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Using data derived from cellular phone locations to estimate visitation to natural areas: An application to water recreation in New England, USA

机译:使用从蜂窝电话地点衍生的数据来估计自然区域的访问:美国新英格兰娱乐的应用

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We introduce and validate the use of commercially available human mobility datasets based on cell phone locations to estimate visitation to natural areas. By combining this data with on-the-ground observations of visitation to water recreation areas in New England, we fit a model to estimate daily visitation for four months to more than 500 sites. The results show the potential for this new big data source of human mobility to overcome limitations in traditional methods of estimating visitation and to provide consistent information at policy-relevant scales. However, the data providers’ opaque and rapidly developing methods for processing locational information required a calibration and validation against data collected by traditional means to confidently reproduce the desired estimates of visitation. We found that with this calibration, the high-resolution information in both space and time provided by cell phone location-derived data creates opportunities for developing next-generation models of human interactions with the natural environment.
机译:我们介绍并验证基于手机位置的市售人类移动数据集的使用,以估算自然区域的访问。通过将这些数据与地面对新英格兰的水娱乐区的娱乐区相结合,我们拟合模型来估计每日探索四个月到500多个地点。结果表明,这种新的大数据来源的潜在人类流动源,以克服传统估算探索方法的限制,并在政策相关规模提供一致的信息。然而,数据提供商的不透明和用于处理位置信息的快速发展方法需要校准和验证通过传统方法收集的数据来自信地再现所需的探索估计。我们发现,通过这种校准,通过手机位置衍生数据提供的空间和时间的高分辨率信息会为开发与自然环境的下一代人类交互模型产生机会。

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