A New Lens on Homelessness: Daily Tent Monitoring with 311 Calls and Street Images

TL;DR

This paper introduces a novel method for monitoring homelessness by leveraging 311 service calls and street images to provide timely, detailed, and cost-effective data on tent trends in San Francisco, surpassing traditional counts.

Contribution

It presents a new predictive model that uses crowdsourced data to track daily and neighborhood-level tent fluctuations, offering more granular insights into homelessness patterns.

Findings

Captures rapid tent fluctuations during COVID-19

Identifies spatial shifts in tent locations

Provides timely, localized homelessness data

Abstract

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.