World Countries Generalized provides a generalized basemap layer for the countries of the world. It has fields for official names and country codes. The generalized boundaries improve draw performance and effectiveness at global and continental levels.This layer is best viewed out beyond a maximum scale (zoomed in) of 1:5,000,000.The sources of this dataset are Esri, Garmin, and U.S. Central Intelligence Agency (The World Factbook). It is updated every 12-18 months as country names or significant borders change.

A dataset containing the longitude and latitude of all countries typically includes the geographic coordinates for each country. The coordinates usually represent the geographic center, capital city, or another significant location within the country. Such a dataset can be useful for various applications, including mapping, geographic analysis, and location-based services.

The average for 2023 based on 47 countries was 487236 sq. km. The highest value was in Russia: 16376870 sq. km and the lowest value was in Monaco: 2 sq. km. The indicator is available from 1961 to 2023. Below is a chart for all countries where data are available.

The increased world population is among the fierce problems the world is facing right now and it will get uncontrolled in the coming future if proper steps for its betterment were not taken immediately. This world has observed the fastest growth during the 20th century. In the 1950s world population was 2.7 billion, By the end of this year it will cross 8 billion. This dataset is uploaded with the assumption to use your Data Science, Machine learning, and Predictive analytics skills and answer the following questions. 1. Which countries have the highest growth rate. 2. What are the densely populated countries in the world. 3. Keeping in view all the variables in mind which countries should take serious steps to control their population.

