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Assessing spatial and attribute errors in large national datasets for population distribution models: a case study of Philadelphia county schools

机译:在人口分布模型的大型国家数据集中评估空间和属性误差:以费城县学校为例

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摘要

Geospatial technologies and digital data have developed and disseminated rapidly in conjunction with increasing computing efficiency and Internet availability. The ability to store and transmit large datasets has encouraged the development of national infrastructure datasets in geospatial formats. National datasets are used by numerous agencies for analysis and modeling purposes because these datasets are standardized and considered to be of acceptable accuracy for national scale applications. At Oak Ridge National Laboratory a population model has been developed that incorporates national schools data as one of the model inputs. This paper evaluates spatial and attribute inaccuracies present within two national school datasets, Tele Atlas North America and National Center of Education Statistics (NCES).
机译:随着计算效率和互联网可用性的提高,地理空间技术和数字数据已得到迅速发展和传播。存储和传输大型数据集的能力鼓励以地理空间格式开发国家基础设施数据集。许多机构将国家数据集用于分析和建模目的,因为这些数据集已标准化,并被认为对于国家规模的应用具有可接受的准确性。在橡树岭国家实验室,已经开发了人口模型,该模型将国立学校的数据作为模型输入之一。本文评估了北美国家电视地图集和美国国家教育统计中心(NCES)这两个国家学校数据集中存在的空间和属性误差。

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