The graph shows the proportion of the population in cities worldwide from 1985 to 2050. **** percent of the world's population lived in cities in the year of 2015. This percentage is forecasted to grow to **** percent in the year 2050.

This dataset includes 2019 estimates and 2035 and 2050 projections approximated to city limits for select cities. It is provided as a convenient summary of NCTCOG 2050 Forecast data, having stated limitations. For more information, see NCTCOG 2050 Forecast Methodology.pdf and Data Dictionary 2050 Forecast (city).pdf.

Climate change is a major concern for governments and institutions worldwide, as is evident from the signing of the Paris Agreement in 2016, where most countries agreed to make efforts to achieve different climate-related goals. The evidence of climate change has been established, as extreme natural events occur more frequently and temperatures increase worldwide. A forecast for 2050 indicates that the temperature of the warmest month in Madrid would increase by 6.4 degrees Celsius, making it comparable to the temperatures of Marrakesh, Morocco.

This dataset provides information about the number of properties, residents, and average property values for 2050 cross streets in Cedar City, UT.

This database represents the historic, current and future estimates and projections with number of inhabitants for the world's largest urban areas from 1950-2050. The data covers cities and other urban areas with more than 750,000 people.

PLANNING AREAS All Connections 2050 Long-Range Plan elements are available online at www.dvrpc.org/plan. The Plan has two primary documents: (1) The Connections 2050 Policy Manual (www.dvrpc.org/Products/21027) identifies the vision, goals, strategies, and a summary of the financial plan. (2) The Connections 2050 Process and Analysis Manual (www.dvrpc.org/Products/21028) provides a more detailed look at the Plan’s outreach, background information, analysis, and financial plan. Greater Philadelphia is a complex mosaic of 352 diverse cities, boroughs, and townships. The Connections 2045 Long-Range Plan characterizes each of the region’s municipalities as either a Core City, Developed Community, Growing Suburb, or Rural Area, as a means of categorizing the types of communities and defining the corresponding long-range planning policies most appropriate for each type. This categorization is shown on the Planning Areas and Centers dataset. Many municipalities have areas within their boundaries that fit the characteristics of more than one of these Planning Area types. Gloucester Township (in Camden County, New Jersey), for example, has neighborhoods that are fully developed, but it also has a significant number of undeveloped acres and forecasted population and employment growth more characteristic of a Growing Suburb. The intent of the Plan is to assign to each municipality the planning area type associated with the long-range planning policies that will be most beneficial to the entire community. While the Planning Areas and Centers map is a guide for policy direction at the regional scale, actual approaches should always be guided by local conditions. The region’s four Core Cities are Philadelphia, Trenton, Camden, and Chester. Targeted infrastructure investment, maintenance and rehabilitation, comprehensive neighborhood revitalization, and efforts focused on reinforcing a network of social and educational programs will help to rebuild and revitalize the region’s cities. Developed Communities are places that have already experienced most of their population and employment growth, and include inner ring communities adjacent to the Core Cities; railroad boroughs and trolley car communities; and mature suburban townships. Many of these communities are stable and thriving, offering affordable housing opportunities; access to transit; safe pedestrian and bicycling environments; and a strong community identity. Others, however, are experiencing population and employment losses; have deteriorating infrastructure systems; have aging resident populations living on limited incomes; and have stagnant or declining tax bases that cannot keep pace with rising service demands. Rehabilitation and maintenance of infrastructure systems and the housing stock, and local economic and community development can help to reinforce location advantages, while stabilizing neighborhoods and stemming decline. Growing Suburbs are communities that have a significant number of developable acres remaining and are experiencing or are forecast to experience significant population and/or employment growth. Key planning policies in these communities focus on the need to improve the form of development, reduce congestion, and mitigate the negative consequences of unmanaged growth, and include growth management and enhanced community design. Smart growth techniques that support a more concentrated development pattern (such as clustering, mixed uses, transit-oriented development, and transfer of development rights) can provide the critical mass necessary to support new transit services and other alternatives to the automobile. The quality of design and architectural character of the built environment, open space preservation, and the creation of an integrated system of open space and recreation are all priorities in these communities. Rural Areas include the region’s agricultural communities and communities with large remaining natural areas. Key policy approaches for these communities focus on preservation and limiting development, and include limited expansion of infrastructure systems, preservation of a rural lifestyle and village character, support for continued farming, and enhanced natural resource protection. Livable communities in these areas include rural centers that have an identi fi able main street, a mix of uses, higher densities than their surrounding uses, and a true sense of place.