This layer shows particulate matter in the air sized 2.5 micrometers of smaller (PM 2.5). The data is aggregated from NASA Socioeconomic Data and Applications Center (SEDAC) gridded data into country boundaries, administrative 1 boundaries, and 50 km hex bins. The unit of measurement is micrograms per cubic meter.The layer shows the annual average PM 2.5 from 1998 to 2016, highlighting if the overall mean for an area meets the World Health Organization guideline of 10 micrograms per cubic meter annually. Areas that don't meet the guideline and are above the threshold are shown in red, and areas that are lower than the guideline are in grey.The data is averaged for each year and over the the 19 years to provide an overall picture of air quality globally. Some of the things we can learn from this layer:What is the average annual PM 2.5 value over 19 years? (1998-2016)What is the annual average PM 2.5 value for each year from 1998 to 2016?What is the statistical trend for PM 2.5 over the 19 years? (downward or upward)Are there hot spots (or cold spots) of PM 2.5 over the 19 years?How many people are impacted by the air quality in an area?What is the death rate caused by the joint effects of air pollution?Choose a different attribute to symbolize in order to reveal any of the patterns above.A space time cube was performed on a multidimensional mosaic version of the data in order to derive an emerging hot spot analysis, trends, and a 19-year average. The country and administrative 1 layers provide a population-weighted PM 2.5 value to emphasize which areas have a higher human impact. Citations:van Donkelaar, A., R. V. Martin, M. Brauer, N. C. Hsu, R. A. Kahn, R. C. Levy, A. Lyapustin, A. M. Sayer, and D. M. Winker. 2018. Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, 1998-2016. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/H4ZK5DQS. Accessed 1 April 2020van Donkelaar, A., R. V. Martin, M. Brauer, N. C. Hsu, R. A. Kahn, R. C. Levy, A. Lyapustin, A. M. Sayer, and D. M. Winker. 2016. Global Estimates of Fine Particulate Matter Using a Combined Geophysical-Statistical Method with Information from Satellites. Environmental Science & Technology 50 (7): 3762-3772. https://doi.org/10.1021/acs.est.5b05833.Boundaries and population figures:Antarctica is excluded from all maps because it was not included in the original NASA grids.50km hex bins generated using the Generate Tessellation tool - projected to Behrmann Equal Area projection for analysesPopulation figures generated using Zonal Statistics from the World Population Estimate 2016 layer from ArcGIS Living Atlas.Administrative boundaries from World Administrative Divisions layer from ArcGIS Living Atlas - projected to Behrmann Equal Area projection for analyses and hosted in Web MercatorSources: Garmin, CIA World FactbookPopulation figures generated using Zonal Statistics from the World Population Estimate 2016 layer from ArcGIS Living Atlas.Country boundaries from Esri 2019 10.8 Data and Maps - projected to Behrmann Equal Area projection for analyses and hosted in Web Mercator. Sources: Garmin, Factbook, CIAPopulation figures attached to the country boundaries come from the World Population Estimate 2016 Sources Living Atlas layer Data processing notes:NASA's GeoTIFF files for 19 years (1998-2016) were first brought into ArcGIS Pro 2.5.0 and put into a multidimensional mosaic dataset.For each geography level, the following was performed: Zonal Statistics were run against the mosaic as a multidimensional layer.A Space Time Cube was created to compare the 19 years of PM 2.5 values and detect hot/cold spot patterns. To learn more about Space Time Cubes, visit this page.The Space Time Cube is processed for Emerging Hot Spots where we gain the trends and hot spot results.The layers are hosted in Web Mercator Auxillary Sphere projection, but were processed using an equal area projection: Behrmann. If using this layer for analysis, it is recommended to start by projecting the data back to Behrmann.The country and administrative layer were dissolved and joined with population figures in order to visualize human impact.The dissolve tool ensures that each geographic area is only symbolized once within the map.Country boundaries were generalized post-analysis for visualization purposes. The tolerance used was 700m. If performing analysis with this layer, find detailed country boundaries in ArcGIS Living Atlas. To create the population-weighted attributes on the country and Admin 1 layers, the hex value population values were used to create the weighting. Within each hex bin, the total population figure and average PM 2.5 were multiplied.The hex bins were converted into centroids and the PM2.5 and population figures were summarized within the country and Admin 1 boundaries.The summation of the PM 2.5 values were then divided by the total population of each geography. This population value was determined by summarizing the population values from the hex bins within each geography.Some artifacts in the hex bin layer as a result of the input NASA rasters. Because the gridded surface is created from multiple satellites, there are strips within some areas that are a result of satellite paths. Some areas also have more of a continuous pattern between hex bins as a result of the input rasters.Within the country layer, an air pollution attributable death rate is included. 2016 figures are offered by the World Health Organization (WHO). Values are offered as a mean, upper value, lower value, and also offered as age standardized. Values are for deaths caused by all possible air pollution related diseases, for both sexes, and all age groups. For more information visit this page, and here for methodology. According to WHO, the world average was 95 deaths per 100,000 people.To learn the techniques used in this analysis, visit the Learn ArcGIS lesson Investigate Pollution Patterns with Space-Time Analysis by Esri's Kevin Bulter and Lynne Buie.

This dataset provides values for WORLD reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

The Gridded Population of the World, Version 4 (GPWv4): National Identifier Grid, Revision 11 is a raster representation of nation-states in GPWv4 for use in aggregating population data. This data set was produced from the input census units which were used to create a raster surface where pixels that cover the same census data source (most often a country or territory) have the same value. Note that these data are not official representations of country boundaries; rather, they represent the area covered by the input data. In cases where multiple countries overlapped a given pixel (e.g. on national borders), the pixels were assigned the country code of the input data set which made up the majority of the land area. The data file was produced as a global raster at 30 arc-second (~1 km at the equator) resolution. To enable faster global processing, and in support of research communities, the 30 arc-second data were aggregated to 2.5 arc-minute, 15 arc-minute, 30 arc-minute and 1 degree resolutions. Each level of aggregation results in the loss of one or more countries with areas smaller than the cell size of the final raster. Rasters of all resolutions were also converted to polygon shapefiles. To provide a raster representation of nation-states in GPWv4 for use in aggregating population data.

