between economic units.
基金Funded by the National Natural Science Foundation of China (N0.40001019).
文摘This paper discusses and sums up the basic criterions of guaranteeing the labeling quality and abstracts the four basic factors including the conflict for a label with a label, overlay for label with the features, position’s priority and the association for a label with its feature. By establishing the scoring system, a formalized four-factors quality evaluation model is constructed. Last, this paper introduces the experimental result of the quality evaluation model applied to the automatic map labeling system-MapLabel.
文摘This paper presents a method of adding label to the map especially for the point feature. This method overcomes the shortcoming of traditional methods, e.g. Conflict\|Backtracking method. Its kernel algorithm use the hopfield neural network to find the best label position for point feature. The experimental results proves that this algorithm has good permanence and high speed.