It is expected that the highest temperature in Summer on average will be approximately 4.8 degrees Fahrenheit hotter in New York City by 2050 compared to the year 2000. The Winter lowest temperature will be 4.2 degrees hotter by 2050. The city of Chicago, Illinois expects an even higher increase of 5.6 degrees Fahrenheit in Summer's highest temperature and an increase of 5.8 degrees in Winter.

Extreme heat in the U.S. – additional information

Projected changes in global average temperature are associated with widespread changes in weather patterns. Scientific studies indicate that extreme weather events, such as heat waves, are likely to become more frequent or more intense within the next few years. These changes may lead to an increase in heat-related deaths in the United States. Outdoor temperatures can affect daily life in many ways. Extreme heat and the combination of high heat and humidity can pose a serious risk for human health. Exposure to extreme heat can lead to heat stroke and dehydration, as well as cardiovascular, respiratory and cerebrovascular disease. When the weather becomes excessively hot, it can be deadly. According to the National Weather Service, heat waves caused 45 fatalities in the United States in 2015.

The average temperatures in the U.S. have risen significantly since 1895. Long-term changes in climate can directly or indirectly affect many aspects of a person’s life. For example, warmer days could increase air conditioning or water supply costs. One way to measure the influence of temperature change on energy demand is by using heating and cooling degree days. Cooling degree days measure the difference between outdoor temperature and a temperature that people generally find comfortable indoors. Cooling degree days have not increased significantly over the past decades. However, a slight increase is evident for this period. In 2014, there were around 1,300 cooling degree days in the U.S., compared to 1,241 in 2009. More cooling degree days indicate an increase in temperature, leading to a greater likeliness of using air conditioning.

In 2020, about 82.66 percent of the total population in the United States lived in cities and urban areas. As the United States was one of the earliest nations to industrialize, it has had a comparatively high rate of urbanization over the past two centuries. The urban population became larger than the rural population during the 1910s, and by the middle of the century it is expected that almost 90 percent of the population will live in an urban setting. Regional development of urbanization in the U.S. The United States began to urbanize on a larger scale in the 1830s, as technological advancements reduced the labor demand in agriculture, and as European migration began to rise. One major difference between early urbanization in the U.S. and other industrializing economies, such as the UK or Germany, was population distribution. Throughout the 1800s, the Northeastern U.S. became the most industrious and urban region of the country, as this was the main point of arrival for migrants. Disparities in industrialization and urbanization was a key contributor to the Union's victory in the Civil War, not only due to population sizes, but also through production capabilities and transport infrastructure. The Northeast's population reached an urban majority in the 1870s, whereas this did not occur in the South until the 1950s. As more people moved westward in the late 1800s, not only did their population growth increase, but the share of the urban population also rose, with an urban majority established in both the West and Midwest regions in the 1910s. The West would eventually become the most urbanized region in the 1960s, and over 90 percent of the West's population is urbanized today. Urbanization today New York City is the most populous city in the United States, with a population of 8.3 million, while California has the largest urban population of any state. California also has the highest urbanization rate, although the District of Columbia is considered 100 percent urban. Only four U.S. states still have a rural majority, these are Maine, Mississippi, Montana, and West Virginia.

This dataset provides information about the number of properties, residents, and average property values for 2050 cross streets in Salt Lake City, UT.

The West Africa Coastal Vulnerability Mapping: Population Projections, 2030 and 2050 data set is based on an unreleased working version of the Gridded Population of the World (GPW), Version 4, year 2010 population count raster but at a coarser 5 arc-minute resolution. Bryan Jones of Baruch College produced country-level projections based on the Shared Socioeconomic Pathway 4 (SSP4). SSP4 reflects a divided world where cities that have relatively high standards of living, are attractive to internal and international migrants. In low income countries, rapidly growing rural populations live on shrinking areas of arable land due to both high population pressure and expansion of large-scale mechanized farming by international agricultural firms. This pressure induces large migration flow to the cities, contributing to fast urbanization, although urban areas do not provide many opportUnities for the poor and there is a massive expansion of slums and squatter settlements. This scenario may not be the most likely for the West Africa region, but it has internal coherence and is at least plausible.

