The population of Latin America and the Caribbean increased from 175 million in 1950 to 515 million in 2000. Where did this growth occur? What is the magnitude of change in different places? How can we visualize the geographic dimensions of population change in Latin America and the Caribbean? We compiled census and other public domain information to analyze both temporal and geographic changes in population in the region. Our database includes population totals for over 18,300 administrative districts within Latin America and the Caribbean. Tabular census data was linked to an administrative division map of the region and handled in a geographic information system. We transformed vector population maps to raster surfaces to make the digital maps comparable with other commonly available geographic information. Validation and error-checking analyses were carried out to compare the database with other sources of population information. The digital population maps created in this project have been put in the public domain and can be downloaded from our website. The Latin America and Caribbean map is part of a larger multi-institutional effort to map population in developing countries. This is the third version of the Latin American and Caribbean population database and it contains new data from the 2000 round of censuses and new and improved accessibility surfaces for creating the raster maps.

Based on land area, Brazil is the largest country in Latin America by far, with a total area of over 8.5 million square kilometers. Argentina follows with almost 2.8 million square kilometers. Cuba, whose surface area extends over almost 111,000 square kilometers, is the Caribbean country with the largest territory.

Brazil: a country with a lot to offer

Brazil's borders reach nearly half of the South American subcontinent, making it the fifth-largest country in the world and the third-largest country in the Western Hemisphere. Along with its landmass, Brazil also boasts the largest population and economy in the region. Although Brasília is the capital, the most significant portion of the country's population is concentrated along its coastline in the cities of São Paulo and Rio de Janeiro.

South America: a region of extreme geographic variation

With the Andes mountain range in the West, the Amazon Rainforest in the East, the Equator in the North, and Cape Horn as the Southern-most continental tip, South America has some of the most diverse climatic and ecological terrains in the world. At its core, its biodiversity can largely be attributed to the Amazon, the world's largest tropical rainforest, and the Amazon river, the world's largest river. However, with this incredible wealth of ecology also comes great responsibility. In the past decade, roughly 80,000 square kilometers of the Brazilian Amazon were destroyed. And, as of late 2019, there were at least 1,000 threatened species in Brazil alone.

In 2020, more than *** Latin American startups in the tech industry (or Tecnolatinas) focused on the Brazilian market. The regional strategy was chosen by *** Tecnolatinas, in comparison to the *** tech startups that adopted a global strategy. That same year, Argentina concentrated approximately ** percent of the startup ecosystem value in Latin America.

In 2020, Latin American technology-based companies (also called Tecnolatinas) with a regional geographic strategy were valued at over 100 billion U.S. dollars. Meanwhile, a large portion of the Tecnolatinas' ecosystem value was credited to startups focusing on the Brazilian market, which reported a market value of ** billion U.S. dollars. As of November 2020, six out of the top 10 most valuable unicorn companies in Latin America were based in Brazil.

This political map of South America shows national boundaries, country names and oceans.

This dataset and the accompanying code are intended to be used to replicate the results published in the paper “Public Services, Geography, and Citizen Perceptions of Government in Latin America.”

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Occupation titles and their 4-digit codes are based on the 2018 Standard Occupational Classification..Industry titles and their 4-digit codes are based on the North American Industry Classification System (NAICS). The Census industry codes for 2023 and later years are based on the 2022 revision of the NAICS. To allow for the creation of multiyear tables, industry data in the multiyear files (prior to data year 2023) were recoded to the 2022 Census industry codes. We recommend using caution when comparing data coded using 2022 Census industry codes with data coded using Census industry codes prior to data year 2023. For more information on the Census industry code changes, please visit our website at https://www.census.gov/topics/employment/industry-occupation/guidance/code-lists.html..Telephone service data are not available for certain geographic areas due to problems with data collection of this question that occurred in 2019. Both ACS 1-year and ACS 5-year files were affected. It may take several years in the ACS 5-year files until the estimates are available for the geographic areas affected..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate beca...

South America is part of Region 6 (Central and South America) for the World Energy Assessment. South America was divided into 107 geologic provinces as background for prioritization and assessment of undiscovered oil and gas resources. The boundaries of geologic provinces are required for the assessment as oil and gas. Data must be allocated to a geographic entity so that decisions can be made as to which provinces are priority for the assessment. Many sources of geologic information were used to define the province boundaries in South America, and several versions of the map were reviewed. Of the 107 geologic provinces defined in South America, about 40 have had some oil and gas production to date.

