Study On Land-use Database Cartographic Generalization With Multi-Constraints Consideration

Land-use database is a thematic type of digital map databases which is based on a detailed survey of land-use status. It is mainly used for land resource management to reflect the land location, quantity, quality, spatial distribution, land-use type, ownership and use status etc. The same as the general geographic data, land-use data contains spatial data and attribute data, the polygons in the land-use spatial data have the characteristic of covering the entire space region with seamless distribution, and the land-use attribute data are enriched with semantic information and multi-level thematic characteristics. Therefore, land-use database cartographic generalization is different from common map database cartographic generalization, it is the typical application for cartographic generalization theory and technology taking into the field of land-use thematic data, its purpose is to improve the map’s readability and understandability. In the process of cartographic generalization, it should consider the regional distribution patterns of sporadic parcels, statistical characteristics, semantics, topology, graphics, precision constraints and other factors according to the application target requirements and mapping regional characteristics, in addition to considering the traditional cartographic theory factors, it needs to generalize systematically in a comprehensively constrained order. Many scholars have done a lot of research on land use data generalization, and made a series of research results, but these studies were mainly, on the one hand, on an interactive generalization for operation lacking of intelligence, and on the other hand, these algorithm usually only took into account a certain constraint or focused on a particular aspect of generalization, due to the difficulty of implementing multiple constraints, which made the result attend to one thing and lose another, and the land-use data generalization is a systematic project, it needs to consider the various constraints. Therefore, neither in theory nor in practical applications, it is meaningful to study on multiple constraints for land use data generalization, and make research on new methods and intelligent system.This thesis focuses on sporadic parcels of land-use database, examines its rational procedure that should be kept to in the generalization flow, the operation that generalization should be taken, and the constraints that operation should be taken into account. According to the operations’ order, polygons’merging generalization, narrow and long polygons’dimension-reducing generalization and polygons’simplifying generalization which are the most common operations for the polygons’ generalization are taken into account, studying on the automatically generalizing methods under the control of multiple constraints and building an intelligent land-use database generalizing system, a land-use data generalization experiment is executed from scale1:10000to1:50000, and the generalization results are assessed which is to verify the proposed algorithm whether is effective and rational and the intelligent generalizing system whether is feasible and practical. Specific research works are as follows:1) The purpose and significance of this research is introduced, then, the general map cartographic generalization research status quo and land-use map generalization research status quo are summarized, the lack of current research on land-use data generalization is pointed out, and the scope of this thesis and the research content are defined.2) The concept of constraint for cartographic generalization and the impact of constraint on cartographic generalization are introduced. The basic characteristics of land use data that multilayer spatial data organization, to cover the whole region by sporadic parcels and rich semantic information and thematic information are analyzed. The difference between land-use map cartography generalization with common map cartographic generalization is introduced. The systematic knowledge of constraints for land-use database cartographic general ization consist of six aspects, such as scale constraint, structural constraint, spatial relations constraint, semantic constraint, geometric constraint and operation process constraint, and each constraint’s meaning and significance is elaborated. Considering the quality controlling and integrity of generalization, several methods for land-use database generalization result assessment are proposed, including area change rate, semantic similarity, structural similarity and distribution stability, which is in order to check whether the results are reasonable, and to ensure generalization quality.3) As for sporadic parcels automatically merging generalization, what constraints that should be taken into account as well as the order that constraints should take for sporadic parcels merging generalization is analysed, and the merging generalization is divided into three types according to the topological relations between polygons, their are aggregation, consolidation, and amalgamation, each type’s meaning and method of operation is given, it points out that the amalgamation operation can be considered a special case of the consolidation operation, and that the aggregation operation should be taken before the consolidation operation. Then, a method for sporadic parcels aggregation generalization is proposed based on raster and vector data model, firstly, it divides the sporadic parcels into several spatial zones and takes cluster analysis base on raster data model, secondly, it aggregates the cluster polygons based on vector data model. The method takes into account the spatial distribution constraint of polygons, semantic constraint, graph structure constraint, precision constraint and other