Spatio-temporal object-based Geo-AI modeling and application to bus route planning

doi:10.13474/j.cnki.11-2246.2025.1004

Abstract

Abstract: Multi-granularity spatio-temporal objects, as the basic data model of the pan-spatial information system, have special advantages in performing spatial data materialization modeling.Based on the cognitive and behavioral ability characteristics of the spatio-temporal object model, the construction and application of Geo-AI has become a research direction that urgently needs to be broken through in the field.On the basis of completing the basic theoretical analysis of Geo-AI and multi-granularity spatio-temporal object model, combining with the basic principle of ant colony algorithm, a Geo-AI group intelligence model based on spatio-temporal object data and applied to bus route planning is constructed, and experiments and applications are carried out in conjunction with practical cases.The results show that combining spatio-temporal object models with artificial intelligence algorithms enables Geo-AI modeling and applications directly based on GIS, and provides advantages in computation, simulation and real-time interaction for spatial planning problems.

Key words: multi-granularity spatio-temporal objects, Geo-AI, ant colony algorithm, route planning

CLC Number:

P208

DU Ying, DENG Guochen, WEI Yuanyuan. Spatio-temporal object-based Geo-AI modeling and application to bus route planning[J]. Bulletin of Surveying and Mapping, 2025, 0(10): 20-25.

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