DATA DESCRIPTION: Version 2.0 estimates of total number of people per grid square for five timepoints between 2000 and 2020 at five year intervals; national totals have been adjusted to match UN Population Division estimates for each time point(1) REGION: Latin America and the Caribbean SPATIAL RESOLUTION: 0.00833333 decimal degrees (approx 1km at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - LAC_PPP_2010_adj_v2.tif = Latin America and the Caribbean (LAC) population dataset presenting people per pixel (PPP) for 2010, adjusted to match UN national estimates (adj), dataset version 2.0 (v2) DATASET CONSTRUCTION DETAILS: This dataset is a mosaic of all WorldPop country level LAC datasets resampled to 1km resolution. The continental grouping of countries honours the macro geographical classification developed and maintained by the United Nations Statistics Division(2). For countries within each continental group which have not been mapped by WorldPop, GPWv4 1km population count data(3) was used to complete the mosaic. Full details of WorldPop population mapping methodologies are described here: www.worldpop.org.uk/data/methods/ DATE OF PRODUCTION: November 2016 Also included: (i) csv table describing the data source of the modelled population data for each country dataset (either WorldPop or GPWv4) which featured in the continental raster mosaic. _ (1) United Nations Population Division, WorldPopulation Prospects, 2015 Revision. http://esa.un.org/wpp/ (2) United Nations Statistics Division. http://unstats.un.org/unsd/methods/m49/m49regin.htm (3) Center for International Earth Science Information Network - CIESIN - Columbia University. 2016. Gridded Population of the World, Version 4 (GPWv4): Population Count. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://dx.doi.org/10.7927/H4X63JVC. Accessed 30 Sept 2016

Abstract (en): The boundaries of five different geographic areas -- North America, South America, Europe, Africa, and Asia -- are digitally represented in this collection of data files that can be used in the production of computer maps. Each of the five areas is encoded in three distinct files: (1) coastline, islands, and lakes, (2) rivers, and (3) international boundaries. There is an additional file for North America (Part 4: North America: Internal Boundaries) delineating state lines in the United States and provincial boundaries in Canada. The data in each of the files is hierarchically structured into subordinate geographic features and ranks, which may be used for output plotting symbol definition. The mapping scale used to encode the data ranged from 1:1 million to 1:4 million. 2006-01-18 File CB8376.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads. (1) There are seven variables and an unknown number of cases for each file. The number of records per case varies according to the number of latitude and longitude coordinates needed to display the particular geographic feature. (2) The codebook is provided by ICPSR as a Portable Document Format (PDF) file. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using PDF reader software, such as the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided on the ICPSR Web site.

The main objective of this project is the creation of a system that integrates biophysical and socioeconomic information at different scales in order to perform analyses at various administrative levels.

Mean Annual Precipitation [mm/year] across South America using the Climate Hazards Group Infrared Precipitation with Station data (CHIRP) dataset.

This dataset presents information about facilities relating to the mineral industries of Latin America and the Caribbean. Facilities include mines, mineral processing plants (including refineries and smelters), oil and gas field locations, and petroleum refineries. Relevant data fields include the mineral commodity, specific forms of the mineral commodity produced, location information, facility name, operator, ownership of the facility, annual production capacity, operational status, as well as geographic coordinates and locational accuracy. These data are derived from data presented by country by the Global Minerals Analysis section of the U.S. Geological Survey's (USGS) National Minerals Information Center (NMIC) in Volume III (International Reports) of the annual Minerals Yearbook.

In 2020, companies with a regional geographic strategy raised approximately 40 percent of the capital investments received by Latin American tech startups (also called Tecnolatinas). Meanwhile, businesses targeting the Brazilian market concentrated around 35 percent of the capital raised by Tecnolatinas in 2020. This pattern is consistent with the rise of venture capital (VC) investments in the increasingly attractive Brazilian market, which accounted for over 50 percent of all VC deals closed in Latin America in 2019.

This political map of Mexico and Central America shows national and state boundaries, country names and oceans.

The mountains of South America are hotspots of plant diversity. How this diversity originated and evolved, and what roles geographic and environmental factors may have played in the diversification of lineages occurring in these regions is not well understood. Escallonia, a morphologically and ecologically diverse group of shrubs and trees widely distributed in these mountains, provides an ideal opportunity for studying the historical underpinnings that have shaped the extraordinarily distinctive, diverse, and endangered flora of these regions, and for evaluating the role of abiotic factors in the process of lineage divergence. I analyzed neutral DNA sequence data from two nuclear loci and one chloroplast locus using maximum parsimony, maximum likelihood, and Bayesian phylogenetic approaches. I used a Bayesian approach to analyze the geographic structure of gene trees, and a phylogenetically controlled decomposition of the variance in bioclimatic variables to analyze the eco-climatic structure of gene trees. I found i) that Escallonia is monophyletic, ii) a remarkable level of geographical and climatic phylogenetic structure, iii) that Escallonia likely originated in the tropical Andes, and iv) a widespread absence of species exclusivity. Geography played an important role early on the history of Escallonia by separating populations that later diversify likely in isolation. Although geographic isolation was generally accompanied by changes in climate, it is not clear whether environmental gradients along elevation have influenced more recent diversification events, or species have evolved broader environmental tolerances.

