A method for identification and fusion update of natural resource survey and monitoring data

Abstract

The present invention relates to a natural resource survey and monitoring data identification and fusion update method, comprising: acquiring natural resource survey and monitoring data and multi-source vector reference data, constructing a Voronoi diagram / generalized Voronoi diagram with entities in the natural resource survey and monitoring data as source entities , based on the constructed Voronoi diagram and generalized Voronoi diagram, search for the corresponding target entity from the multi-source vector reference data; carry out geometric identification and attribute identification on the natural resource survey and monitoring data and candidate identification sets in turn, and calculate the similarity of graphics and attributes. Compared with the preset threshold to determine the state changes of the graphics and attributes, incremental data is extracted from the candidate recognition set to update the changed graphics and / or attributes. By implementing the method of the invention, incremental data can be efficiently extracted from multi-source vector reference data, the current situation of natural resource survey and monitoring data can be ensured, and the data update period can be shortened.

Description

technical field [0001] The invention belongs to the technical field of geographic information and data identification, and in particular relates to a method for identifying and merging and updating natural resource survey and monitoring data. Background technique [0002] Natural resources refer to the sum of natural environmental factors that exist naturally, have use value, and can improve the current and future welfare of human beings. Most resource-rich countries in the world, such as the United States, Russia, and Canada, implement overall management of natural resources. Due to China's vast territory, natural resources have to be managed separately. Therefore, various natural resource classification systems and data standards are not unified. There are repetitions, overlaps, and even contradictions in terms of objects, scope, and content, which make it difficult to comprehensively analyze and utilize data results. [0003] One of the key points that need to be grasped...

AI Technical Summary

Problems solved by technology

However, there is no technical solution in the prior art to realize the data identification and fusion update method

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