Dataset

This dataset was created by Nabin Oli

Contents

Abstract

The World Bank Group is interested in gauging the views of clients and partners who are either involved in development in Brazil or who observe activities related to social and economic development. The World Bank Country Assessment Survey is meant to give the World Bank Group's team that works in Brazil, greater insight into how the Bank's work is perceived. This is one tool the World Bank Group uses to assess the views of its critical stakeholders. With this understanding, the World Bank Group hopes to develop more effective strategies, outreach and programs that support development in Brazil at the federal/state/municipal level. The World Bank Group commissioned an independent firm to oversee the logistics of this effort in Brazil.

This survey was designed to achieve the following objectives: - Assist the World Bank Group in gaining a better understanding of how stakeholders in Brazil perceive the Bank;

• Obtain systematic feedback from stakeholders in Brazil regarding: · Their views regarding the general environment in Brazil; · Their overall attitudes toward the World Bank Group in Brazil; · Overall impressions of the World Bank Group's effectiveness and results, knowledge work, and communication and information sharing in Brazil; · Perceptions of the recent trends and the World Bank Group's future role in Brazil.

• Use data to help inform Brazil country team's strategy.

Geographic coverage

National

Analysis unit

Stakeholder

Universe

Stakeholders of the World Bank in Brazil

Kind of data

Sample survey data [ssd]

Sampling procedure

From June to August 2013, 10,200 stakeholders of the World Bank Group in Brazil were invited to provide their opinions on the Bank's assistance to the country by participating in a country survey. Participants in the survey were drawn from the office of the President, Prime Minister/Minister, office of a parliamentarian, ministries, ministerial departments, or implementation agencies; consultants/ contractors working on World Bank Group-supported projects/programs; project management units (PMUs) overseeing implementation of a project; state Government; municipal governments; bilateral and multilateral agencies; private sector organizations; private foundations; the financial sector/private banks; NGOs; community-based organizations; the media; independent government institutions; trade unions; academia/research institutes/think tanks; faith-based groups, the judiciary branch; and other organizations.

Mode of data collection

Internet [int]

Research instrument

The Questionnaire consists of 8 Sections:

A. General Issues facing Brazil: Respondents were asked to indicate whether Brazil is headed in the right direction, what they thought were the top three development priorities in Brazil, and which areas would contribute most to reducing poverty and generating economic growth

B. Overall Attitudes toward the World Bank Group: Respondents were asked to rate their familiarity with the World Bank, Inter-American Development Bank, Latin American Development Bank, and the International Finance Corporation, their perceived effectiveness of these organizations in Brazil, and which of these organizations they work with the most in Brazil. They were asked to rate the Bank staff's preparedness to help Brazil solve its development challenges, their agreement with various statements regarding the Bank's work, and the extent to which the Bank is an effective development partner.

Respondents were also asked to indicate the Bank's greatest values, greatest weaknesses, the most effective instruments in helping reduce poverty in Brazil, in which sectoral areas the Bank should focus most resources, to what extent the Bank should seek to influence the global development agenda, and to what reasons respondents attributed failed or slow reform efforts. Respondents were invited to indicate at what level (federal, state, or municipal) the World Bank Group works mostly in Brazil. They were asked if the Bank is most effective when it works in one sector or multi-sectorally. Lastly, they were asked to indicate to what extent they believe the combination of financial, knowledge, and convening services provided by the Bank meets the national development needs of Brazil.

C. World Bank Group Effectiveness and Results: Respondents were asked to rate the extent to which the Bank's work helps achieve development results, the extent to which the Bank meets Brazil's needs for knowledge services and financial instruments, and the Bank's level of effectiveness across thirty-two development areas, such as education, public sector governance/reform, health, transport, and anti-corruption. They were also asked to what extent they believe that Brazil receives value for money from the World Bank Group's fee-based services/products.

D. The World Bank Group's Knowledge: Respondents were asked to indicate the areas on which the Bank should focus its research efforts and to rate the effectiveness and quality of the Bank's knowledge work and activities, including how significant of a contribution it makes to development results and its technical quality. Respondents were also asked whether they read/consulted the most recent LAC Flagship Report and whether it provided useful information in their work.

