Construction method of urban geographic information data warehouse

Abstract

The invention discloses a construction method of an urban geographic information data warehouse. Original spatial data are processed when missing data, repeating data and abnormal data exist, according to spatial characteristics of time type data, space type data and time and space mixed type data, all record values minus a record average value by a mean and sigma method and are divided by a record value standard deviation to obtain processed data; a model based on spatial characteristics according to the processed data is built to obtain an urban geographic information data warehouse; and data changes in the original spatial data are monitored, data are extracted and updated according to a design feature object data table, when a preset time is up, the updated data are added into the urban geographic information data warehouse. The construction method of the urban geographic information data warehouse has the advantages of being capable of improving the query, analysis and monitoring efficiency and reducing the data extraction cost.

Description

technical field [0001] The invention relates to the field of urban geographic information systems, in particular to a method for constructing an urban geographic information data warehouse. Background technique [0002] GIS (Geographic Information System, geographic information system) has become a management application information system for storage, management, query, simple analysis and result display. Storage and management, and relatively simple auxiliary decision-making analysis, after years of hard work, its related technologies and tools have been perfected and gradually matured. [0003] With the diversified development of society, every city collects and stores a large amount of spatial basic data and industry attribute data, and it is growing at a rate of terabytes all the time. [0004] In the process of realizing the present invention, the inventor finds that at least the following disadvantages and deficiencies exist in the prior art: [0005] To a certain e...

AI Technical Summary

Problems solved by technology

[0005] To a certain extent, these massive data have exceeded the analysis and processing capabilities of traditional geographic information systems, making the efficiency of query and analysis slow. For example, urban geographic information data in Tianjin has grown rapidly from GB, TB to PB. When traditional geographic information systems process massive data, the waiting time for graphic browsing and printing output is long, which cannot meet the requirements for high-performance, large-capacity distributed storage and management

Secondly, traditional data warehouses have great limitations in processing spatial data and cannot support spatial feature data. They are usually converted into non-spatial data for processing, resulting in the loss of many spatial features and inaccurate processing results.

For example: urban geographic information data is space-oriented, has spatial dimensions and spatial measurements, can do various spatial data analysis, and statistically analyzes the spatial structure and morphological change trends of industrial land in Tianjin. It is difficult to implement traditional data warehouses because traditional data Warehouses are mainly aimed at non-spatial data. When converting spatial data to non-spatial data, the spatial characteristics, temporal characteristics, and topological characteristics of industrial land are lost.

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