In the past decade, Japan’s degree of urbanization has leveled off at around 92.04 percent. This means that less than 10 percent of Japan’s population of 126 million inhabitants do not live in an urban setting. Japan is well above the degree of urbanization worldwide, which is 55 percent. Japan is also known for its high population density: In 2017, it amounted to an eye-watering 347.78 inhabitants per square kilometer - however, it is not even among the top twenty countries with the highest population density worldwide. That ranking is lead by Monaco, followed by China, and Singapore. Japan’s aging population The main demographic challenge that Japan currently faces is an aging population, as the number of inhabitants over 65 years old is an increasing percentage of the population. As of 2018, Japan is the country with the largest percentage of total population over 65 years, and life expectancy at birth there is about 84 years. Simultaneously, the birth rate in Japan is declining, resulting in negative population growth in recent years. One method Japan is using to address these demographic shifts is by investing in automated work processes; it's one of the top countries interested in collaborative robots.

The statistic shows the development of the urban and rural population in Japan from 2008 to 2017. In 2017, about 117 million people lived in urban areas of Japan, compared to eleven million people in rural areas.

Japan JP: Urban Population Growth data was reported at 0.248 % in 2017. This records a decrease from the previous number of 0.344 % for 2016. Japan JP: Urban Population Growth data is updated yearly, averaging 0.900 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 4.082 % in 1961 and a record low of 0.248 % in 2017. Japan JP: Urban Population Growth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank: Population and Urbanization Statistics. Urban population refers to people living in urban areas as defined by national statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects.; ; World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2014 Revision.; Weighted average;

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Cities can be tremendously efficient. It is easier to provide water and sanitation to people living closer together, while access to health, education, and other social and cultural services is also much more readily available. However, as cities grow, the cost of meeting basic needs increases, as does the strain on the environment and natural resources. Data on urbanization, traffic and congestion, and air pollution are from the United Nations Population Division, World Health Organization, International Road Federation, World Resources Institute, and other sources.

Japan JP: Access to Electricity: Urban: % of Population data was reported at 100.000 % in 2016. This stayed constant from the previous number of 100.000 % for 2015. Japan JP: Access to Electricity: Urban: % of Population data is updated yearly, averaging 100.000 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 100.000 % in 2016 and a record low of 100.000 % in 2016. Japan JP: Access to Electricity: Urban: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank: Energy Production and Consumption. Access to electricity, urban is the percentage of urban population with access to electricity.; ; World Bank, Sustainable Energy for All (SE4ALL) database from the SE4ALL Global Tracking Framework led jointly by the World Bank, International Energy Agency, and the Energy Sector Management Assistance Program.; Weighted average;

Japan Urban Land Price Index: Biggest 6 City: Residential data was reported at 41.000 31Mar1990=100 in Mar 2002. This records a decrease from the previous number of 42.200 31Mar1990=100 for Sep 2001. Japan Urban Land Price Index: Biggest 6 City: Residential data is updated semiannually, averaging 21.900 31Mar1990=100 from Mar 1955 (Median) to Mar 2002, with 95 observations. The data reached an all-time high of 105.800 31Mar1990=100 in Sep 1990 and a record low of 0.490 31Mar1990=100 in Mar 1955. Japan Urban Land Price Index: Biggest 6 City: Residential data remains active status in CEIC and is reported by Japan Real Estate Institute. The data is categorized under Global Database’s Japan – Table JP.EB017: Urban Land Price Index: 31Mar1990=100.