E. Working with the World Bank Group: Respondents were asked to rate their level of agreement with a series of statements regarding working with the Bank, such as the World Bank Group's "Safeguard Policy" requirements being reasonable, the Bank imposing reasonable conditions on its lending, disbursing funds promptly, increasing Brazil's institutional capacity, and providing effective implementation support.

F. The Future Role of the World Bank Group in Brazil: Respondents were asked to rate how significant a role the World Bank Group should play in Brazil in the near future and to indicate what the Bank should do to make itself of greater value. Respondents were asked to indicate to what extent they believe the World Bank Group has moved in the right direction in terms of the focus of its work in Brazil and how significant a role international development cooperation should play in Brazil's development in the near future at the federal, state, and/or municipal level.

G. Communication and Information Sharing: Respondents were asked to indicate how they get information about economic and social development issues, how they prefer to receive information from the Bank, and their usage and evaluation of the Bank's websites. Respondents were asked about their awareness of the Bank's Access to Information policy, whether they used/had used the World Bank Group website, and whether they accessed the Bank's social media channels. Respondents were also asked about their level of agreement that they know how to find information from the Bank, and that the Bank is responsive to information requests. Respondents were also asked to indicate what kind of e-services they are currently subscribed to.

H. Background Information: Respondents were asked to indicate their current position, specialization, at what level (federal, state, or municipal) they primarily work at, whether they professionally collaborate with the World Bank Group, whether they worked with the International Finance Corporation in Brazil, their exposure to the Bank in Brazil, and their geographic location.

Response rate

A total of 200 stakeholders participated in the survey (2% response rate).

Retirement Notice: This item is in mature support as of June 2025 and will retire in December 2026. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. World Time Zones represents the time zones of the world. The time zones are best displayed with World Countries or World Administrative Divisions.

Geo-Political TAGS consist of two-letter codes for countries and world regions. The country codes are taken from the Federal Information Processing Standards Publication No. 10 (FIPS). Some of the Regional TAGS are based strictly on geographic locations while others are based on political regions.

Graph and download economic data for Harmonised Unemployment - Monthly Rates: Total: All Persons for the Euro Area (19 Countries) (LRHUTTTTEZA156N) from 1993 to 2022 about Euro Area, harmonized, Europe, persons, unemployment, and rate.

The average for 2023 based on 18 countries was 6.2 percent. The highest value was in Syria: 24 percent and the lowest value was in Djibouti: 0.1 percent. The indicator is available from 1961 to 2023. Below is a chart for all countries where data are available.

Abstract

The World Bank Group is interested in gauging the views of clients and partners who are either involved in development in Peru or who observe activities related to social and economic development. The following survey will give the World Bank Group's team that works in Peru, greater insight into how the Bank's work is perceived. This is one tool the World Bank Group uses to assess the views of its stakeholders, and to develop more effective strategies that support development in Peru. A local independent firm was hired to oversee the logistics of this survey.

This survey was designed to achieve the following objectives: - Assist the World Bank Group in gaining a better understanding of how stakeholders in Peru perceive the Bank Group; - Obtain systematic feedback from stakeholders in Peru regarding: · Their views regarding the general environment in Peru; · Their overall attitudes toward the World Bank Group in Peru; · Overall impressions of the World Bank Group's effectiveness and results, knowledge work and activities, and communication and information sharing in Peru; · Perceptions of the World Bank Group's future role in Peru. - Use data to help inform Peru country team's strategy.

