The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Brazil: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Dataset Overview

This dataset provides a comprehensive overview of Brazil’s 2022 Census data, focusing on São Paulo’s neighbourhoods. The data combines demographic and socioeconomic information with geospatial shapefiles of São Paulo’s neighbourhoods, enabling users to perform statistical and spatial analyses.

Users can explore patterns, trends, and transformations in São Paulo’s urban landscape by linking census sectors to neighbourhood boundaries.

Key Components

Census 2022 Data

• Source: Brazil's 2022 Census (IBGE)
• Content: Demographic data including age, gender, income, education levels, household size, and population density across census sectors.
• Format: CSV

São Paulo Neighborhood Shapefile

• Source: GIS-based shapefiles for São Paulo neighbourhoods (IBGE Census Sectors and Manually created Neighbourhoods)
• Content: Spatial geometry for São Paulo's neighbourhoods with census sector identifiers.
• Format: Parquet

Use Cases

• Neighborhood Demographics Analysis: Combine census data with shapefiles to generate neighborhood-level demographic reports.
• Urban Development Studies: Study how São Paulo neighbourhoods have grown using historical context and 2022 Census data.
• Spatial Data Visualizations: Create maps showing income distribution, population density, or other demographic factors across neighbourhoods.
• Policy Planning & Research: Support urban planning, resource allocation, and policy development in São Paulo.

Potential Applications

• Analyze the relationship between neighbourhood demographics and urban growth patterns.
• Visualize inequalities in population distribution, income, or education levels.
• Identify trends in housing and population density for urban studies.
• Provide insights into São Paulo’s historical and ongoing transformations.

Why Use This Dataset?

• Comprehensive Coverage: Detailed census data and spatial boundaries allow in-depth analyses.
• Flexible Integration: Easily combine demographic data with shapefiles to enable advanced spatial analyses.

Dataset Details

• File Formats: CSV (Census Data), GeoJSON/Shapefile (Neighborhood Shapefiles)
• Spatial Resolution: Census sector linked to São Paulo’s neighbourhood boundaries

Geographic Scope: São Paulo, Brazil

This dataset is ideal for data scientists, urban planners, and researchers seeking to uncover the dynamics of São Paulo’s neighbourhoods through an intersection of demographic and spatial data.

Contribute to new insights and empower decision-making in understanding Brazil’s largest city!

These maps represent a modeled distribution of population based on the nominal censuses of the town of Curitiba and adjacent towns, providing a snapshot of the demographic situation in a specific year. Classification of data is normalized for each year to allow comparison between different categories of data for the same year.

Data used in my analysis of COVID-19 underreporting in Brazil. It includes 2019 brazilian population estimates by state, provided by IBGE, and a rds file with Brazilian map also by state.

Abstract The study analyzes the demographic boom of African slave populations in the plantation areas from the Mapas de População of Maranhão. In particular, we focus on the parish of Rosário do Itapecuru using other sources - post-mortem inventories and parish baptismal records. The maps from 1798 and 1821 made it possible to evidence the gender, age, ethnicity and legal status of the resident population as well as show the importance of slave population in cotton and rice crop areas, reaching almost 80% of residents. These populations, in turn, presented certain peculiarities in relation to other plantation areas in the State of Brazil, such as the sex ratio marked by the almost parity between men and women.

This data set contains physical, hydrologic, political, demographic, and societal maps for the Ji-Parana River Basin, in the state of Rondonia, Brazil. These data were used as base information in subsequent investigations of land use/land cover, biogeochemistry, soils, and water balance processes (Ballester et al., 2003). This data set includes a Digital Elevation Model (DEM), river networks and morphometric characteristics of the region (derived from the DEM), and a number of social and demographic vector sets (roads as of 2001, county borders, population change from 1970-2000, and settlement projects). The DEM is provided in GeoTIFF format. Other files are provided as shapefiles.

