University of Florida, Department of Civil and Coastal Engineering, Gainesville, Florida, 32611, USA.
Massey University, School of Built Environment, Auckland, 0632, New Zealand.
Sci Data. 2022 Oct 7;9(1):608. doi: 10.1038/s41597-022-01731-6.
As the threat of wildfire increases, it is imperative to enhance the understanding of household evacuation behavior and movements. Mobile GPS data provide a unique opportunity for studying evacuation routing behavior with high ecological validity, but there are little publicly available data. We generated a highway vehicle routing dataset derived from GPS trajectories generated by mobile devices (e.g., smartphones) in Sonoma County, California during the 2019 Kincade Fire that started on October 23, 2019. This dataset contains 21,160 highway vehicle routing records within Sonoma County from October 16, 2019 to November 13, 2019. The quality of the dataset is validated by checking trajectories and average travel speeds. The potential use of this dataset lies in analyzing and modeling evacuee route choice behavior, estimating traffic conditions during the evacuation, and validating wildfire evacuation simulation models.
随着野火威胁的增加，提高对家庭疏散行为和动向的理解至关重要。移动 GPS 数据为研究疏散路径行为提供了一个具有高度生态有效性的独特机会，但公开可用的数据很少。我们生成了一个高速公路车辆行驶路线数据集，该数据集源自加利福尼亚州索诺玛县在 2019 年 10 月 23 日爆发的金凯德火灾期间移动设备（例如智能手机）生成的 GPS 轨迹。该数据集包含 2019 年 10 月 16 日至 11 月 13 日期间在索诺玛县内的 21160 条高速公路车辆行驶路线记录。通过检查轨迹和平均行驶速度来验证数据集的质量。该数据集的潜在用途在于分析和建模疏散者的路线选择行为、估计疏散期间的交通状况以及验证野火疏散模拟模型。