Until 2007, the share of the global population living in urban areas was always smaller than the rural population, but in 2021, the world's level of urbanization has risen to around 56 percent, and by 2050, it is estimated that two thirds of the world will live in urban areas. Urbanization on such a large scale is a relatively new phenomenon, and has a strong correlation with the industrial maturity of a society. For most of pre-industrial times, fewer than five percent of the total population lived in urban centers, which were generally trading and administrative centers. The main reason for this was the agricultural demands of the time, where subsistence farming was the primary method of food production for the general population. Compared to Japan and China, a larger share of Western Europe lived in urban centers in the 16th century, due to higher levels of trade along the Mediterranean and between northern states, but around 94 percent of the population still lived in a rural setting. Effect of industrialization With the onset of the first industrial revolution in the 19th century, the mechanization of agriculture and development of manufacturing industries saw a shift in labor demands in Western Europe. People began migrating to cities on a large scale, and migration to the U.S. also increased due to industrialization in the northeastern states. Urban populations then became more prosperous, although mortality rates were initially higher due to the more rapid spread of disease and poor sanitation infrastructure. This mortality also disproportionately affected children and more recent arrivals. Global trends Waves of industrialization in Europe saw further urbanization throughout the 1800s, and roughly a third of the population had urbanized by the end of the 19th century. Globally, it would take until the 1960s before one third of the population had urbanized, and it was not until the late 1990s where China's urbanization rate had reached this level. However, China's urbanization rate has grown rapidly since the 1980s, and is now around 80 percent of the EU's level, whereas it was closer to 50 percent just two decades previously. Japan's urbanization rate was comparable to Europe's for most of the 20th century, but increased further throughout the 2010s; today it has one of the highest rates among more developed nations, although this has presented some challenges for Japanese society.

Forecast: Population in Urban Agglomerations of More Than 1 Million in Japan 2024 - 2028 Discover more data with ReportLinker!

Japan Urban Land Price Index: OB: Industrial data was reported at 83.400 31Mar1990=100 in Mar 2002. This records a decrease from the previous number of 85.700 31Mar1990=100 for Sep 2001. Japan Urban Land Price Index: OB: Industrial data is updated semiannually, averaging 58.000 31Mar1990=100 from Mar 1955 (Median) to Mar 2002, with 95 observations. The data reached an all-time high of 111.100 31Mar1990=100 in Sep 1991 and a record low of 2.040 31Mar1990=100 in Mar 1955. Japan Urban Land Price Index: OB: Industrial data remains active status in CEIC and is reported by Japan Real Estate Institute. The data is categorized under Global Database’s Japan – Table JP.EB017: Urban Land Price Index: 31Mar1990=100.

Forecast: Volume of Urban Wastewater Discharged After Treatment in Japan 2023 - 2027 Discover more data with ReportLinker!

n online questionnaire survey was conducted for people of various attributes who live in multiple places in Japan. Data of respondents’ U-turn motivations, willingness of settlement in current residentce, and evaluations of living environments.

Japan Urban Land Price Index: NC: Tokyo Toka: Residential data was reported at 48.900 31Mar1990=100 in Mar 2002. This records a decrease from the previous number of 50.500 31Mar1990=100 for Sep 2001. Japan Urban Land Price Index: NC: Tokyo Toka: Residential data is updated semiannually, averaging 67.600 31Mar1990=100 from Mar 1985 (Median) to Mar 2002, with 35 observations. The data reached an all-time high of 126.000 31Mar1990=100 in Sep 1987 and a record low of 41.800 31Mar1990=100 in Mar 1985. Japan Urban Land Price Index: NC: Tokyo Toka: Residential data remains active status in CEIC and is reported by Japan Real Estate Institute. The data is categorized under Global Database’s Japan – Table JP.EB016: Urban Land Price Index: 31Mar1990=100.

Urban search and rescue teams as of 17th March 2011

This scatter chart displays urban population (people) against access to electricity (% of population) and is filtered where the country is Japan. The data is about countries per year.

As of July 2020, 542 municipalities in Japan had plans for location optimization, representing roughly one-third of all municipalities. While 203 were preparing plans for site optimization, 339 had already announced concrete plans. In the light of the population decline in Japan, location optimization aims to achieve urban restructuring, creating compact cities connected to public transportation networks that are sustainable and ensure access to essential services.

This dataset provides detailed information on road surfaces from OpenStreetMap (OSM) data, distinguishing between paved and unpaved surfaces across the region. This information is based on road surface prediction derived from hybrid deep learning approach. For more information on Methods, refer to the paper

Roughly 2.3432 million km of roads are mapped in OSM in this region. Based on AI-mapped estimates the share of paved and unpaved roads is approximately 0.4029 and 0.0294 (in million kms), corressponding to 17.1957% and 1.2527% respectively of the total road length in the dataset region. 1.911 million km or 81.5516% of road surface information is missing in OSM. In order to fill this gap, Mapillary derived road surface dataset provides an additional 0.0405 million km of information (corressponding to 2.1189% of total missing information on road surface)

It is intended for use in transportation planning, infrastructure analysis, climate emissions and geographic information system (GIS) applications.