constraints. Another method for sporadic parcels consolidation generalization is proposed based on neighborhood relationship analysis of parcels, in which the measure of neighborhood relation is the key point. A method for measuring the degree of neighborhood considering the topology and semantic constraints is introduced, and on this basis, the order for the terra-type parcels consolidation to take is given. Finally, the experiment flow for sporadic parcels automatically merging generalization and results are presented.4) As for long and narrow polygon automatic dimension-reducing generalization, the reason that why do the long and narrow polygons need to take dimension-reducing generalization and what inconsistencies would be made by the dimension-reducing generalization is given, the lack of current research is pointed out. An method for detecting long and narrow polygon automatically and an method for segmenting the long and narrow part of polygon automatically witch are all based on CDT is proposed, on this basis, a method for long and narrow polygon automatic dimension-reducing generalization is introduced. Then, focusing on the inconsistency of topology and semantics produced by the dimension-reducing generalization, an approach for the inconsistencies correcting is given separately. The previous is based on the topology between the target polygon and its adjacent polygons, it classifies the arcs into three types, Ⅰ, Ⅱ and Ⅲ, and presents that the topology consistency correcting is keeping the type I arcs, deleting type II arcs, and prolong the type III arcs to the polygon’s centerline, then, clips the arcs and rebuild the topology partly, and the latter aims at semantics consistency correcting based on the sematic rules. Finally, the experiment flow for the long and narrow polygon automatic dimension-reducing generalization and results are presented.5) As for sporadic parcels automatically simplifying generalization, based on the detailed analysis of various constrained factors that impact on the polygons simplification, it divides the sporadic parcels into two major categories that are natural features and man-made features according to the geographic features of polygons’ expression, and the characteristics of each type of polygons and simplification priorities are analyzed. In the following, an improved version of least squares adjustment for man-made features simplification algorithm considering multiple constraints is proposed base on the principle of building polygons simplification algorithm, the algorithm first detecting the structure of man-made feature, then pretreating the polygon before taking simplification that whose edges are shared by another polygon, the last, constructing various equations according to the simplification required multiple constraints, and solving the equations under the least-squares adjustment to get the final results. For natural features simplification, it points out that topological relation, the curved character of polygon’s boundary and area balance maintain are mainly constraints that natural features simplification should take into account, and it divides the polygons into island polygons and non-island polygons according to whether the polygon is contained by other polygon. For the non-island polygons, an automatically simplifying algorithm is presented base on the curved character of polygon’s boundary and considering multiple constraints, it first detecting and identifying the bend character of polygons shared borders base on CDT, and analyzing its convex characteristics, then taking a progressive simplification policy, it deletes the convex bend alternatively to keep the polygon’s area balance as possible as it can in the process of simplification, and finally exaggerating or deleting some bend to balance polygon’s accumulation area of simplification, getting the result of simplification with polygon’s area kept balanced. For the island polygons, first splitting the polygon’s boundary with its smallest outsourcing rectangle, then taking the policy of non-island polygon’s simplification for each section, thus keeping the polygon’s mainly direction and overall structure characteristics well in addition, expect containing the base area balance and bending characteristics constraints. In order to test the effectiveness of automatically simplifying algorithm for polygons, an experimental flow of polygons automatically simplifying generalization and results are presented at last.6) A prototype system is analyzed and designed based on the actual application requirements for land use database cartographic generalization, and the prototype system called Land use-Gen which meet the land use database cartography is developed on the MapGIS K9platform using MS Visual Studio2005. The system takes a workflow policy design, which takes the required source data, generalization operators, generalization parameters, generalization knowledge, generalization rules and other necessary resources as a flow node in the generalizing process and each node is stored in the system’s functional warehouse. The cartographers, according to the pre-established solution of generalizing operation for project, build the generalizing work flow with the referring flow node in the process of generalization using system’s providing build tool, and each work flow is for a specific generalizing application requirements, it is a embodiment of cartographic experts decision-making for generalization. Therefore, when each work flow is executed, the generalizing process is endowed with some knowledge, experience and decision-making ability of people, and thus making the system have a certain intelligence. In order to check the system’s feasibility and practicality, an experiment conducted with Tie shan gang land use data of Guang xi for generalization from1:10000to1:50000is described in detail.