[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-5016":3,"related-5016":59},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":18,"tags":20,"primary_topic":9,"secondary_topics":25,"classification":26,"search_phrases":41,"slug":44,"view_count":15,"doi":45,"paper":46,"created_at":58},5016,"Метод формування інформаційної бази для планування добровільних рятувальних формувань на основі відкритих геопросторових даних","https:\u002F\u002Fdoi.org\u002F10.15276\u002Fict.03.2026.65","The article develops a method for forming an information base for planning volunteer rescue formations using open geospatial data.The relevance of the study is determined by the need to provide decision-support systems with structured, spatially consistent, and analytically suitable data on settlements, road networks, buildings, and infrastructure objects within territorial communities.The study aims to develop a method that enables automated collection, verification, preprocessing, integration, aggregation, and structuring of open geospatial data for further use in planning volunteer rescue formations.The proposed method includes identification of the study area, acquisition of data from an open mapping environment, selection of target spatial objects, data quality checking and cleaning, spatial integration, aggregation of territorial characteristics, and formation of a structured feature matrix with associated metadata.To implement the method, software code was developed in Python in a cloud-based computing environment using specialized libraries for geospatial data processing, tabular data management, and visualization.The method was experimentally tested using a territorial community in Volyn Oblast as a case study.As a result, an information base was formed containing spatially consistent characteristics of settlements, road networks, buildings, and infrastructure objects.Experimental verification confirmed the operability of the proposed method according to spatial, structural, and logical criteria.The practical value of the study l ies in creating a reproducible information basis for further assessment and prediction of rescue-service accessibility and for decision support in planning volunteer rescue formations.Further research should focus on integrating additional official and departmental data sources and using the formed information base in models for accessibility prediction and rational location of rescue formations.","本文提出了一种利用开放地理空间数据构建志愿救援队伍规划信息库的方法。该研究的现实意义在于，决策支持系统需要获得关于领土社区内居民点、道路网络、建筑物和基础设施对象的结构化、空间一致且适合分析的数据。研究旨在开发一种方法，能够自动采集、验证、预处理、集成、聚合和结构化开放地理空间数据，以供志愿救援队伍规划进一步使用。所提方法包括确定研究区域、从开放制图环境获取数据、选择目标空间对象、数据质量检查与清洗、空间集成、领土特征聚合，以及构建带有相关元数据的结构化特征矩阵。为实施该方法，在云计算环境中使用Python开发了软件代码，并调用了用于地理空间数据处理、表格数据管理和可视化的专业库。该方法以沃伦州某领土社区为案例进行了实验测试。结果形成了一个信息库，包含居民点、道路网络、建筑物和基础设施对象在空间上一致的特征。实验验证按照空间、结构和逻辑标准确认了所提方法的可操作性。该研究的实践价值在于为后续评估和预测救援服务可达性以及为志愿救援队伍规划提供决策支持创建了可复现的信息基础。进一步研究应侧重于整合更多官方和部门数据源，并将所形成的信息库用于可达性预测和救援队伍合理布局的模型中。",null,"Ìnformatika, kulʹtura, tehnìka.","2026-10-13T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"该论文聚焦开放地理空间数据支持志愿救援队伍规划，属应急管理与地理信息领域，与三农、农业信息化、智慧农业无关，不建议进入每日精选。",[19],{"name":10,"url":6},[21,22,23,24],"地理空间数据","志愿救援","应急规划","开放数据",[],{"status":27,"locked":14,"version":28,"method":29,"evidence":30},"needs_review","2026-10-22.2","rules",{"candidates":31,"agricultural_evidence":14,"reason":40},[32],{"code":33,"score":34,"supported":35,"title":36,"abstract":37,"tags":39},"I2",3,true,[],[38],"decision support",[],"农业相关性需要复核",[42,43],"Волинська область геопросторові дані","добровільні рятувальні формування","Волинськаобластьгеопросторовідані-5016","10.15276\u002Fict.03.2026.65",{"doi":45,"openalex_id":47,"authors":48,"venue":10,"cited_by_count":15,"oa_url":49,"card":50,"direction":56,"ingested_from":57},"W7221656257",[],"https:\u002F\u002Fict.od.ua\u002Findex.php\u002Fjournal\u002Fuk\u002Farticle\u002Fdownload\u002F178\u002F174\u002F588",{"tldr":51,"method":52,"finding":53,"direction":54,"opportunity":55},"提出利用开放地理空间数据自动构建志愿救援队规划信息库的方法。","Python云环境与地理空间库，采集清洗整合开放地图数据。","在乌克兰一社区验证方法可行，形成空间一致的特征矩阵。","数字乡村与农业信息化","可延伸至乡村应急服务可达性预测与救援队选址优化模型研究。","农业人工智能与决策模型","openalex","2026-10-15T23:30:49.541584Z",{"total":15,"page":60,"page_size":60,"items":61},1,[]]