Geographic coverage

Metropolitan Lima Area, Outside of Metropolitan Lima Area

Analysis unit

Stakeholders in Peru

Universe

Stakeholders in Peru

Kind of data

Sample survey data [ssd]

Sampling procedure

In February-April 2014, 465 stakeholders of the World Bank Group in Peru were invited to provide their opinions on the WBG's work in the country by participating in a country opinion survey. Participants were drawn from the office of the President; the office of the Prime Minister; office of a minister; office of a parliamentarian; ministries, ministerial departments, or implementation agencies; consultants/contractors working on WBG-supported projects/programs; project management units (PMUs) overseeing implementation of a project; local government officials; bilateral and multilateral agencies; private sector organizations; private foundations; the financial sector/private banks; NGOs; community based organizations; the media; independent government institutions; trade unions; faith-based groups; academia/research institutes/think tanks; judiciary branch; and other organizations.

Mode of data collection

Other [oth]

Research instrument

The Questionnaire consists of following sections:

A. General Issues Facing Peru: Respondents were asked to indicate whether Peru is headed in the right direction, what they thought were the top three most important development priorities in the country, which areas would contribute most to reducing poverty and generating economic growth in Peru, and how "shared prosperity" would be best achieved.

B. Overall Attitudes toward the World Bank Group (WBG): Respondents were asked to rate their familiarity with the WBG and other regional development banks, their effectiveness in Peru, WBG staff preparedness to help Peru solve its development challenges, WBG's local presence, WBG's capacity building in Peru, their agreement with various statements regarding the WBG's work, and the extent to which the WBG is an effective development partner. Respondents were asked to indicate the WBG's greatest values and weaknesses, the most effective instruments in helping reduce poverty in Peru, in which sectoral areas the WBG should focus most of its resources (financial and knowledge services), and to what reasons respondents attributed failed or slow reform efforts. Respondents were also asked to respond to a few questions about capacity building and whether they believe the World Bank Group should have more or less local presence.

C. World Bank Group's Effectiveness and Results: Respondents were asked to rate the extent to which the WBG's work helps achieve development results in Peru, the extent to which the WBG meets Peru's needs for knowledge services and financial instruments, the importance for the WBG to be involved in thirty one development areas, and the WBG's level of effectiveness across these areas, such as education, public sector governance/reform, water and sanitation, and transport.

D. The World Bank Group's Knowledge Work and Activities: Respondents were asked to indicate how frequently they consult WBG's knowledge work and activities and to rate the effectiveness and quality of the WBG's knowledge work and activities, including how significant of a contribution it makes to development results and its technical quality. Respondents were also asked about the WBG reports, including which of them are the most useful, whether they raised substantive new information, and whether they provided them with useful information in terms of work they do.

E. Working with the World Bank Group: Respondents were asked to rate WBG's technical assistance/advisory work's contribution to solving development challenges and their level of agreement with a series of statements regarding working with the WBG, such as the WBG's "Safeguard Policy" requirements being reasonable, and disbursing funds promptly.

F. The Future Role of the World Bank Group in Peru: Respondents were asked to indicate what the WBG should do to make itself of greater value in Peru, and which services the Bank should offer more of in the country. They were asked whether WBG has moved to the right direction, and the future role international development cooperation should play in Peru.

G. Communication and Information Sharing: Respondents were asked to indicate how they get information about economic and social development issues, how they prefer to receive information from the WBG, and their usage and evaluation of the WBG's websites. Respondents were also asked about their awareness of the WBG's Access to Information policy, were asked to rate WBG's responsiveness to information requests, value of its social media channels, and levels of easiness to find information they needed.

H. Background Information: Respondents were asked to indicate their current position, specialization, whether they professionally collaborate with the WBG, their exposure to the WBG in Peru, which WBG agencies they work with, whether IFC and the Bank work well together, and their geographic location.

Response rate

A total of 197 stakeholders participated in the survey (42% response rate).