These maps represent a modeled distribution of population based on the nominal censuses of the town of Curitiba and adjacent towns. Classification of data is normalized for each category to allow comparison between different periods of time.

Retirement Notice: This item is in mature support as of September 2025 and will retire in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.Brazil Subdistrito Boundaries provides a 2021 boundary with a total population count. The layer is designed to be used for mapping and analysis. It can be enriched with additional attributes using data enrichment tools in ArcGIS Online.The 2021 boundaries are provided by Michael Bauer Research GmbH. They are sourced from 2013 Instituto Brasileiro de Geografia e Estatistica. These were published in October 2022. A new layer will be published in 18 months. Other administrative boundaries for this country are also available: Country Unidade Municipio Distrito Sectore

BackgroundThis study aims to describe the role of mobility in malaria transmission by discussing recent changes in population movements in the Brazilian Amazon and developing a flow map of disease transmission in this region.Methodology/Principal findingsThis study presents a descriptive analysis using an ecological approach on regional and local scales. The study location was the municipality of Porto Velho, which is the capital of Rondônia state, Brazil. Our dataset was obtained from the official health database, the population census and an environmental database. During 2000–2007 and 2007–2010, the Porto Velho municipality had an annual population growth of 1.42% and 5.07%, respectively. This population growth can be attributed to migration, which was driven by the construction of the Madeira River hydroelectric complex. From 2010 to 2012, 63,899 malaria-positive slides were reported for residents of Porto Velho municipality; 92% of the identified samples were autochthonous, and 8% were allochthonous. The flow map of patients' movements between residential areas and areas of suspected infection showed two patterns of malaria transmission: 1) commuting between residential areas and the Jirau hydropower dam reservoir, and 2) movements between urban areas and farms and resorts in rural areas. It was also observed that areas with greater occurrences of malaria were characterized by a low rate of deforestation.ConclusionsThe Porto Velho municipality exhibits high malaria endemicity and plays an important role in disseminating the parasite to other municipalities in the Amazon and even to non-endemic areas of the country. Migration remains an important factor for the occurrence of malaria. However, due to recent changes in human occupation of the Brazilian Amazon, characterized by intense expansion of transportation networks, commuting has also become an important factor in malaria transmission. The magnitude of this change necessitates a new model to explain malaria transmission in the Brazilian Amazon.

AbstractUrbanization often substantially influences animal movement and gene flow. However, few studies to date have examined gene flow of the same species across multiple cities. In this study, we examine brown rats (Rattus norvegicus) to test hypotheses about the repeatability of neutral evolution across four cities: Salvador, Brazil; New Orleans, USA; Vancouver, Canada; New York City, USA. At least 150 rats were sampled from each city and genotyped for a minimum of 15,000 genome-wide SNPs. Levels of genome-wide diversity were similar across cities, but varied across neighborhoods within cities. All four populations exhibited high spatial autocorrelation at the shortest distance classes (< 500 m) due to limited dispersal. Coancestry and evolutionary clustering analyses identified genetic discontinuities within each city that coincided with a resource desert in New York City, major waterways in New Orleans, and roads in Salvador and Vancouver. Such replicated studies are crucial to assessing the generality of predictions from urban evolution, and have practical applications for pest management and public health. Future studies should include a range of global cities in different biomes, incorporate multiple species, and examine the impact of specific characteristics of the built environment and human socioeconomics on gene flow. Usage notesPLINK .map file for New Orleans rat SNP GenotypesPLINK .map file for New Orleans SNP genotypes. The genotypes themselves are in the .ped file of the same name, and the .map file contains the chromosomal coordinates for each SNP.NOL.plink.mapPLINK .ped file for New Orleans rat SNP GenotypesPLINK .ped file for New Orleans SNP genotypes. The genotypes themselves are in the .ped file, and the .map file contains the chromosomal coordinates for each SNP.NOL.plink.pedPLINK .map file for New York City rat SNP GenotypesPLINK .map file for New York City SNP genotypes. The genotypes themselves are in the .ped file of the same name, and the .map file contains the chromosomal coordinates for each SNP.NYC.plink.mapPLINK .ped file for New York City rat SNP GenotypesPLINK .ped file for New York City SNP genotypes. The genotypes themselves are in the .ped file, and the .map file contains the chromosomal coordinates for each SNP.NYC.plink.pedPLINK .map file for Salvador, Brazil rat SNP GenotypesPLINK .map file for Salvador, Brazil SNP genotypes. The genotypes themselves are in the .ped file of the same name, and the .map file contains the chromosomal coordinates for each SNP.SAL.plink.mapPLINK .ped file for Salvador, Brazil rat SNP GenotypesPLINK .ped file for Salvador, Brazil SNP genotypes. The genotypes themselves are in the .ped file, and the .map file contains the chromosomal coordinates for each SNP.SAL.plink.pedPLINK .map file for Vancouver rat SNP GenotypesPLINK .map file for Vancouver SNP genotypes. The genotypes themselves are in the .ped file of the same name, and the .map file contains the chromosomal coordinates for each SNP.VAN.plink.mapPLINK .ped file for Vancouver rat SNP GenotypesPLINK .ped file for Vancouver SNP genotypes. The genotypes themselves are in the .ped file, and the .map file contains the chromosomal coordinates for each SNP.VAN.plink.ped

