Spatial representation and spatial interaction
著者
書誌事項
Spatial representation and spatial interaction
（Studies in applied regional science, v. 10）
Martinus Nijhoff Social Sciences Division, 1978
大学図書館所蔵 件 / 全35件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Bibliography: p. 207-212
内容説明・目次
内容説明
In recent years the development of spatial referencing techniques in com puter-based information systems has enormously increased the opportuni ties that exist for the treatment and presentation of both point and interaction data. The extent of this increase has drawn attention to the need for special aggregation and clustering procedures to be developed which enable data to be grouped in an efficient way for analytical pur poses with a minimum loss of detail. In the case of interaction data, economy of representation is particularly important as the analysis is further complicated by the two-way directionality that is inherent in each data set. Procedural rules of this kind are needed not only for descriptive analy sis and spatial accounting but also for hypothesis testing and the develop ment of operational models of spatial interaction. Yet the importance of spatial representation in this kind of research has only recently been fully understood. The first generation of urban development models that were developed in Europe and North America during the 1960's often treated matters of zoning system specification very casually, even though in some cases this imposed severe limits on the interpretation of their findings and it was not until the Centre for Environmental Studies/Cheshire project (Barras et al. , 1971) that a serious attempt was made to put forward general principles which could be used as guidelines in future work.
目次
1. Spatial representation and spatial interaction: an overview.- 1.1. Introduction.- 1.2. The multi-criteria aggregation problem.- 1.3. The multi-level specification problem.- I: Multi-Criteria Aggregation Problems.- 2. Sequential treatment of the multi-criteria aggregation problem: a case study of zoning system design.- 2.1. Introduction.- 2.2. The Wirral case study.- 2.3. Conclusions.- 3. An empirical investigation of the use of Broadbent's rule in spatial system design.- 3.1. Introduction.- 3.2. Broadbent's rule.- 3.3. The Merseyside study.- 3.4. Conclusions.- 4. A simplistic approach to the redistricting problem.- 4.1. Introduction.- 4.2. Electoral redistricting methods.- 4.3. The development of the simplistic algorithm.- 4.4. The redistricting algorithm.- 4.5. Application of the procedure to the West Midlands.- 4.6. Conclusions.- 5. An optimal zoning approach to the study of spatially aggregated data.- 5.1. Introduction.- 5.2. Alternative approaches to the design of zoning systems for spatial study.- 5.3. Solving the automatic zoning problem.- 5.4. Applications.- 5.5. Zone design and spatial study.- 6. Speculations on an information theoretic approach to spatial representation.- 6.1. Introduction.- 6.2. Spatial entropy functions.- 6.3. Measures of relative spatial information.- 6.4. The aggregation of information.- 6.5. Theoretical aggregation problems: in a population density model.- 6.6. Hierarchical aggregation.- 6.7. Information measures of spatial efficiency.- 6.8. Spatial probability models incorporating zone size.- 6.9. An empirical algorithm based on spatial information theory.- 6.10. Conclusions.- II: Multi-Level Specification Problems.- 7. The specification of multi-level systems for spatial analysis.- 7.1. Introduction.- 7.2. Slater's method.- 7.3. The Intramax procedure.- 7.4. An analytical framework for the specification of multi-level spatial systems.- 7.5. Conclusions.- 8. Hierarchical trip distribution models and the design of accounting systems.- 8.1. Introduction.- 8.2. The matching of hierarchical models.- 8.3. Compound accounting systems.- 8.4. Conclusion.- 9. Some suggestions for future research.- References.
「Nielsen BookData」 より