General Entropy Model of Line Segments Uncertainty in GIS

Spatial data uncertainty can directly affect the quality of digital products and GIS-based decision making. On the basis of the characteristics of randomicity of positional data and fuzziness of attribute data, taking entropy as a measure, the stochastic entropy model of positional data uncertainty and fuzzy entropy model of attribute data uncertainty are proposed. As both randomic-ity and fuzziness usually simultaneously exist in linear segments, their omnibus effects are also investigated and quantified. A novel uncertainty measure, general entropy, is presented. The general entropy can be used as a uniform measure to quantify the total un-certainty caused by stochastic uncertainty and fuzzy uncertainty in GIS.

FLEXIBLE MULTIBODY SYSTEM DYNAMICS-FINITE SEGMENT METHOD

The principle and method of flexible multibody system dynamics is presented. The dynamic equation have been developed by means of Huston's method based on Kane's equation. In which the flexible members with general cross-section characters were divided into finite segment models under the assumption of small strain. In order to decrease the degrees of freedom of the system and increase the efficiency of numerical calculation. the mode transformation has been introduced. A typical example is presented. and the foregoing method has been perfectly verified.

Automatic generalization of metro maps based on dynamic segmentation

A metro map is usually optimized for the readability of connections and transportation networks structure.In order to assure good readability and meet aesthetic considerations,a set of principles for good metro map layout are proposed.According to these principles,a new methodology based on dynamic segmentation is presented to produce the metro maps automatically.Firstly,routes are constructed according to the line attribute similarity and geometry continuity.Then a set of cartographic generalization methods about the shape,angle,length,and topology are presented for these routes.This method is validated by Beijing metro plan map.From the experiment results,it can be concluded that this new method is more effective than the static segmentation method to produce metro maps with better readability for route plans.

Investigating the influence of segmentation in estimating safety performance functions for roadway sections

Safety performance functions（SPFs） are crucial to science-based road safety management.Success in developing and applying SPFs, apart data quality and availability, depends fundamentally on two key factors： the validity of the statistical inferences for the available data and on how well the data can be organized into distinct homogeneous entities. The latter aspect plays a key role in the identification and treatment of road sections or corridors with problems related to safety. Indeed, the segmentation of a road network could be especially critical in the development of SPFs that could be used in safety management for roadway types, such as motorways（freeways in North America）, which have a large number of variables that could result in very short segments if these are desired to be homogeneous. This consequence, from an analytical point of view, can be a problem when the location of crashes is not precise and when there is an overabundance of segments with zero crashes. Lengthening the segments for developing and applying SPFs can mitigate this problem, but at a sacrifice of homogeneity. This paper seeks to address this dilemma by investigating four approaches for segmentation for motorways, using sample data from Italy. The best results were obtained for the segmentation based on two curves and two tangents within a segment and with fixed length segments. The segmentation characterized by a constant value of all original variables inside each segment was the poorest approach by all measures.

A raster-based typification method for multiscale visualization of building features considering distribution patterns

In map multiscale visualization,typification is the process of replacing original objects,such as buildings,using a smaller number of objects while maintaining initial geometrical and distribution characteristics.During the past few decades,many vector-based methods for building typification have been developed,whereas raster-based methods have received less attention.In this paper,a new method for the typification of buildings with different distribution patterns called superpixel building typification(SUBT)is developed based on raster data.Using this method,buildings with different distribution patterns,such as linear,grid and irregular patterns,are first grouped by image connected component detection and superpixel analysis.Then,the new positions for building typification are determined by superpixel resegmentation.Finally,a new representation of the buildings is determined through analysis of the orientation and shape of the buildings in each superpixel.To test the proposed SUBT method,buildings from both cities and countrysides in China are applied to perform typification.The experimental results show that the proposed SUBT method can realize typification for buildings with linear,grid and irregular distributions while effectively maintaining the original distribution characteristics of the buildings.