As of October 2025, India had the largest offline population worldwide, with more than 440 million people lacking internet access. Pakistan ranked second, with approximately 139.39 million people not connected to the internet. Despite these figures, both countries also ranked among those with the highest numbers of internet users globally. Internet access in Africa In 2023, Africa lagged behind other global regions regarding internet penetration rate, as only 37 percent of the continent’s population accessed the web. In contrast, around 91 percent of Europe’s population were internet users. This is heavily influenced by the infrastructure development in the region. However, some improvements are forecasted, as by 2028, the internet penetration rate in Africa will be at an estimated 48.15 percent. Global internet access challenges: disruptions and restrictions Government internet shutdowns around the world are another challenge for internet access. Between 2015 and the first half of 2023, 172 local internet connection disruptions occurred due to protests globally. Moreover, according to a 2023report on internet freedom, almost four out of ten global internet users were deprived of essential freedoms on online platforms. In 2023, 76 new restrictions on internet usage were implemented worldwide. Asia led in imposing these restrictions, accounting for approximately 55 cases across various countries in the region.

Dataset

This dataset was created by Paramartha Sengupta

Contents

Women and Men in Spain: Early dropout of education and training of persons aged 18 to 24. Spain and EU-28. Annual. National.

Abstract

The World Bank is interested in gauging the views of clients and partners who are either involved in development in Sierra Leone or who observe activities related to social and economic development. The World Bank Country Assessment Survey is meant to give the World Bank's team that works in Sierra Leone, greater insight into how the Bank's work is perceived. This is one tool the World Bank uses to assess the views of its critical stakeholders. With this understanding, the World Bank hopes to develop more effective strategies, outreach and programs that support development in Sierra Leone. The World Bank commissioned an independent firm to oversee the logistics of this effort in Sierra Leone.

The survey was designed to achieve the following objectives: - Assist the World Bank in gaining a better understanding of how stakeholders in Sierra Leone perceive the Bank; - Obtain systematic feedback from stakeholders in Sierra Leone regarding: · Their views regarding the general environment in Sierra Leone; · Their overall attitudes toward the World Bank in Sierra Leone; · Overall impressions of the World Bank's effectiveness and results, knowledge work and activities, and communication and information sharing in Sierra Leone; · Perceptions of the World Bank's future role in Sierra Leone. - Use data to help inform Sierra Leone team's strategy.

Geographic coverage

National

Analysis unit

Stakeholder

Universe

Stakeholders of the World Bank in Sierra Leone

Kind of data

Sample survey data [ssd]

Sampling procedure

In March-April 2013, 600 stakeholders of the World Bank in Sierra Leone were invited to provide their opinions on the Bank's assistance to the country by participating in a country survey. Participants in the survey were drawn from among the office of the President; the office of the Prime Minister; the office of a Minister; the office of a Parliamentarian; employees of a ministry, ministerial department, or implementation agency; consultants/ contractors working on World Bank-supported projects/programs; project management units (PMUs) overseeing implementation of a project; local government officials or staff; bilateral and multilateral agencies; private sector organizations; private foundations; the financial sector/private banks; NGOs; community-based organizations; the media; independent government institutions; trade unions; faith-based groups; academia/research institutes/think tanks; judiciary branches; and other organizations.

Mode of data collection

Mail Questionnaire [mail]

Research instrument

The Questionnaire consists of 8 Sections:

A. General Issues Facing Sierra Leone: Respondents were asked to indicate whether Sierra Leone is headed in the right direction, what they thought were the top three most important development priorities in the country, and which areas would contribute most to reducing poverty and generating economic growth in Sierra Leone.

B. Overall Attitudes toward the World Bank: Respondents were asked to rate their familiarity with the World Bank, the Bank's effectiveness in Sierra Leone, Bank staff preparedness to help Sierra Leone solve its development challenges, their agreement with various statements regarding the Bank's work, and the extent to which the Bank is an effective development partner. Respondents were asked to indicate the sectoral areas on which it would be most productive for the Bank to focus its resources, the Bank's greatest values and weaknesses in its work, the most effective instruments in helping to reduce poverty in Sierra Leone, with which stakeholder groups the Bank should collaborate more, and to what reasons respondents attributed failed or slow reform efforts.

