Your browser doesn't support javascript.
loading
Unveiling community adaptations to extreme heat events using mobile phone location data.
Tian, Hao; Cai, Heng; Hu, Leiqiu; Qiang, Yi; Zhou, Bing; Yang, Mingzheng; Lin, Binbin.
Afiliación
  • Tian H; Department of Geography, Texas A&M University, College Station, TX 77840, USA.
  • Cai H; Department of Geography, Texas A&M University, College Station, TX 77840, USA. Electronic address: hengcai@tamu.edu.
  • Hu L; Department of Atmospheric Science, University of Alabama in Huntsville, AL 35899, USA.
  • Qiang Y; School of Geosciences, University of South Florida, Tampa, FL 33620, USA.
  • Zhou B; Department of Geography, Texas A&M University, College Station, TX 77840, USA.
  • Yang M; Department of Geography, Texas A&M University, College Station, TX 77840, USA.
  • Lin B; Department of Geography, Texas A&M University, College Station, TX 77840, USA.
J Environ Manage ; 366: 121665, 2024 Aug.
Article en En | MEDLINE | ID: mdl-39032252
ABSTRACT
The escalating frequency, duration, and intensity of extreme heat events have posed a significant threat to human society in recent decades. Understanding the dynamic patterns of human mobility under extreme heat will contribute to accurately assessing the risk of extreme heat exposure. This study leverages an emerging geospatial data source, anonymous cell phone location data, to investigate how people in different communities adapt travel behaviors responding to extreme heat events. Taking the Greater Houston Metropolitan Area as an example, we develop two indices, the Mobility Disruption Index (MDI) and the Activity Time Shift Index (ATSI), to quantify diurnal mobility changes and activity time shift patterns at the city and intra-urban scales. The results reveal that human mobility decreases significantly in the daytime of extreme heat events in Houston while the proportion of activity after 8 p.m. is increased, accompanied with a delay in travel time in the evening. Moreover, these mobility-decreasing and activity-delaying effects exhibited substantial spatial heterogeneity across census block groups. Causality analysis using the Geographical Convergent Cross Mapping (GCCM) model combined with correlation analyses indicates that people in areas with a high proportion of minorities and poverty are less able to adopt heat adaptation strategies to avoid the risk of heat exposure. These findings highlight the fact that besides the physical aspect of environmental justice on heat exposure, the inequity lies in the population's capacity and knowledge to adapt to extreme heat. This research is the first of the kind that quantifies multi-level mobility for extreme heat responses, and sheds light on a new facade to plan and implement heat mitigations and adaptation strategies beyond the traditional approaches.
Asunto(s)
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Teléfono Celular / Calor Extremo Límite: Humans Idioma: En Revista: J Environ Manage Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Teléfono Celular / Calor Extremo Límite: Humans Idioma: En Revista: J Environ Manage Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido