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Proceedings Paper

An on-demand provision model for geospatial multisource information with active self-adaption services
Author(s): Hong Fan; Huan Li
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Paper Abstract

Location-related data are playing an increasingly irreplaceable role in business, government and scientific research. At the same time, the amount and types of data are rapidly increasing. It is a challenge how to quickly find required information from this rapidly growing volume of data, as well as how to efficiently provide different levels of geospatial data to users. This paper puts forward a data-oriented access model for geographic information science data. First, we analyze the features of GIS data including traditional types such as vector and raster data and new types such as Volunteered Geographic Information (VGI). Taking into account these analyses, a classification scheme for geographic data is proposed and TRAFIE is introduced to describe the establishment of a multi-level model for geographic data. Based on this model, a multi-level, scalable access system for geospatial information is put forward. Users can select different levels of data according to their concrete application needs. Pull-based and push-based data access mechanisms based on this model are presented. A Service Oriented Architecture (SOA) was chosen for the data processing. The model of this study has been described by providing decision-making process of government departments with a simulation of fire disaster data collection. The use case shows this data model and the data provision system is flexible and has good adaptability.

Paper Details

Date Published: 14 December 2015
PDF: 8 pages
Proc. SPIE 9815, MIPPR 2015: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 98150B (14 December 2015); doi: 10.1117/12.2207380
Show Author Affiliations
Hong Fan, Wuhan Univ. (China)
Huan Li, Wuhan Univ. (China)

Published in SPIE Proceedings Vol. 9815:
MIPPR 2015: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Jianguo Liu; Hong Sun, Editor(s)

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