Updating Geospatial Data From Large Scale Data Sources

Abstract

ABSTRACT:In the past decades, many geospatial databases have been established at national, regional and municipal levels over the world. Nowadays, it has been widely recognized that how to update these established geo-spatial database and keep them up to date is most critical for the value of geo-spatial database. So, more and more efforts have been devoted to the continuous updating of these geospatial databases.Currently, there exist two main types of methods for Geo-spatial database updating: directly updating with remote sensing images or field surveying materials, and indirectly updating with other updated data result such as larger scale newly updated data. The former method is the basis because the update data sources in the two methods finally root from field surveying and remote sensing. The later method is often more economical and faster than the former. Therefore, after the larger scale database is updated, the smaller scale database should be updated correspondingly in order to keep the consistency of multi-scale geo-spatial database. In this situation, it is very reasonable to apply map generalization technology into the process of geo-spatial database updating. The latter is recognized as one of most promising methods of geo-spatial database updating, especially in collaborative updating environment in terms of map scale, i.e , different scale database are produced and maintained separately by different level organizations such as in China.This paper is focused on applying digital map generalization into the updating of geo-spatial database from large scale in the collaborative updating environment for SDI. The requirements of the application of map generalization into spatial database updating are analyzed firstly. A brief review on geospatial data updating based digital map generalization is then given. Based on the requirements analysis and review, we analyze the key factors for implementing updating geospatial data from large scale including technical and non-technical factors, followed by the general strategy of digital map generalization in practical production environment. In fact the most important factor is recognized that it is very difficult to establish generalization rules for production systems. We emphasized on this factor in our work and established a set of rules or constrains for scale topographical database updating 1:50000 scaled data from 1:10000 scaled data in a full digital environment mainly based on map specifications. Finally, We discussed the generic system structure and give an example of production system used in the project of 1:50000 scaled database updating in China.