Nighttime lights reveal substantial spatial heterogeneity and inequality in post-hurricane recovery

• Published in: Remote sensing of environment Vol. 319; p. 114645
• Main Authors: Zheng, Qiming, Zeng, Yiwen, Zhou, Yuyu, Wang, Zhuosen, Mu, Te, Weng, Qihao
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 15.03.2025
• Subjects: algorithms; Black Marble product; environment; FEMA; humans; hurricanes; Inequality; Nighttime light; Post-hurricane recovery; spatial variation; statistics; time series analysis; VIIRS; Nighttime light; VIIRS; Post-hurricane recovery; FEMA; Black Marble product; Inequality
• ISSN: 0034-4257
• DOI: 10.1016/j.rse.2025.114645

While severe hurricanes continue to challenge the resilience of local communities, fine-scale knowledge of post-hurricane recovery remains scarce. Existing recovery tracking approaches mainly rely on aggregated metrics that would disguise the spatial heterogeneity in recovery patterns. Here, we present a spatiotemporally explicit investigation into the recovery of human activity after 10 recent severe hurricanes in the U.S., with daily nighttime light (NTL) time series images from NASA's Black Marble VIIRS NTL product suite. We utilized a Bayesian-based time series change detection model and temporal clustering algorithm to analyze the post-hurricane recovery of each built-up area pixel within 446 counties severely affected by the hurricanes. To investigate the potential inaccuracies stemming from assessments using aggregated statistics, we further compared the recovery pattern estimated at pixel scale with that estimated by aggregated NTL radiance at county and census tract scales. Last, we examined the inequality in post-hurricane recovery and how it related to socioeconomic factors and current hurricane assistance programs. Our analysis shows a 7-fold difference in the recovery duration of hurricane-affected built-up areas within a county, with one-third of the areas experiencing a prolonged recovery lasting over 200 days. We emphasize the necessity of fine-scale knowledge in recovery assessments as aggregated statistics tend to largely underestimate the severity of hurricane impact and spatial heterogeneity of recovery. More importantly, we identify a prevailing recovery inequality across minority and disadvantaged populations, as well as a continued disproportionate allocation of hurricane assistance served as a key driver of exacerbating recovery inequality. Our study offers nuanced insights into the spatial heterogeneity of post-hurricane recovery that can inform strategic and equitable recovery efforts, as well as more effective hurricane relief programs and protocols. •Spatiotemporal pattern of the recovery of 10 recent severe hurricanes was analyzed.•A 7-fold intra-county difference in the recovery duration was observed.•Aggregated metrics tended to underestimate severity and heterogeneity of recovery.•A prevailing recovery inequality biased towards minorities and the disadvantaged.•The unequal allocation of FEMA assistance was a key driver of recovery inequality.