Techsalerator’s News Event Data in Latin America offers a detailed and extensive dataset designed to provide businesses, analysts, journalists, and researchers with an in-depth view of significant news events across the Latin American region. This dataset captures and categorizes key events reported from a wide array of news sources, including press releases, industry news sites, blogs, and PR platforms, offering valuable insights into regional developments, economic changes, political shifts, and cultural events.

Key Features of the Dataset: Comprehensive Coverage:

The dataset aggregates news events from numerous sources such as company press releases, industry news outlets, blogs, PR sites, and traditional news media. This broad coverage ensures a wide range of information from multiple reporting channels. Categorization of Events:

News events are categorized into various types including business and economic updates, political developments, technological advancements, legal and regulatory changes, and cultural events. This categorization helps users quickly locate and analyze information relevant to their interests or sectors. Real-Time Updates:

The dataset is updated regularly to include the most recent events, ensuring users have access to the latest news and can stay informed about current developments. Geographic Segmentation:

Events are tagged with their respective countries and regions within Latin America. This geographic segmentation allows users to filter and analyze news events based on specific locations, facilitating targeted research and analysis. Event Details:

Each event entry includes comprehensive details such as the date of occurrence, source of the news, a description of the event, and relevant keywords. This thorough detailing helps in understanding the context and significance of each event. Historical Data:

The dataset includes historical news event data, enabling users to track trends and perform comparative analysis over time. This feature supports longitudinal studies and provides insights into how news events evolve. Advanced Search and Filter Options:

Users can search and filter news events based on criteria such as date range, event type, location, and keywords. This functionality allows for precise and efficient retrieval of relevant information. Latin American Countries Covered: South America: Argentina Bolivia Brazil Chile Colombia Ecuador Guyana Paraguay Peru Suriname Uruguay Venezuela Central America: Belize Costa Rica El Salvador Guatemala Honduras Nicaragua Panama Caribbean: Cuba Dominican Republic Haiti (Note: Primarily French-speaking but included due to geographic and cultural ties) Jamaica Trinidad and Tobago Benefits of the Dataset: Strategic Insights: Businesses and analysts can use the dataset to gain insights into significant regional developments, economic conditions, and political changes, aiding in strategic decision-making and market analysis. Market and Industry Trends: The dataset provides valuable information on industry-specific trends and events, helping users understand market dynamics and emerging opportunities. Media and PR Monitoring: Journalists and PR professionals can track relevant news across Latin America, enabling them to monitor media coverage, identify emerging stories, and manage public relations efforts effectively. Academic and Research Use: Researchers can utilize the dataset for longitudinal studies, trend analysis, and academic research on various topics related to Latin American news and events. Techsalerator’s News Event Data in Latin America is a crucial resource for accessing and analyzing significant news events across the region. By providing detailed, categorized, and up-to-date information, it supports effective decision-making, research, and media monitoring across diverse sectors.

Violence has harmful effects on individuals and society. This is especially true in Latin America, a region that stands out globally for its high homicide rate. Building on research on subnational politics, democratization, and an inter-disciplinary literature that seeks to understand sources of violence, we examine the effect of municipal politics on homicide rates in Brazil while controlling for conventional socio-structural accounts. Specifically, we test the effect of four key political variables – party identification of mayors, partisan alignment of mayors and governors, electoral competition, and voter participation – and examine the locally varying effect of these variables with geographically weighted regressions (GWR). Our emphasis on political explanations of criminal violence is a rare departure from dominant accounts of violent crime, suggesting comparisons with the literature on political violence, and the spatial approach allows an analysis of the territorially uneven effect of political variables. The results show the statistical significance, direction, and magnitude of key political factors vary substantially across Brazil’s 5562 municipalities, showcasing the uneven effect of predictors of violence across space, and generating new hypothesis regarding the conditional effect of key predictors. In the time period examined (2007–2012), the largest left party in Brazil, Workers' Party (PT), had a beneficial effect, reducing violence in large parts of Brazil, the center party that held most local governments (PMDB) had a harmful effect in certain areas of Brazil, and the largest center-right party (PSDB) had mixed effects – helpful in some parts of Brazil and harmful in others. These results help us understand key features of the relationship between Brazilian politics and public security across different parts of the country, illuminating the political geography of violence in the region's largest country.

