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Unmanned aerial vehicles (UAVs) in behavior mapping: A case study of neighborhood parks

机译:行为测绘的无人驾驶飞行器(无人机):邻里公园的案例研究

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摘要

Behavior mapping is an effective tool for the direct observation of the interaction between people and places. However, current approaches have shortcomings that introduce location inaccuracies and hinder micro-context recording of observed activities. This study explores the applicability of unmanned aerial vehicles (UAVs) in behavior mapping. First, we suggest a protocol for the use of UAVs in behavior mapping. Then, as a case study, we explore neighborhood park uses using the behavior maps and quantitative information collected from 30 neighborhood parks in Salt Lake County, UT, USA. Inter-rater reliability tests of identifying user attributes (e.g., gender, age group, activity level) and geocoding produced high Kappa statistics and location precision. The case study results show different park usage by sex, age groups, and activity types across different times. For example, we observed only a few seniors and more males than females, a gap that becomes larger among children and teenage groups. User density was higher in picnic areas and playgrounds and lower in lawns, baseball fields, and water features.
机译:行为映射是直接观察人与地点之间互动的有效工具。然而,目前的方法具有引入位置不准确的缺点并阻碍观察到的活动的微观上容记录。本研究探讨了无人机(无人机)在行为映射中的适用性。首先,我们建议在行为映射中使用无人机的协议。然后,作为一个案例研究,我们探索邻里公园使用来自美国盐湖县的30个邻域公园所收集的行为地图和定量信息。识别用户属性的帧间间可靠性测试(例如,性别,年龄组,活动水平)和地理编码产生了高kappa统计和位置精度。案例研究结果显示不同时间的性别,年龄组和活动类型的不同公园使用情况。例如,我们只观察到少数老年人和更多的男性,而不是女性,在儿童和青少年群体中变得更大的差距。野餐区和操场上的用户密度较高,草坪,棒球场和水分特征较低。

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