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.

Urban population (% of total population) in India was reported at 36.87 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Urban population (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

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.

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.

Urban population growth (annual %) in India was reported at 2.2645 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Urban population growth (annual %) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

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".

This raster layer shows the areas of Jalna, 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.

Following the Geopolis guidelines, the dataset provides the shapefile of all physical agglomerates of over 5,000 inhabitants as urban in India in 2010 with their population data of 2001 and 2011 – an agglomerate being considered as a contiguous built-up area. The objective of the e-Geopolis project is to promote the use of a single, globally applicable technical definition of the term. This approach is based on:

• a simple morphological criterion across space and time: (the contiguity of built-up areas with a maximum of 200 meters separating constructions), and

• a single threshold (10,000 inhabitants) applied uniformly across the board, even when the national definition uses other criteria

• 6,485 morphological agglomerate’s polygons with at least 10,000 inhabitants in 2001 considered urban are delineated

• as well as smaller morphological agglomerates above 5,000 inhabitants in 2001.

Geopolis definition eliminates the technical or methodological biases of the official definition, linked in the case of India to the problem of the spread of an agglomeration over different administrative units either officially rural or urban and/or crossing State borders. Having carried out the necessary processes of standardization on a diachronic set of data, verification on the ground and digitalization of each morphological configuration, we can now offer a scientifically valid view of India’s urban continuum. These steps have eliminated most (if not all) of the distortions resulting from an unquestioning dependence on official figures, besides attempting a classical analysis of demographic trends.

Delineation of agglomerates has been made using GoogleEarth imagery.

see:

Denis, E., & Marius-Gnanou, K. (2010). Toward a better appraisal of urbanization in India. A fresh look at the landscape of morphological agglomerates. Cybergeo: European Journal of Geography.

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.

There is an abundance of studies on the urban-rural dichotomy. In the mainstream economic and regional science literature, the urban centers have usually been described as growth machines, growth poles, or growth foci, and urbanization as a driver of economic growth. It is commonly assumed that the assemblage of factors of production in urban centers will create economies of scale, and that economic growth will trickle down from these centers to the periphery. Most of these studies hypothesize a mono-directional causal relationship between urbanization and economic growth. However, there are ample possibilities of reverse causalities in regions where the propulsive powers of urban centers are weaker and where social overhead capital (SOC) is not adequately developed in non-urban regions. In this situation, even minor economic changes in non-urban economies will cause the growth of the urban population. The present paper attempts to examine the relationship between urbanization and economic growth in India at the state level during 1971–2020 by employing a bootstrap panel Granger causality test. It is found that in India the majority of the states display a unidirectional Granger causality from economic growth to urbanization. This finding indicates not only a lower propulsive power of urban centers, but also an unbalanced development of SOC between urban centers and rural areas, hence causing a migration of people to cities with a rise in their income in order to take advantage of the urban facilities.

This raster layer contains the total area occupied by the built-up area of Jalna, India and its urbanized open space in 2000. Categories of urban land use represented in these data include: urban, suburban, rural and urbanized open land. The built-up area of the city is the area occupied by built-up pixels within the set of administrative boundaries defining the city. The urbanized open space consists of all fringe open spaces (including exterior open spaces) and all captured open spaces. These data are part of the Atlas of Urban Expansion.

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

Growth of the Census Towns of India during 2001 to 2011

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

This raster layer shows the areas of Kānpur, 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 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 raster layer shows the areas of Kolkata, 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.

In 2022, roughly ** percent of Bhutan's population resided in urban areas. Comparatively, approximately ** percent of Sri Lanka's population lived in urban areas in 2022.

Urbanization in the APAC region

The Asia-Pacific region is currently experiencing a significant trend towards urbanization, with a growing number of individuals relocating from rural areas to urban centers in pursuit of improved economic prospects. From 2015 to 2020, there was an increase in the urban population throughout Asia. The projection for the region indicates a continuation of urbanization, although at a decelerated rate. As of 2021, a third of the entire population of India resided in urban areas. The data shows a notable upsurge in urbanization in India over the past ten years, indicating a shift of the populace from rural to urban centers in search of employment opportunities and livelihood.

 Population of megacities in APAC 

The APAC region is home to some of the world's most populous megacities. According to recent data, in 2023, the annual metropolitan population growth rate of China surpassed that of other megacities in the APAC region. In contrast to other cities, the three megacities in Japan, namely Tokyo, Osaka, and Nagoya, exhibited the lowest annual population growth rates. That same year, the APAC region was home to ** megacities, more than ten of which were in China. India, Japan, and Pakistan also had more than once megacity each as of January 2023.