An Increment Based Model for Multi-resolution Geodata Management in a Mobile System

Follin, Jean-Michel; Bouju, Alain; Bertrand, Frédéric; Stockus, Arunas

doi:10.1007/11599289_5

Cited by 3 publications

(1 citation statement)

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“…Specialists and scholars have long committed to improve previous algorithms and data structures, and made considerable achievements in reducing data redundancy, improving the efficiency of data access and maintaining consistency of spatial data [3][4][5][6][7]. In addition, a series of concept were proposed, such as "critical scale", "incremental", providing new ideas and methods for the representation of multi-scale vector data [8][9][10]. The existing method of multi-scale representation is broadly divided into four categories: multi-scale explicit storage, initial scale changes accumulation, Key scale function evolution and Senior scale automatic generalization.…”

Section: Introductionmentioning

confidence: 99%

Research on the Method of Feature-Based Multi-scale Vector Data Model

Yang

Zhang

et al. 2013

Computer and Computing Technologies in Agriculture VI

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International audienceMulti-scale representation of spatial data is a research focus in GIS, while building multi-scale data model is a key to implementing multi-scale representation of vector data. In view of the shortcomings of existing multi-scale data model in geographical cognition and special analysis, this paper puts forward a method of feature-based, and studies on it qualitatively from definition, description and extraction. Compared to conventional single-scale E-R model, in this paper, the key strategies of building multi-scale conceptual model are put forward. Deeply study and analysis are applied on abstraction and expression of multiple geometric characteristics, of multi-attribution, and of semantic relation among different scales,and the design of feature-based multi-scale conceptual model is realized. Finally, the object-oriented multi-scale logic model is researched, which lays a theoretical foundation for building the feature-based multi-scale vector data model

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