Abstract: ［Purpose/Significance］The calculation and deduction that takes the stage of national social development and the scenario of surveying and mapping into consideration is an application of space remote sensing intervening in social science. The proposed map information meta-learning framework model is expected to realize the archival activation and environment topology of remote sensing GIS geographic information data, based upon which the ubiquitous structural description of ancient map semantics could be achieced. As a result, a quantitative calculation basis could be provided for association studies with knowledge graph construction.［Design/Methodology］An integrated knowledge graph of map archives and history books was built to realize geographic transportational location mapping. Description and analysis of geographical classics could help realize the function of integrated retrieval and provide a complex research environment for the composition of geographic classics and spatial location.
［Findings/Conclusion］The proposed meta-information framework is able to realize efficient integration of single knowledge objective with broad external knowledge. Finally, it enables the analysis and research of map resources to achieve a leap from map archives to map data, then to map scenarios.［Originality/Value］This study provides a circumscription of semantic division between natural description semantics and image scenarios structural description. Besides, it can match suitable adaptive analysis models for different types of map scenarios, which effectively improves the efficiency of knowledge discovery and the robustness of geographic ubiquitous computing process in the field of space humanities.

Keywords: Map, Map scenario, Meta-learning framework of information, Knowledge graph, Geographic information system, Space calculation