C. World Bank Effectiveness and Results: Respondents were asked to rate the extent to which the Bank's work helps achieve development results in Sierra Leone, the extent to which the Bank meets Sierra Leone's needs for knowledge services and financial instruments, and the Bank's level of effectiveness across forty-two development areas, such as education, energy, agricultural development, job creation/employment, infrastructure, and others.

D. The World Bank's Knowledge: Respondents were asked to indicate how frequently they consult Bank knowledge work/activities, the areas on which the Bank should focus its research efforts, and to rate the effectiveness and quality of the Bank's knowledge work/activities, including how significant of a contribution it makes to development results and its technical quality.

E. Working with the World Bank: Respondents were asked to rate their level of agreement with a series of statements regarding working with the Bank, such as the World Bank's "Safeguard Policy" requirements being reasonable, the Bank imposing reasonable conditions on its lending, disbursing funds promptly, increasing Sierra Leone's institutional capacity, and providing effective implementation support. Respondents also were asked that to what extent they believed the Bank was adequately staffed in Sierra Leone.

F. The Future Role of the World Bank in Sierra Leone: Respondents were asked to rate how significant a role the Bank should play in Sierra Leone's development in the near future and to indicate what the Bank should do to make itself of greater value. They were also asked about the effectiveness of the donors in their work to see through development results on the ground and the effectiveness of the Bank in helping forge regional economic integration.

G. Communication and Information Sharing: Respondents were asked to indicate how they get information about economic and social development issues, how they prefer to receive information from the Bank, and their usage and evaluation of the Bank's websites. Respondents were asked about their awareness of the Bank's Access to Information policy, past information requests from the Bank, and their level of agreement that they use more data from the World Bank as a result of the Bank's Open Data policy. Respondents were also asked about their level of agreement that they know how to find information from the Bank and that the Bank is responsive to information requests.

H. Background Information: Respondents were asked to indicate their current position, specialization, whether they professionally collaborate with the World Bank, their exposure to the Bank in Sierra Leone, and their geographic location.

Response rate

A total of 340 stakeholders participated in the survey (57% response rate).

Graph and download economic data for Activity Rate: Aged 15-74: All Persons for the Euro Area (19 Countries) (LRAC74TTEZQ156S) from Q1 2005 to Q4 2022 about 15 to 74 years, participation, Euro Area, Europe, labor force, labor, and rate.

