In 2023, approximately a third of the total population in India lived in cities. The trend shows an increase of urbanization by more than 4 percent in the last decade, meaning people have moved away from rural areas to find work and make a living in the cities. Leaving the fieldOver the last decade, urbanization in India has increased by almost 4 percent, as more and more people leave the agricultural sector to find work in services. Agriculture plays a significant role in the Indian economy and it employs almost half of India’s workforce today, however, its contribution to India’s GDP has been decreasing while the services sector gained in importance. No rural exodus in sightWhile urbanization is increasing as more jobs in telecommunications and IT are created and the private sector gains in importance, India is not facing a shortage of agricultural workers or a mass exodus to the cities yet. India is a very densely populated country with vast areas of arable land – over 155 million hectares of land was cultivated land in India as of 2015, for example, and textiles, especially cotton, are still one of the major exports. So while a shift of the workforce focus is obviously taking place, India is not struggling to fulfill trade demands yet.

Urbanisation is a form of social transformation from traditional rural societies to modern, industrial and urban communities. It is long term continuous process. It is progressive concentration of population in urban unit. Kingsley Davies has explained urbanisation as process of switch from spread out pattern of human settlements to one of concentration in urban centers. Migration is the key process underlying growth of urbanization.

Challenges in urban development--->;

Institutional challenges

Urban Governance 74th amendment act has been implemented half-heartedly by the states, which has not fully empowered the Urban local bodies (ULBs). ULBs comprise of municipal corporations, municipalities and nagar panchayats, which are to be supported by state governments to manage the urban development. For this , ULBs need clear delegation of functions, financial resources and autonomy. At present urban governance needs improvement for urban development, which can be done by enhancing technology, administrative and managerial capacity of ULBs.

Planning Planning is mainly centralized and till now the state planning boards and commissions have not come out with any specific planning strategies an depend on Planning commission for it. This is expected to change in present government, as planning commission has been abolished and now focus is on empowering the states and strengthening the federal structure.

In fact for big cities the plans have become outdated and do not reflect the concern of urban local dwellers, this needs to be take care by Metropolitan planning committee as per provisions of 74th amendment act. Now the planning needs to be decentralized and participatory to accommodate the needs of the urban dwellers.

Also there is lack of human resource for undertaking planning on full scale. State planning departments and national planning institutions lack qualified planning professional. Need is to expand the scope of planners from physical to integrated planning- Land use, infrastructure, environmental sustainability, social inclusion, risk reduction, economic productivity and financial diversity.

Finances Major challenge is of revenue generation with the ULBs. This problem can be analyzed form two perspectives. First, the states have not given enough autonomy to ULBs to generate revenues and Second in some case the ULBs have failed to utilize even those tax and fee powers that they have been vested with.

There are two sources of municipal revenue i.e. municipal own revenue and assigned revenue. Municipal own revenue are generated by municipal own revenue through taxes and fee levied by them. Assigned revenues are those which are assigned to local governments by higher tier of government.

There is growing trend of declining ratio of own revenue. There is poor collection property taxes. Use of geographical information system to map all the properties in a city can have a huge impact on the assessment rate of properties that are not in tax net.

There is need to broaden the user charge fee for water supply, sewerage and garbage disposal. Since these are the goods which have a private characteristics and no public spill over, so charging user fee will be feasible and will improve the revenue of ULBs , along with periodic revision. Once the own revenue generating capacity of the cities will improve, they can easily get loans from the banks. At present due to lack of revenue generation capabilities, banks don’t give loan to ULBs for further development. For financing urban projects, Municipal bonds are also famous, which work on the concept of pooled financing.

Regulator

There is exponential increase in the real estate, encroaching the agricultural lands. Also the rates are very high, which are not affordable and other irregularities are also in practice. For this, we need regulator, which can make level playing field and will be instrumental for affordable housing and checking corrupt practices in Real estate sector.

Infrastructural challenges

Housing Housing provision for the growing urban population will be the biggest challenge before the government. The growing cost of houses comparison to the income of the urban middle class, has made it impossible for majority of lower income groups and are residing in congested accommodation and many of those are devoid of proper ventilation, lighting, water supply, sewage system, etc. For instance in Delhi, the current estimate is of a shortage of 5,00,000 dwelling units the coming decades. The United Nations Centre for Human Settlements (UNCHS) introduced the concept of “Housing Poverty” which includes “Individuals and households who lack safe, secure and healthy shelter, with basic infrastructure such as piped water and adequate provision for sanitation, drainage and the removal of hou...

In 2022, India's urban population recorded a growth rate of two percent. The growth rate slowed down by 0.1 percent from the previous year's growth rate. The growth rate has been on a downward trend since 2020 after a period of stagnation between 2014 and 2018.

Actual value and historical data chart for India Urban Population Percent Of Total

According to projections, *** percent of the population of NCT Delhi, Chandigarh and Lakshadweep in India were expected to live in urban areas by 2035. By contrast, slightly over *** percent of the population of Himachal Pradesh was expected to live in urban areas by the same year, which has the least share compared to the other states.

Actual value and historical data chart for India Urban Population Growth Annual Percent

This statistic shows the ten countries with the largest increase in the size of the population between 2023 and 2050. Based on forecasted population figures, the population of India is projected to be around *** million more in 2050 than it was in 2023.

This dataset is about books. It has 1 row and is filtered where the book is Urbanization and urban India. It features 7 columns including author, publication date, language, and book publisher.

In financial year 2025, the Indian state of Delhi allocated the largest budget share to urban development, accounting for approximately *** percent of their respective total budgets. Gujarat closely followed, with urban development receiving about *** percent of the state's total budget.

