Research On Geographic Analysis Task Driven Multi-source Geography Data Extraction And Push Method

Different models exist distinct geographic differences geographic data needs. Increasingly complex requirements of geographic analysis tasks coupled with enhanced integration between models, leading to the task, even for the same geographic analysis, data conversion and transformation among which there may be a big difference. So, whether it is from the ease of use or the geographical models from model integration perspective, need to bridge the geographical structure of the model and geographic data between multiple sources. By explicitly model the specific needs of the data, multi-source geodatabase schema and data conversion tool, interconnected geographic models and data.Starting from the characteristics of geographic data. Geographic data classification, calibration and automatic extraction is an important way to achieve geographic data model needs to adapt. While the data needs of different models for system data, summarize relatively generic model interface is standardized data interface to achieve the model, through the integration between the different models is important to protect the data stream. Therefore, relying on geographic analysis tasks, starting from the data requirements of geographic data and geographic features two main model was constructed based on geography task model of unified data management, extraction and matching, and then build task flow model based on geographic analysis model platform is an effective model to improve geographic availability, an important way to strengthen the analytical capabilities of geographic model.This paper models and geographic data from a geographic perspective dual constructed based on data classification and description of the topic and the data type and data-based and integrated in a single dimension dimension extraction method based on this. Analysis of the data model needs to extract design information and operating data requirements operator database, create a database data into the data stream and automatically push method model demand. The main contents are:1:Based on geographic data MongoDB unified organization and management methodsOf the existing multi-source geographic data characteristics are summarized and analyzed to study the existing data classification method proposed multi-source geographic data classification method combines thematic data and geographic data types. Use MongoDB unstructured storage mode, to build a variety of geographic data MongoDB unified storage management interface, multi-source MongoDB-based unified organization and management of geographic data.2:Extraction and automatic push mechanism based on the data dimension task modelCarding a common geography and inductive analysis model library, tasks needs of different models and data needs hierarchical structure analysis; through demand template to build the model, the model needs to achieve the extraction; task-demand-driven model, the use of dimension extraction after extraction operations functions and operators libraries, database schema, extraction operation, connection between the child and the operation of the model calculation, the dimension data extraction and push.3:Task-based model and the data is automatically pushed coastal beach analysis prototype systemConstruction of the data storage, data display, data extraction, data manipulation and data flow as the main functional blocks to build a prototype system to analyze coastal beach, for example, to verify the unified multi-source geographic data management, data extraction and automatic push dimensions feasibility.