地理与地理信息科学

针对大气污染执法存在数据资源难以整合集成、违法认定和处罚决定不一致、案件难以实现全程追溯等问题，提出顾及时空特征的大气污染执法事理图谱构建方法。首先，以大气污染执法事件为核心，提出大气污染执法事件本体表示模型，自上而下系统梳理大气污染执法事件知识体系，构建大气污染执法事件本体；在此基础上，提出大气污染执法事理图谱案例知识自动化抽取和存储方法，并以某燃气锅炉超标排放执法案件为例，开展大气污染执法事理图谱构建实践，结果展现了大气污染执法事件的时空变化特征和逻辑演化规律，弥补了事理图谱研究中较少关注事件间时空演变关系这一不足，可助推事理图谱构建发展，促进大气污染执法数据资源整合与共享、智能辅助裁定以及案件全程关联和跟踪监督。

Focusing on the problems of difficult integration of data resources, inconsistency in illegal identification and penalty decisions, and difficulty in achieving full traceability of cases in air pollution law enforcement, the construction method of air pollution law enforcement event logic graph base on spatiotemporal features was proposed.Firstly, taking air pollution law enforcement events as the core, an ontology representation model of air pollution law enforcement events was proposed, the knowledge system of air pollution events was summarized from top and bottom, and the ontology of air pollution law enforcement events was constructed.Secondly, the automatic extraction and storage methods for case knowledge of air pollution law enforcement event logic graph were proposed.In the end, taking the case of excessive emission of gas boiler operated by a thermal company as example, the construction practice of air pollution law enforcement event logic graph was carried out.The result reveals spatiotemporal features and logic evolution law in air pollution law enforcement event, and makes up for the lack of paying less attention to the spatiotemporal evolution relationship between events in the study of event logic graph.The research can help the construction and development of event logic graph, promote the integration and sharing of data resources in different stages of air pollution law enforcement, intelligent assistance adjudication of air pollution law enforcement, and the whole process correlation, tracking and supervision of air pollution law enforcement cases.