Figure 1. Origin of Phakopsora pachyrhizi populations in Brazil map. Leaves sampled collected of soybean plants infected with Asian soybean rust collected the 2017/2018 soybean seasons. Brazilian States: BA - Bahia and PR - Paraná. Municipalities: BA - Luis Eduardo Magalhães; PR - Campo Magro, Palmeira, Palotina and Ponta Grossa.

This data set contains physical, hydrologic, political, demographic, and societal maps for the Ji-Parana River Basin, in the state of Rondonia, Brazil. These data were used as base information in subsequent investigations of land use/land cover, biogeochemistry, soils, and water balance processes (Ballester et al., 2003).

This data set includes a Digital Elevation Model (DEM), river networks and morphometric characteristics of the region (derived from the DEM), and a number of social and demographic vector sets (roads as of 2001, county borders, population change from 1970-2000, and settlement projects). The DEM is provided in GeoTIFF format. Other files are provided as shapefiles.

P-values of single and multiple QTLs and haplotype combinations associated with witches’ broom disease. The first tab contains the single QTL with their different parental haplotype combinations. The different columns contain the total number of trees with each haplotype and the results of the Chi-squared test for resistance and susceptibility. The last column contains the percentage of resistant trees with the particular haplotype combination. The second and third tab contain the same info but for combinations of two and three QTL, respectively. The combinations marked in grey belong to the top five of lowest P-values and indicate the highest associations between the QTL and WBD resistance/susceptibility. (XLS 81 kb)

This 1 km resolution 41-class land cover classification map of South America was produced from 1-15 km National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data over the time period 1987 through 1991.

These data were originally acquired from Woods Hole Research Center ("http://terra.whrc.org/science/tropfor/setLBA.htm") and were modified as described in documentation provided when data are ordered from EOS-WEBSTER.

Digital images of these data are also available from the EOS-WEBSTER Image Gallary. Please see the Data Tab at the following URL: "http://eos-earthdata.sr.unh.edu/". These images can be downloaded as JPEGs and used directly in a document or printed.

This is a PDF format map of the country, as released by the United Nations.

