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基于城市知识体系的公共数据要素构建方法 被引量:2
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作者 郑宇 易修文 +1 位作者 齐德康 潘哲逸 《大数据》 2024年第4期130-148,共19页
数据要素是数字经济发展的核心动能。城市公共数据的基础良好、普适性强、应用场景丰富,成为政府主导的数据要素的首选。当前数据与应用耦合,不同应用之间共享数据难,人工数据治理过程滞后、繁重低效,仅依靠自动抽取技术无法保证数据要... 数据要素是数字经济发展的核心动能。城市公共数据的基础良好、普适性强、应用场景丰富,成为政府主导的数据要素的首选。当前数据与应用耦合,不同应用之间共享数据难,人工数据治理过程滞后、繁重低效,仅依靠自动抽取技术无法保证数据要素的精度。为此,基于人机智能协同的总体思路,提出基于城市知识体系的数据要素构建方法。首先,对大量城市业务进行解构和抽象,构建以人、地、事、物、组织5类实体,实体间关系及实体属性为核心的城市知识体系,并以这些实体、关系和属性为数据要素的原子描述,向上组合表达各种城市业务,向下形成可标准化的数据资源体系。其次,研发一套数字化控件,承载基于城市知识体系的数据要素化理论,通过灵活配置的方式开发服务于市民的各类应用,使数据在产生时就与城市知识体系关联,自动形成数据要素。最后,构建智能学习和推荐算法,更好地连接数字化控件和城市知识体系,使应用配置人员无须学习城市知识体系就能顺畅地使用数字化控件,降低了工具的使用门槛。该方法可大大提高公共数据要素产生的效率和扩大公共数据要素的规模,释放公共数据要素的价值。 展开更多
关键词 数据要素 数据资源体系 城市计算 城市知识体系
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Spatial Patterns of LULC and Driving Forces in the Transnational Area of Tumen River:A Comparative Analysis of the Sub-regions of China,the DPRK,and Russia 被引量:2
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作者 NAN Ying WANG Bingbing +3 位作者 ZHANG Da LIU Zhifeng qi dekang ZHOU Haohao 《Chinese Geographical Science》 SCIE CSCD 2020年第4期588-599,共12页
Understanding the spatial patterns of land-use and land-cover(LULC)and their driving forces in transnational areas is important for the sustainable development of these regions.However,the spatial patterns of LULC and... Understanding the spatial patterns of land-use and land-cover(LULC)and their driving forces in transnational areas is important for the sustainable development of these regions.However,the spatial patterns of LULC and their driving forces across multiple scales are poorly understood in transnational areas.In this study,we analyzed the spatial patterns of LULC and driving forces in the transnational area of Tumen River(TATR)in 2016 across two scales:the entire region and the sub-regions of China,the Democratic People’s Republic of Korea(DPRK),and Russia.Results showed that the LULC was dominated by broadleaf forest and dry farmland in the TATR in 2016,which accounted for 66.86%and 13.60%of the entire region,respectively.Meanwhile,the LULC in the three sub-regions exhibited noticeable differences.In the Chinese and the DPRK’s sub-regions,the area of broadleaf forest was greater than those for the other LULC types,while the Russian sub-region was dominated by broadleaf forest and grassland.The spatial patterns of LULC were mainly influenced by topography,climate,soil properties,and human activities.In addition,the driving forces of the spatial patterns of LULC in the TATR had an obvious scaling effect.Therefore,we suggest that effective policies and regulations with cooperation among China,the DPRK,and Russia are needed to plan the spatial patterns of LULC and improve the sustainable development of the TATR. 展开更多
关键词 land-use and land-cover(LULC) spatial pattern driving force transnational area of Tumen River
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