Reading Time: < 1 minute過去20年以上、日本では他地域から東京圏への転入者数を、転出者数が毎年平均10万人を上回ってきました。継続的な首都地域への国内純流入として、OECD諸国の中でも最大規模の例です。また、2000年以降、東京圏以外のほとんどの道府県で人口減少が進んでいます。そして、若者、特に若い女性が、より多くの機会を求めて地方都市から大都市圏へと移り住んでいます。
Tag: cities
Les smart cities ne suffisent plus : les villes ont besoin de systèmes de résilience
Reading Time: 4 minutesDepuis des années, les villes investissent dans des capteurs intelligents, des tableaux de bord et des services numériques. Mais alors que les chocs se propagent en cascade à travers les systèmes d’eau, d’énergie, de transport et les systèmes sociaux, les villes intelligentes ne suffisent plus. Que faudra-t-il pour transformer les infrastructures intelligentes en une résilience réelle?
Beyond Tokyo: Can Japan boost the appeal of its regions?
Reading Time: 4 minutesRegions and cities are being reshaped by falling birth rates, ageing populations and the continued movement of young people to large metropolitan hubs. Japan knows this story well: for more than two decades, over 100,000 people a year have moved to the Tokyo metropolitan area from elsewhere in Japan. The question is no longer how to strengthen Tokyo, but how to strengthen everywhere else?
Smart Cities Are Not Enough: Cities Need Resilience Systems
Reading Time: 3 minutesFor years, cities have invested in smart sensors, dashboards and digital services. But as shocks cascade across water, energy, transport and social systems, smart cities aren’t enough. What will it take to turn smart infrastructure into real resilience?
From World Cup excitement to lasting local benefits: what can cities learn?
Reading Time: 4 minutesOn June 11, Mark Carney opened the 2026 men’s FIFA World Cup with a message of pride and ambition. Two weeks later, that ambition became history: how can countries turn global attention into lasting local benefits?
From rainfall to response: how data guided recovery in Maipú
Reading Time: 4 minutesOn Saturday, 31 January 2026, a single cloud changed Maipú in less than an hour – 17 millimetres of rainfall in forty-five minutes, flooding streets and destroying homes. Images spread across social media. Many claimed they were fake. They were not. The storm devastated more than a thousand families. So how did Maipú use real-time data to reach those in need?
De las lluvias a la respuesta: cómo los datos guiaron la recuperación en Maipú
Reading Time: 4 minutesEl sábado 31 de enero de 2026, una sola nube transformó Maipú en menos de una hora – 17 milímetros de lluvia en cuarenta y cinco minutos, inundando calles y destruyendo viviendas. Las imágenes se difundieron por las redes sociales. Muchos afirmaron que eran falsas. No lo eran. La tormenta devastó a más de mil familias. ¿Cómo usó Maipú los datos en tiempo real para llegar a quienes lo necesitaban?
Can cities work better for women?
Reading Time: 3 minutesWomen’s movements are often more fragmented due to unpaid caregiving, a pattern known as “trip chaining”, yet cities remain organised around linear home-to-work commutes. If care shapes the everyday reality of so many people, why are our cities still not designed around them?