As of October 2025, India had the largest Facebook audience worldwide, with over 403 million users. To put this figure into perspective, if India’s Facebook user base were a country, it would rank as the third most populous nation globally. Besides India, three other markets had more than 100 million Facebook users each: the United States, Indonesia and Brazil. Facebook – the most used social media Meta, the company that was previously called Facebook, owns four of the most popular social media platforms worldwide, WhatsApp, Facebook Messenger, Facebook, and Instagram. As of the third quarter of 2021, there were around 3.5 billion cumulative monthly users of the company’s products worldwide. With around 2.9 billion monthly active users, Facebook is the most popular social media worldwide. With an audience of this scale, it is no surprise that the vast majority of Facebook’s revenue is generated through advertising. Facebook usage by device As of July 2021, it was found that 98.5 percent of active users accessed their Facebook account from mobile devices. In fact, almost 81.8 percent of Facebook audiences worldwide access the platform only via mobile phone. Facebook is not only available through mobile browser as the company has published several mobile apps for users to access their products and services. As of the third quarter 2021, the four core Meta products were leading the ranking of most downloaded mobile apps worldwide, with WhatsApp amassing approximately six billion downloads.

Phenotypic data of witches’ broom disease in MP01. (XLS 184 kb)

As of October 2025, Indonesia was the country with the largest TikTok advertising reach, with ****** million users engaging with the popular social video platform. The United States followed, with ****** million TikTok users. Brazil came in third, with ****** million users on TikTok watching short videos. From Reels to Shorts: Social short video takes the internet Between 2021 and 2022, some of the most popular social media platforms have been adding short-video features on the heels of TikTok’s popularity. YouTube Shorts, which rolled out to the global market in June 2021, reached *** billion monthly active logged-in users in 2023. In comparison, Instagram’s short-video format Reels, which launched in August 2020, presented a higher view rate than regular videos on the platform between June 2021 and June 2022, as well as a higher likes rate than other content types on Instagram. TikTok business model TikTok is owned by the Beijing-based ByteDance, along with the short-video app Douyin (TikTok’s version for the Chinese market), video platform Xigua, and popular news app Toutiao. While the products intended for domestic market consumption operate in the Chinese digital ecosystem and have a plurality of established monetization methods, such as live-shopping events hosted by famous influencers, TikTok’s main revenue stream comes from online advertising. In 2025, ByteDance was estimated to have generated around **** billion U.S. dollars worldwide via online advertising.

Forest Ecosystem Dynamics (FED) Project Spatial Data Archive: Elevation Contours for the Northern Experimental Forest

The Biospheric Sciences Branch (formerly Earth Resources Branch) within the Laboratory for Terrestrial Physics at NASA's Goddard Space Flight Center and associated University investigators are involved in a research program entitled Forest Ecosystem Dynamics (FED) which is fundamentally concerned with vegetation change of forest ecosystems at local to regional spatial scales (100 to 10,000 meters) and temporal scales ranging from monthly to decadal periods (10 to 100 years). The nature and extent of the impacts of these changes, as well as the feedbacks to global climate, may be addressed through modeling the interactions of the vegetation, soil, and energy components of the boreal ecosystem.

The Howland Forest research site lies within the Northern Experimental Forest of International Paper. The natural stands in this boreal-northern hardwood transitional forest consist of spruce-hemlock-fir, aspen-birch, and hemlock-hardwood mixtures. The topography of the region varies from flat to gently rolling, with a maximum elevation change of less than 68 m within 10 km. Due to the region's glacial history, soil drainage classes within a small area may vary widely, from well drained to poorly drained. Consequently, an elaborate patchwork of forest communities has developed, supporting exceptional local species diversity.

This data layer contains elevation contours for the 10 X 10 km area located within the Northern Experimental Forest. Contours and elevation benchmarks from the United States Geological Survey 7.5" Maine quadsheets for Howland and Lagrange were digitized, and elevation data in feet were added.

The data was revised by projecting it into NAD83 datum by L. Prihodko at NASA Goddard Space Flight Center. Although the data was received at GSFC with an undeclared datum, it was assumed to be in North American Datum of 1927 (NAD27) because the original map from which the data were digitized was in NAD27. Also, the data fit exactly within the bounds of the FED site grid (even Universal Transverse Mercator projections) in NAD27. After projecting the data into NAD83 it was checked to insure that the change was a linear translation of the coordinates.

This is a PDF format map of the country, as released by the United Nations.