Use this country model layer when performing analysis within a single country. This layer displays a single global land cover map that is modeled by country for the year 2050 at a pixel resolution of 300m. ESA CCI land cover from the years 2010 and 2018 were used to create this prediction.Variable mapped: Projected land cover in 2050.Data Projection: Cylindrical Equal AreaMosaic Projection: Cylindrical Equal AreaExtent: Global Cell Size: 300mSource Type: ThematicVisible Scale: 1:50,000 and smallerSource: Clark UniversityPublication date: April 2021What you can do with this layer?This layer may be added to online maps and compared with the ESA CCI Land Cover from any year from 1992 to 2018. To do this, add Global Land Cover 1992-2018 to your map and choose the processing template (image display) from that layer called “Simplified Renderer.” This layer can also be used in analysis in ecological planning to find specific areas that may need to be set aside before they are converted to human use.Links to the six Clark University land cover 2050 layers in ArcGIS Living Atlas of the World:There are three scales (country, regional, and world) for the land cover and vulnerability models. They’re all slightly different since the country model can be more fine-tuned to the drivers in that particular area. Regional (continental) and global have more spatially consistent model weights. Which should you use? If you’re analyzing one country or want to make accurate comparisons between countries, use the country level. If mapping larger patterns, use the global or regional extent (depending on your area of interest). Land Cover 2050 - GlobalLand Cover 2050 - RegionalLand Cover 2050 - CountryLand Cover Vulnerability to Change 2050 GlobalLand Cover Vulnerability to Change 2050 RegionalLand Cover Vulnerability to Change 2050 CountryWhat these layers model (and what they don’t model)The model focuses on human-based land cover changes and projects the extent of these changes to the year 2050. It seeks to find where agricultural and urban land cover will cover the planet in that year, and what areas are most vulnerable to change due to the expansion of the human footprint. It does not predict changes to other land cover types such as forests or other natural vegetation during that time period unless it is replaced by agriculture or urban land cover. It also doesn’t predict sea level rise unless the model detected a pattern in changes in bodies of water between 2010 and 2018. A few 300m pixels might have changed due to sea level rise during that timeframe, but not many.The model predicts land cover changes based upon patterns it found in the period 2010-2018. But it cannot predict future land use. This is partly because current land use is not necessarily a model input. In this model, land set aside as a result of political decisions, for example military bases or nature reserves, may be found to be filled in with urban or agricultural areas in 2050. This is because the model is blind to the political decisions that affect land use.Quantitative Variables used to create ModelsBiomassCrop SuitabilityDistance to AirportsDistance to Cropland 2010Distance to Primary RoadsDistance to RailroadsDistance to Secondary RoadsDistance to Settled AreasDistance to Urban 2010ElevationGDPHuman Influence IndexPopulation DensityPrecipitationRegions SlopeTemperatureQualitative Variables used to create ModelsBiomesEcoregionsIrrigated CropsProtected AreasProvincesRainfed CropsSoil ClassificationSoil DepthSoil DrainageSoil pHSoil TextureWere small countries modeled?Clark University modeled some small countries that had a few transitions. Only five countries were modeled with this procedure: Bhutan, North Macedonia, Palau, Singapore and Vanuatu.As a rule of thumb, the MLP neural network in the Land Change Modeler requires at least 100 pixels of change for model calibration. Several countries experienced less than 100 pixels of change between 2010 & 2018 and therefore required an alternate modeling methodology. These countries are Bhutan, North Macedonia, Palau, Singapore and Vanuatu. To overcome the lack of samples, these select countries were resampled from 300 meters to 150 meters, effectively multiplying the number of pixels by four. As a result, we were able to empirically model countries which originally had as few as 25 pixels of change.Once a selected country was resampled to 150 meter resolution, three transition potential images were calibrated and averaged to produce one final transition potential image per transition. Clark Labs chose to create averaged transition potential images to limit artifacts of model overfitting. Though each model contained at least 100 samples of "change", this is still relatively little for a neural network-based model and could lead to anomalous outcomes. The averaged transition potentials were used to extrapolate change and produce a final hard prediction and risk map of natural land cover conversion to Cropland and Artificial Surfaces in 2050.39 Small Countries Not ModeledThere were 39 countries that were not modeled because the transitions, if any, from natural to anthropogenic were very small. In this case the land cover for 2050 for these countries are the same as the 2018 maps and their vulnerability was given a value of 0. Here were the countries not modeled:AndorraAntigua and BarbudaBarbadosCape VerdeComorosCook IslandsDjiboutiDominicaFaroe IslandsFrench GuyanaFrench PolynesiaGibraltarGrenadaGuamGuyanaIcelandJan MayenKiribatiLiechtensteinLuxembourgMaldivesMaltaMarshall IslandsMicronesia, Federated States ofMoldovaMonacoNauruSaint Kitts and NevisSaint LuciaSaint Vincent and the GrenadinesSamoaSan MarinoSeychellesSurinameSvalbardThe BahamasTongaTuvaluVatican CityIndex to land cover values in this dataset:The Clark University Land Cover 2050 projections display a ten-class land cover generalized from ESA Climate Change Initiative Land Cover. 1 Mostly Cropland2 Grassland, Scrub, or Shrub3 Mostly Deciduous Forest4 Mostly Needleleaf/Evergreen Forest5 Sparse Vegetation6 Bare Area7 Swampy or Often Flooded Vegetation8 Artificial Surface or Urban Area9 Surface Water10 Permanent Snow and Ice