50 year Projected Urban Growth scenarios. Base year is 2000. Projected year in this dataset is 2050.

By 2020, most forecasters agree, California will be home to between 43 and 46 million residents-up from 35 million today. Beyond 2020 the size of California's population is less certain. Depending on the composition of the population, and future fertility and migration rates, California's 2050 population could be as little as 50 million or as much as 70 million. One hundred years from now, if present trends continue, California could conceivably have as many as 90 million residents. Where these future residents will live and work is unclear. For most of the 20th Century, two-thirds of Californians have lived south of the Tehachapi Mountains and west of the San Jacinto Mountains-in that part of the state commonly referred to as Southern California. Yet most of coastal Southern California is already highly urbanized, and there is relatively little vacant land available for new development. More recently, slow-growth policies in Northern California and declining developable land supplies in Southern California are squeezing ever more of the state's population growth into the San Joaquin Valley. How future Californians will occupy the landscape is also unclear. Over the last fifty years, the state's population has grown increasingly urban. Today, nearly 95 percent of Californians live in metropolitan areas, mostly at densities less than ten persons per acre. Recent growth patterns have strongly favored locations near freeways, most of which where built in the 1950s and 1960s. With few new freeways on the planning horizon, how will California's future growth organize itself in space? By national standards, California's large urban areas are already reasonably dense, and economic theory suggests that densities should increase further as California's urban regions continue to grow. In practice, densities have been rising in some urban counties, but falling in others.

These are important issues as California plans its long-term future. Will California have enough land of the appropriate types and in the right locations to accommodate its projected population growth? Will future population growth consume ever-greater amounts of irreplaceable resource lands and habitat? Will jobs continue decentralizing, pushing out the boundaries of metropolitan areas? Will development densities be sufficient to support mass transit, or will future Californians be stuck in perpetual gridlock? Will urban and resort and recreational growth in the Sierra Nevada and Trinity Mountain regions lead to the over-fragmentation of precious natural habitat? How much water will be needed by California's future industries, farms, and residents, and where will that water be stored? Where should future highway, transit, and high-speed rail facilities and rights-of-way be located? Most of all, how much will all this growth cost, both economically, and in terms of changes in California's quality of life? Clearly, the more precise our current understanding of how and where California is likely to grow, the sooner and more inexpensively appropriate lands can be acquired for purposes of conservation, recreation, and future facility siting. Similarly, the more clearly future urbanization patterns can be anticipated, the greater our collective ability to undertake sound city, metropolitan, rural, and bioregional planning.

Consider two scenarios for the year 2100. In the first, California's population would grow to 80 million persons and would occupy the landscape at an average density of eight persons per acre, the current statewide urban average. Under this scenario, and assuming that 10% percent of California's future population growth would occur through infill-that is, on existing urban land-California's expanding urban population would consume an additional 5.06 million acres of currently undeveloped land. As an alternative, assume the share of infill development were increased to 30%, and that new population were accommodated at a density of about 12 persons per acre-which is the current average density of the City of Los Angeles. Under this second scenario, California's urban population would consume an additional 2.6 million acres of currently undeveloped land. While both scenarios accommodate the same amount of population growth and generate large increments of additional urban development-indeed, some might say even the second scenario allows far too much growth and development-the second scenario is far kinder to California's unique natural landscape.

This report presents the results of a series of baseline population and urban growth projections for California's 38 urban counties through the year 2100. Presented in map and table form, these projections are based on extrapolations of current population trends and recent urban development trends. The next section, titled Approach, outlines the methodology and data used to develop the various projections. The following section, Baseline Scenario, reviews the projections themselves. A final section, entitled Baseline Impacts, quantitatively assesses the impacts of the baseline projections on wetland, hillside, farmland and habitat loss.

VITAL SIGNS INDICATOR Population (LU1)

FULL MEASURE NAME
Population estimates

LAST UPDATED
February 2023

DESCRIPTION
Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region.