Yearly citation counts for the publication titled "Urbanization and agricultural land loss in India: Comparing satellite estimates with census data".

Urbanization is associated with higher prevalence of cardiovascular disease worldwide. Aortic stiffness, as measured by carotid-femoral pulse wave velocity is a validated predictor of cardiovascular disease. Our objective was to determine the association between urbanization and carotid-femoral pulse wave velocity. The analysis included 6166 participants enrolled in an ongoing population-based study (mean age 42 years; 58% female) who live in an 80 × 80 km region of southern India. Multiple measures of urbanization were used and compared: 1) census designations, 2) satellite derived land cover (crops, grass, shrubs or trees as rural; built-up areas as urban), and 3) distance categories based on proximity to an urban center. The association between urbanization and carotid-femoral pulse wave velocity was tested in sex-stratified linear regression models. People residing in urban areas had significantly (p < 0.05) elevated mean carotid-femoral pulse wave velocity compared to non-urban populations after adjustment for other risk factors. There was also an inverse association between distance from the urban center and mean carotid-femoral pulse wave velocity: each 10 km increase in distance was associated with a decrease in mean carotid-femoral pulse wave velocity of 0.07 m/s (95% CI: -0.09, -0.06 m/s). The association was stronger among older participants, among smokers, and among those with other cardiovascular risk factors. Further research is needed to determine which components in the urban environment are associated with higher carotid-femoral pulse wave velocity.

This raster layer shows the areas of Poona, India which were developed between 1990 and 2000. Categories of new development represented in these data include: infill, extension and leapfrog. Infill represents development within all the open spaces in the urban footprint of the earlier period excluding exterior open space. Extension represents development in contiguous clusters that contained exterior open space in the earlier period and that were not infUnited States Leapfrog represents development entirely outside the exterior open space of the earlier period. These data are part of the Atlas of Urban Expansion.

This dataset includes the LULC maps developed using the Landsat 8/7 datasets for the years 2002, 2013 and 2021 for the Jammu district in India. The dataset further includes the 1 km interval buffer rings for the multi-buffer ring analysis for retrieving urbanization parameters such as the urban area, urban density and urban growth rate. Additionally, a quality index is derived based on these parameters and an amenity database to compare the status of Jammu and Indore cities.

Growth of the Census Towns of India during 2001 to 2011

In 2020, over ************ projects worth nearly ************ U.S. dollars were completed within India's smart cities mission initiative. Over ************* projects worth nearly ** billion U.S. dollars had been tendered and around ***** projects worth nearly ** billion U.S. dollars were ongoing.

The smart cities mission was initiated in 2015 and aimed at implementing technological infrastructure in urban areas. One hundred cities were selected for a period from 2019 to 2023.

How do rising temperatures affect long-term labor reallocation in developing economies? In this paper, we examine how increases in temperature impact structural transformation and urbanization within Indian districts between 1951 and 2011. We find that rising temperatures are associated with lower shares of workers in non-agriculture, with effects intensifying over a longer time frame. Supporting evidence suggests that local demand effects play an important role: declining agricultural productivity under higher temperatures reduces the demand for non-agricultural goods and services, which subsequently lowers non-agricultural labor demand. Our results illustrate that rising temperatures limit sectoral and rural-urban mobility for isolated households.

The statistic displays the main states and union territories with the highest number of people living in urban areas in India in 2011. In that year, the state of Maharashtra had the highest population with over 50 million people living in urban areas. The population density in India from 2004 to 2014 can be seen here.

In 2024, approximately 67 percent of the total population in China lived in cities. The urbanization rate has increased steadily in China over the last decades. Degree of urbanization in China Urbanization is generally defined as a process of people migrating from rural to urban areas, during which towns and cities are formed and increase in size. Even though urbanization is not exclusively a modern phenomenon, industrialization and modernization did accelerate its progress. As shown in the statistic at hand, the degree of urbanization of China, the world's second-largest economy, rose from 36 percent in 2000 to around 51 percent in 2011. That year, the urban population surpassed the number of rural residents for the first time in the country's history.The urbanization rate varies greatly in different parts of China. While urbanization is lesser advanced in western or central China, in most coastal regions in eastern China more than two-thirds of the population lives already in cities. Among the ten largest Chinese cities in 2021, six were located in coastal regions in East and South China. Urbanization in international comparison Brazil and Russia, two other BRIC countries, display a much higher degree of urbanization than China. On the other hand, in India, the country with the worlds’ largest population, a mere 36.3 percent of the population lived in urban regions as of 2023. Similar to other parts of the world, the progress of urbanization in China is closely linked to modernization. From 2000 to 2024, the contribution of agriculture to the gross domestic product in China shrank from 14.7 percent to 6.8 percent. Even more evident was the decrease of workforce in agriculture.

Additional file 2: Raw Dietary Diversity Data Collected. Raw Dietary Diversity Data Collected. Excel sheet of food consumption data collected from participants by enumerators.

his dataset contains demographic information for Indian states from the Census years 1951 to 2011. It includes total population, rural and urban population, literacy rate, and sex ratio for each state/UT across multiple decades.

The dataset can be used for:

Analyzing population trends over time

Studying urbanization and rural migration

Examining literacy growth across states

Understanding sex ratio imbalances historically

Building machine learning models for future population prediction

Columns Included:

State – Name of the State or Union Territory

Year – Census year (1951, 1961, ..., 2011)

Total_Population – Total population in that year

Rural_Population – Population in rural areas

Urban_Population – Population in urban areas

Literacy_Rate – Literacy percentage of the population

Sex_Ratio – Number of females per 1000 males