
Cities, Год журнала: 2025, Номер 162, С. 105894 - 105894
Опубликована: Март 31, 2025
Язык: Английский
Cities, Год журнала: 2025, Номер 162, С. 105894 - 105894
Опубликована: Март 31, 2025
Язык: Английский
Transportation Research Interdisciplinary Perspectives, Год журнала: 2025, Номер 31, С. 101395 - 101395
Опубликована: Март 22, 2025
Язык: Английский
Процитировано
0Population Space and Place, Год журнала: 2025, Номер 31(3)
Опубликована: Март 23, 2025
ABSTRACT Assessing populations exposed to climate change impacts traditionally relies upon census data estimations. Yet, these only provide a static picture of risk since censuses are often undertaken and released over long periods thus cannot be updated regularly. In this study, we investigate how leverage multi‐temporal geolocated social media from Meta‐Facebook assess spatio‐temporal variations population exposure vulnerability climate‐related risks. Building advanced spatial analytical methods, address the selection bias datasets further analyse varies daily, weekly, seasonally during 4‐month typhoon‐free period in Philippines 2021. Results show changes density combined with varying levels can increase size hazard events at specific places, even scenarios where movements constrained. When comparing daytime nighttime exposure, less vulnerable areas presented decrease density, while higher showed increase. An opposite trend, however, was observed weekend holiday periods, an areas. While limitations remain regarding study representativeness data, our findings contribute guiding disaster reduction strategies support climate‐resilient pathways complementarity traditional sources field‐based practices.
Язык: Английский
Процитировано
0Population Space and Place, Год журнала: 2025, Номер 31(3)
Опубликована: Март 23, 2025
ABSTRACT This paper aims to enrich the current literature on study of migratory movements in context COVID‐19 and post‐pandemic period. While most studies this topic measure migration using official registers, we propose a new methodology based leverage mobile phone network data, taken from Madrid region, as case study. use such data are common other fields, transport mobility planning, demonstrate their usefulness migration. Analysing Madrid, find evidence changes trends during COVID‐19, increased immigration into rural outer suburban areas emigration core urban areas. A geographical description is provided different scales (from national metropolitan municipal scale, including small transportation zones), by socioeconomic group. In addition, provide some ideas about these context, evolution varies for groups.
Язык: Английский
Процитировано
0Scientific Data, Год журнала: 2025, Номер 12(1)
Опубликована: Март 24, 2025
Abstract Student mobility is a distinct form of human movement. It can indicate the characteristics and attractiveness regions, which relevant for governance, policy, planning. In Europe, Erasmus+ programme has facilitated over two million students between 2014 2022, this individual-level data openly available. However, lack spatial information hinders its use in geographical research. article, we present enriched student by adding at Local Administrative Unit (LAU) Nomenclature Territorial Units Statistics (NUTS) 3 regional levels. Using Photon geocoding service, converted textual origin destination locations into data, creating precise annual-level dataset. The geolocated dataset contains both individual- aggregate-level flows LAU NUTS units across Europe from to 2022. We validated through random sampling manual verification, achieving accuracy scores above 96%. Finally, provide cases data.
Язык: Английский
Процитировано
0Cities, Год журнала: 2025, Номер 162, С. 105894 - 105894
Опубликована: Март 31, 2025
Язык: Английский
Процитировано
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