Research On Detection And Handling Of Spatial Conflicts Between Building And Road Feature Based On Multi-constraint Optimization Method

Cartographic generalization is a cartographic method to establish a new map model that can reflect the regional geographic laws and characteristics through the selection,simplification,generalization and relationship coordination of map content under the conditions of map use,scale and geographic characteristics of the cartographic area.Its goal is to provide users with appropriate content and exquisite visual effects.With the rapid development of network information technology,the increasing enrichment of crowd-sourced data,and the continuous growth of user’s personalized needs,map services are facing more extensive spatial information content,more complex element relationships,and richer graphical visualization.All these characteristics will cause more serious conflicts in the map space.More efficient detection,displacement,and evaluation processing strategies are needed to solve this problem.The new era of cartographic generalization is facing new challenges.In order to cope with this challenge,this thesis conducts a special research on the handling of conflicts in map space.Displacement is the most commonly used context-sensitive generalization operator for resolving spatial conflicts.In the process of displacement,not only the geometric and semantic characteristics of the conflicting features themselves,but also the influence of other elements in its neighborhood and the propagation effect of displacement must be considered.Therefore,displacement can be regarded as a multifactor decision-making process that satisfies a variety of cartographic constraints,so it can be solved by optimization techniques.The application premise of the displacement operation is that there is extra displacement space around the conflicting features.If the displacement space is insufficient,the spatial conflicts between the features cannot be resolved by using only the displacement operation.It is necessary to consider combining other generalization operators to deal with spatial conflicts.The use of optimization technology to solve the spatial conflicts between features is the development trend of automated generalization and intelligent generalization.Therefore,this paper takes the spatial conflicts between the two most important features on the map,building and road as the research object,and explores how to use optimization displacement method,and combine multiple generalization operators to deal with the spatial conflicts between them.The main research contents of the thesis are as follows:(1)This research summarizes the current related displacement methods for resolving spatial conflicts and compares the advantages and disadvantages of the optimized displacement methods,and systematically expounds the relevant theoretical basis supporting the spatial conflict handling of the features,including the theory of cartographic generalization and the theory of displacement operation.Finally,the basic principles of standard genetic algorithm and simulated annealing algorithm are introduced in detail and their defects are analyzed.On this basis,the implementation process of its improved multi-population genetic algorithm and genetic simulated annealing algorithm is described.(2)For the complex and changeable types of spatial conflicts between features,a classification standard for spatial conflicts that takes into account geometric and semantic features is proposed.Since displacement is the processing of the relationship between multi-element targets with different geometric dimensions,the conflicting objects involve the same type of elements and different types of elements,and the conflicting elements have different effects of internal and external forces.Therefore,this paper determines the displacement distance and displacement direction of the conflicting objects in different conflict types according to the geometric and semantic characteristics of the elements.At the same time,due to the propagation effect of displacement,the movement of the conflicting object will not only affect other elements in its neighborhood,but also the elements in the neighborhood will have an effect on the conflicting object,which will affect the displacement distance and direction of the conflicting object,which in turn affect the determination of the principle of displacement.(3)For the detection of spatial conflicts between features,a formal expression model of spatial conflict detection and conflict regions is established by using the idea of expression based on spatial field neighborhood.This model expresses the adjacency relationship between features by the connection of the constrained Delaunay triangulation network,and defines a specific function to detect the conflict area between conflicting objects,that is,a set of constrained Delaunay triangles meeting specific conditions.The paper uses a visual way to show the effect of conflict detection and conflict areas,and the results show that the model can effectively detect conflict areas in different conflict types and has universal applicability.(4)For the problem of spatial conflicts caused by the widening of roads in the block,a building displacement method based on multipopulation genetic algorithm is proposed.This method uses a spatial field model to detect conflict areas between features and calculate the number of conflicts.The total displacement distance and the number of remaining spatial conflicts are optimized control conditions.At the same time,the relative position relationship between the features and the arrangement pattern and other cartographic constraints are considered to obtain the best displacement position of the buildings in the block.In the experimental part,the performance of multipopulation genetic algorithm in building displacement is discussed,and the effectiveness of the displacement method is verified by using urban block building data,and the displacement results are evaluated qualitatively and quantitatively.At the same time,it is compared with the other two combinational optimization methods.(5)Aiming at the problem that the spatial conflicts between features in highdensity blocks cannot be resolved by using only displacement operations,a heuristic spatial conflict processing strategy based on the combination of multiple generation operators is proposed.The model uses a progressive selection operation to reduce the density of buildings in the block,uses a genetic simulated annealing algorithm to achieve the displacement of the buildings,and finally aggregates the remaining conflicting buildings to obtain the final result.This paper verifies the validity of the model with the data of high-density urban blocks,and conducts quantitative and qualitative analysis.The results show that combining multiple generalization operators can resolve complex conflict types,and more cartographic constraints can be considered.Aiming at the problem of spatial conflicts between buildings and roads in the process of cartographic generalization,this research proposes a building displacement method based on intelligent optimization methods and a strategy of multigeneralization operators to jointly handle spatial conflicts.It has made contributions to the realization of the automation and intelligent processing of spatial conflicts in the field of cartographic generalization.The disadvantage of this research is that it only studies the spatial conflict resolution methods between buildings and roads,and will further study the application of intelligent optimization methods in the spatial conflict resolution of other elements.