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Geographic Information System Analytics Market Size 2024-2028

The geographic information system analytics market size is forecast to increase by USD 12 billion at a CAGR of 12.41% between 2023 and 2028.

The GIS Analytics Market analysis is experiencing significant growth, driven by the increasing need for efficient land management and emerging methods in data collection and generation. The defense industry's reliance on geospatial technology for situational awareness and real-time location monitoring is a major factor fueling market expansion. Additionally, the oil and gas industry's adoption of GIS for resource exploration and management is a key trend. Building Information Modeling (BIM) and smart city initiatives are also contributing to market growth, as they require multiple layered maps for effective planning and implementation. The Internet of Things (IoT) and Software as a Service (SaaS) are transforming GIS analytics by enabling real-time data processing and analysis.
Augmented reality is another emerging trend, as it enhances the user experience and provides valuable insights through visual overlays. Overall, heavy investments are required for setting up GIS stations and accessing data sources, making this a promising market for technology innovators and investors alike.

What will be the Size of the GIS Analytics Market during the forecast period?

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The geographic information system analytics market encompasses various industries, including government sectors, agriculture, and infrastructure development. Smart city projects, building information modeling, and infrastructure development are key areas driving market growth. Spatial data plays a crucial role in sectors such as transportation, mining, and oil and gas. Cloud technology is transforming GIS analytics by enabling real-time data access and analysis. Startups are disrupting traditional GIS markets with innovative location-based services and smart city planning solutions. Infrastructure development in sectors like construction and green buildings relies on modern GIS solutions for efficient planning and management. Smart utilities and telematics navigation are also leveraging GIS analytics for improved operational efficiency.
GIS technology is essential for zoning and land use management, enabling data-driven decision-making. Smart public works and urban planning projects utilize mapping and geospatial technology for effective implementation. Surveying is another sector that benefits from advanced GIS solutions. Overall, the GIS analytics market is evolving, with a focus on providing actionable insights to businesses and organizations.

How is this Geographic Information System Analytics Industry segmented?

The geographic information system analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

End-user

  Retail and Real Estate
  Government
  Utilities
  Telecom
  Manufacturing and Automotive
  Agriculture
  Construction
  Mining
  Transportation
  Healthcare
  Defense and Intelligence
  Energy
  Education and Research
  BFSI


Components

  Software
  Services


Deployment Modes

  On-Premises
  Cloud-Based


Applications

  Urban and Regional Planning
  Disaster Management
  Environmental Monitoring Asset Management
  Surveying and Mapping
  Location-Based Services
  Geospatial Business Intelligence
  Natural Resource Management


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    South Korea


  Middle East and Africa

    UAE


  South America

    Brazil


  Rest of World

By End-user Insights

The retail and real estate segment is estimated to witness significant growth during the forecast period.

The GIS analytics market analysis is witnessing significant growth due to the increasing demand for advanced technologies in various industries. In the retail sector, for instance, retailers are utilizing GIS analytics to gain a competitive edge by analyzing customer demographics and buying patterns through real-time location monitoring and multiple layered maps. The retail industry's success relies heavily on these insights for effective marketing strategies. Moreover, the defense industries are integrating GIS analytics into their operations for infrastructure development, permitting, and public safety. Building Information Modeling (BIM) and 4D GIS software are increasingly being adopted for construction project workflows, while urban planning and designing require geospatial data for smart city planning and site selection.

The oil and gas industry is leveraging satellite imaging and IoT devices for land acquisition and mining operations. In the public sector,

ABSTRACT Stachytarpheta is the second largest genus of Verbenaceae, mainly distributed in xeric habitats of South America. The morphological revision of South American specimens clarified the taxonomic identity of three previously accepted species from informal group Gesnerioides: S. sprucei (from the Amazon Forest domain), S. alata, and S. tomentosa (from the Atlantic Forest domain). A new taxonomic arrangement is proposed here, with the synonymization of S. alata and S. tomentosa under S. sprucei. Consequently, the newly circumscribed S. sprucei evidences a remarkable geographic disjunction, with populations separated by the Caatinga, Cerrado, and Chaco domains (the South American dry diagonal). It inhabits inselbergs, tepuis, and savannas in the Amazon Forest domain, and top of inselbergs surrounded by forest in the Atlantic Forest domain. A detailed species description, taxonomic comments, a geographic distribution map, photos of living specimens, and an identification key to the species from the Gesnerioides group are included.