This dataset provides comprehensive information on road and urban area features, including location, surface quality, and classification metadata. This dataset includes attributes from OpenStreetMap (OSM) data, AI predictions for road surface, and urban classifications.

AI features:

• pred_class: Model-predicted class for the road surface, with values "paved" or "unpaved."

• pred_label: Binary label associated with pred_class (0 = paved, 1 = unpaved).

• osm_surface_class: Classification of the surface type from OSM, categorized as "paved" or "unpaved."

• combined_surface_osm_priority: Surface classification combining pred_label and surface(OSM) while prioritizing the OSM surface tag, classified as "paved" or "unpaved."

• combined_surface_DL_priority: Surface classification combining pred_label and surface(OSM) while prioritizing DL prediction pred_label, classified as "paved" or "unpaved."

• n_of_predictions_used: Number of predictions used for the feature length estimation.

• predicted_length: Predicted length based on the DL model’s estimations, in meters.

• DL_mean_timestamp: Mean timestamp of the predictions used, for comparison.

OSM features may have these attributes(Learn what tags mean here):

• name: Name of the feature, if available in OSM.

• name:en: Name of the feature in English, if available in OSM.

• name:* (in local language): Name of the feature in the local official language, where available.

• highway: Road classification based on OSM tags (e.g., residential, motorway, footway).

• surface: Description of the surface material of the road (e.g., asphalt, gravel, dirt).

• smoothness: Assessment of surface smoothness (e.g., excellent, good, intermediate, bad).

• width: Width of the road, where available.

• lanes: Number of lanes on the road.

• oneway: Indicates if the road is one-way (yes or no).

• bridge: Specifies if the feature is a bridge (yes or no).

• layer: Indicates the layer of the feature in cases where multiple features are stacked (e.g., bridges, tunnels).

• source: Source of the data, indicating the origin or authority of specific attributes.

Urban classification features may have these attributes:

• continent: The continent where the data point is located (e.g., Europe, Asia).

• country_iso_a2: The ISO Alpha-2 code representing the country (e.g., "US" for the United States).

• urban: Binary indicator for urban areas based on the GHSU Urban Layer 2019. (0 = rural, 1 = urban)

• urban_area: Name of the urban area or city where the data point is located.

• osm_id: Unique identifier assigned by OpenStreetMap (OSM) to each feature.

• osm_type: Type of OSM element (e.g., node, way, relation).

The data originates from OpenStreetMap (OSM) and is augmented with model predictions using images downloaded from Mapillary in combination with the GHSU Global Human Settlement Urban Layer 2019 and AFRICAPOLIS2020 urban layer.

This dataset is one of many HeiGIT exports on HDX. See the HeiGIT website for more information.

We are looking forward to hearing about your use-case! Feel free to reach out to us and tell us about your research at communications@heigit.org – we would be happy to amplify your work.

With approximately 9.57 million inhabitants, Tokyo was Japan's most populous city as of 2023, followed by Yokohama, which, in the same year, counted about 3.75 million inhabitants. In total, there were twelve cities with a population of over one million people in Japan.

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This horizontal bar chart displays urban population (people) by country full name and is filtered where the country is Japan. The data is about countries per year.

This study explored the relationship between community participation/community attachment and subjective well-being (SWB) among Japanese older adults. The study was conducted in Japanese urban (Tokyo and Osaka) and rural (Shikoku region) areas. Structural equation modelling was performed to assess the potential relationship between community participation, community attachment and SWB. Results showed that community participation and community attachment were positively associated in both areas. However, community attachment had a significant impact on SWB only in rural areas with little impact on increasing SWB in urban areas. We conclude that the role of community attachment varies according to regions with different socioeconomic properties. These findings contribute to the design of detailed region-specific initiatives to improve SWB of older adults.