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A Novel Algorithm to Enrich Geographical Information Systems with Hybrid Data for Better Informed Decisions
Arabian Journal for Science and Engineering ( IF 2.9 ) Pub Date : 2021-06-08 , DOI: 10.1007/s13369-021-05802-5
Omar Aboulola , Basma Alharbi , Ala’ Eshmawi , Mashael Khayyat , Nahla Aljojo , Areej Alshutayri

Land use and census data are of a significant value to urban planners, decision-makers, and investors. Important decisions are made based upon historical data, i.e, inductive reasoning. Such data become increasingly valuable at a fine-grain level to decision-makers in businesses where audience segmentation is needed. In rapidly developing countries, land use and census data are widely available at a coarse-grain level. However, accurate fine-grain mapping of such data is a very challenging task. In this paper, we propose a hierarchical methodology that enriches Geographical Information Systems (GIS) by utilizing existing datasources, rule-based algorithms, and workers (mechanical turks) to identify and map socioeconomic data at a fine-grain level. The proposed methodology was tested and evaluated on multiple cities in Saudi Arabia, with an overall accuracy of 90%. The output of this work, a GIS enriched with socioeconomic data and population count, is of high importance to decision makers and can be utilized in different problems to help make a better informed decision.



中文翻译:

一种用混合数据丰富地理信息系统以做出更明智决策的新算法

土地利用和人口普查数据对城市规划者、决策者和投资者具有重要价值。重要的决定是根据历史数据做出的,即归纳推理。对于需要细分受众的企业中的决策者而言,此类数据在细粒度级别变得越来越有价值。在快速发展的国家,粗粮级的土地利用和普查数据广泛可用。然而,对此类数据进行精确的细粒度映射是一项非常具有挑战性的任务。在本文中,我们提出了一种分层方法,该方法通过利用现有数据源、基于规则的算法和工人(机械土耳其人)在细粒度级别识别和绘制社会经济数据来丰富地理信息系统 (GIS)。提议的方法在沙特阿拉伯的多个城市进行了测试和评估,总体准确率为 90%。这项工作的输出是一个富含社会经济数据和人口计数的 GIS,对决策者非常重要,可用于解决不同的问题,以帮助做出更明智的决策。

更新日期:2021-06-09
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