DATA SOURCE
California Department of Finance: Population and Housing Estimates - http://www.dof.ca.gov/Forecasting/Demographics/Estimates/
Table E-6: County Population Estimates (1960-1970)
Table E-4: Population Estimates for Counties and State (1970-2021)
Table E-8: Historical Population and Housing Estimates (1990-2010)
Table E-5: Population and Housing Estimates (2010-2021)

Bay Area Jurisdiction Centroids (2020) - https://data.bayareametro.gov/Boundaries/Bay-Area-Jurisdiction-Centroids-2020-/56ar-t6bs
Computed using 2020 US Census TIGER boundaries

U.S. Census Bureau: Decennial Census Population Estimates - http://www.s4.brown.edu/us2010/index.htm- via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University
1970-2020

U.S. Census Bureau: American Community Survey (5-year rolling average; tract) - https://data.census.gov/
2011-2021
Form B01003

Priority Development Areas (Plan Bay Area 2050) - https://opendata.mtc.ca.gov/datasets/MTC::priority-development-areas-plan-bay-area-2050/about

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
All historical data reported for Census geographies (metropolitan areas, county, city and tract) use current legal boundaries and names. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of December 2022.

Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.

Population estimates for Bay Area tracts and PDAs are from the decennial Census (1970-2020) and the American Community Survey (2011-2021 5-year rolling average). Population estimates for PDAs are allocated from tract-level Census population counts using an area ratio. For example, if a quarter of a Census tract lies with in a PDA, a quarter of its population will be allocated to that PDA. Estimates of population density for PDAs use gross acres as the denominator. Note that the population densities between PDAs reported in previous iterations of Vital Signs are mostly not comparable due to minor differences and an updated set of PDAs (previous iterations reported Plan Bay Area 2040 PDAs, whereas current iterations report Plan Bay Area 2050 PDAs).

The following is a list of cities and towns by geographical area:

Big Three: San Jose, San Francisco, Oakland

Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside

Inland, Delta and Coastal: American Canyon, Antioch, Benicia, Brentwood, Calistoga, Clayton, Cloverdale, Concord, Cotati, Danville, Dixon, Dublin, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Lafayette, Livermore, Martinez, Moraga, Morgan Hill, Napa, Novato, Oakley, Orinda, Petaluma, Pittsburg, Pleasant Hill, Pleasanton, Rio Vista, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Sonoma, St. Helena, Suisun City, Vacaville, Walnut Creek, Windsor, Yountville

Unincorporated: all unincorporated towns

DC 2050 presents an opportunity for the District to identify future challenges and opportunities and consider how to meet them in the next two decades. The DC Office of Planning (OP) will work with residents, community-based organizations, businesses, and elected officials to develop policies that guide how new buildings are added as the District's population and economy grow over the coming years.

Through an inclusive and robust public process, the District’s diverse communities will be invited to imagine the kind of city they want for themselves, their neighbors, and their children. Our approach for DC 2050:Community-centeredEngagement will reach residents who face the greatest barriers to involvement. Policies will be developed and assessed based on their impact on these populations.Data-drivenOP will use data in new ways to help residents learn how the Comprehensive Plan's policies are likely to impact their communities.User-friendlyA shorter, visually-appealing, and well-organized document will set priorities that can be easily understood by residents, property owners, investors, and community-based organizations.Outcome-orientedThe Comprehensive Plan will clearly explain the changes DC residents can expect for the District and their community.

Cities are facing climate-related hazards that are becoming ever more frequent and severe. As of 2020, about 99 cities globally reported that they experienced heat waves, and about 45 cities expected to experience this particular climate risk between 2022 and 2025.

The tier I areas are expected to receive urban services (sewer, water, roads, etc…) within the 30 year planning period. Tier II are areas that will receive urban services after 2060. As the 2060 Comp Plan is updated in upcoming years, some of these areas may be moved into the Tier I area. Tier II should remain in its current use in order to facilitate future development. Tier III, are areas for future development in the very long term – beyond 50 years. It is delineated along drainage basin lines that are mainly within the City’s 3-mile extraterritorial jurisdiction and is not actively planned for urban land uses and infrastructure. Maintained and Updated by the City of Lincoln / Lancaster County Planning Department.

