用311热线和街景图监测旧金山无家可归者帐篷分布，实现每日更新。
A New Lens on Homelessness: Daily Tent Monitoring with 311 Calls and Street Images
- 结合311市民热线与街景图像数据，构建每日监测模型。
- 发现疫情期间帐篷数量快速波动及位置动态迁移规律。
- 为政策制定提供及时、低成本、精细化的决策支持。
美国无家可归问题已升至大萧条以来最高水平。然而，现有的点位计数（PIT）方法在频率、一致性与空间精度上存在局限。本研究提出一种新方法，利用公开的众包数据——311服务呼叫记录与街景影像，追踪并预测旧金山地区无家可归者帐篷的动态变化。所构建的预测模型能够捕捉到日级与街区级的细微差异，揭示传统计数常忽略的模式，如新冠疫情时期的快速波动及帐篷位置随时间的空间迁移。该方法提供更及时、局部化且成本较低的信息，有助于指导应对政策并评估减少露天无家可归现象的干预措施效果。
原文摘要 · Abstract (English)
Homelessness in the United States has surged to levels unseen since the Great Depression. However, existing methods for monitoring it, such as point-in-time (PIT) counts, have limitations in terms of frequency, consistency, and spatial detail. This study proposes a new approach using publicly available, crowdsourced data, specifically 311 Service Calls and street-level imagery, to track and forecast homeless tent trends in San Francisco. Our predictive model captures fine-grained daily and neighborhood-level variations, uncovering patterns that traditional counts often overlook, such as rapid fluctuations during the COVID-19 pandemic and spatial shifts in tent locations over time. By providing more timely, localized, and cost-effective information, this approach serves as a valuable tool for guiding policy responses and evaluating interventions aimed at reducing unsheltered homelessness.
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