Five-layer hierarchical network (5-HiNet) of geospatial information service for AIGC of geographic analysis model

doi:10.11947/j. AGCS.2024.20240109.

Abstract

Abstract:

Within the context of artificial intelligence generation (AIGC) and large language model (LLM), improving the intelligence level of generating geographic analysis models has gained widespread attention in the field. This paper proposes a geospatial information service hierarchical network model, named 5-HiNet. This model allows for a step-by-step description of heterogeneous geographic analysis models based on the five-layer hierarchical sub-network structure of demand description, abstract model, functional module, service interface, and functional instance, which depicts the realization process of geographic analysis models from the general to the specific. Within the five-layer hierarchical sub-network structure, the 5-HiNet can integrate massive expert knowledge embedded in the geographic analysis models and thus form a well-rounded domain knowledge system. Furthermore, the 5-HiNet can be coupled with the LLM to generate geographic analysis models automatically. A prototype system with a case study is developed in this paper to demonstrate the feasibility of the proposed 5-HiNet, and several research directions and insights for future study are provided.

Key words: geospatial information service, geographic analysis model, hierarchical network, domain knowledge, intelligent generation

CLC Number:

P208

Huayi WU, Anqi ZHAO, Jianyuan LIANG, Shuyang HOU. Five-layer hierarchical network (5-HiNet) of geospatial information service for AIGC of geographic analysis model[J]. Acta Geodaetica et Cartographica Sinica, 2024, 53(11): 2053-2063.

Figures/Tables 6

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服务接口子网络	服务接口ServiceInt	<ServiceInt₁，匹配，ServiceInt₂>
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函数实例子网络	函数实例FunctionInst	<FunctionInst₁，必要连接，FunctionInst₂>
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