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Guide for Seasonal Adjustment and Crowdsourced Data Scaling.
| 题名： | Guide for Seasonal Adjustment and Crowdsourced Data Scaling. |
| 作者： | Dadashova, B.; Griffin, G.; Das, S.; Turner, S.; Graham, M. |
| 关键词： | Pedestrian, Bicyclist, Gps(Geographical positioning system), Count, Data, Seasonal adjustment factors, Crowdsourced data scaling, Texas Department of Transportation (TxDOT) |
| 摘要： | This guide describes two different adjustment processes that can be used with pedestrian and bicyclist data. The first adjustment process is seasonal adjustment, which is applied to short-duration counts that are collected during a specific month of the year. Seasonal adjustment annualizes the short-duration counts, such that the resulting adjusted count value is a better estimate of the annual average daily traffic. This guide provides monthly adjustment factors for both pedestrian and bicyclist count data, which is recommended for use with all short-duration count data that include at least seven days of data. The second adjustment process described in this guide is crowdsourced data scaling, which is applied to crowdsourced bicyclist data samples that are collected from GPS-enabled smartphones. Because the crowdsourced data represent only a sample of the total bicyclists, the number of samples must be scaled or expanded to estimate the total number of bicyclists. This guide describes a simple scaling process that estimates average annual daily bicyclists using the number of crowdsourced data samples, the functional class of the bicyclist travel facility, and the density of high-income households near the bicyclist travel facility. |
| 报告类型： | 科技报告 |
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