Based on the future population forecast data, urban expansion driving factor data (road network density, residential area, night light, GDP) and so on, the future urban expansion model is used to simulate and predict the urban expansion pattern and land use distribution of Xining City in 2050. The data set contains four data results corresponding to the urban pattern of Xining in 2050 under different scenarios. They are maintaining the status quo (BAU), urban compact development (infill), continuing the existing pattern and protecting cultivated land (protect), compact development and protecting cultivated land (infill).

This polygonal layer represents projected land use and residential density in the year 2050. This layer was submitted as part of the City of Tempe's General Plan.Contact: Jacob Payne, Lucas JensenContact E-Mail: jacob_payne@tempe.gov, lucas_jensen@tempe.govContact Phone: 480-350-8096Link to department home page: https://www.tempe.gov/planningData Source: Spatial DatabaseData Source Type: GeospatialPreparation Method: Created based off documentation in current and previous General PlansPublish Frequency: As NecessaryPublish Method: Automatic

FUME data on projected distributions of migrants at local level between 2030 and 2050.

The dataset contains a folder of data for each destination city as a gridded dataset at 100m resolution in GeoTIFF format. The examined destination cities are: Amsterdam, Copenhagen, Krakow and Rome. The dataset is provided as 100m grid cells based on the Eurostat GISCO grid of the 2021 NUTS version, using ETRS89 Lambert Azimuthal Equal-Area (EPSG: 3035) as coordinate system. The file names consist of the projected year, the corresponding scenario, and the reference migrant group. The projections have been performed for the years 2030, 2040 and 2050. The investigated scenarios are the following: • benchmark (bs), • baseline (bs), • Rising East (re), • EU Recovery (eur), • Intensifying Global Competition (igc), and • War (war).

The migration background is derived from data about the Region of Origin (RoO) for migrants in Copenhagen and Amsterdam, and from Region of Citizenship (CoC) for migrants in Krakow and Rome.

The case study of Copenhagen covers the two central NUTS3 areas (DK011, DK012) and the groups presented are the following: • total population (totalpop), • native population (DNK), • Eastern EU European migrants (EU_East), • Western EU Europeans migrants (EU_West), • Non-EU European migrants (EurNonEU), • migrants from Turkey (Turkey), • the MENAP countries (MENAP; excluding Turkey), • other non-Western (OthNonWest), and • other Western countries (OthWestern).

The case study of Amsterdam covers one NUTS3 area (NL329) and the presented groups are the following: • total population (totalpop), • native population (NLD), • Eastern EU European migrants (EU East), • Western EU European migrants (EU West), • migrants from Turkey and Morocco (Turkey + Morocco), • migrants from the Middle East and Africa (Middle East + Africa), • migrants from the former colonies (Former Colonies), and • migrants from the rest of the world (Other Europe etc).

The case study of Krakow covers the Municipality of Krakow, and the presented groups are the following: • total population (totalpop), • native population (POL), • EU/EFTA European migrants (EU), • non-EU European migrants (Europe_nonEU), and • migrants from the rest of the world (Other).

The case of Rome covers the Municipality of Rome, and the presented groups are the following: • total population (totalpop), • native population (ITA), • migrants from Romania (ROU), • Philippines (PHL), • Bangladesh (BGD), • the EU (EU; excluding Romania), • Africa (Africa), • Asia (Asia; excluding Philippines and Bangladesh) and • America (America).

Subject to copyright IRENA 2018: Refer to attachment section of information tab for further details.REN21 Global Renewable Status stated examples of cities with renewable targets

Climate change projections suggest that European summer heat waves will become more frequent and severe during this century, continuing the trend of the past decades. The most severe impacts arise from multi-day heat waves associated with warm night-time temperatures and high relative humidity. Heat waves include tropical nights (with minimum temperatures above 20°C) and hot days (with maximum temperatures exceeding 35°C). The temperature map is the result of climatic modelling and represents the number of combined tropical nights and hot days. These projections are just one set of many different modelled scenarios that were produced by the ENSEMBLES project and featured in CLIMATE-ADAPT. For methodology see Fischer, E. M. and Schär, C., 2010, 'Consistent geographical patterns of changes in high-impact European heatwaves', Nature Geoscience, 3(6), pp.398–403. The original map is presented in the EEA report 2/2012 'Urban adaptation to climate change in Europe': map 2.4; data table and further methodological explanations in Annex II.