Explore the state of democracy across Africa with data sourced from Stears’ Open Data. This interactive map visualizes the ages of uninterrupted democracy in African countries, helping you understand democratic rights, political trends, and governance across the continent.

This layer shows the overall 2016 Environmental Democracy Index for 70 countries around the world. The map also shows the total population of each country for reference.The Environmental Democracy Index is an average of three overall pillars: transparency, participation, and justice. These pillars are made up of 23 guidelines adopted by the United Nations Environment Programme (UNEP), which are arithmetic averages of 75 legal indicators. As described on the Background and Methodology page, the Environmental Democracy Index rides on the following:"Environmental democracy is rooted in the idea that meaningful public participation is critical to ensure that land and natural resource decisions adequately and equitably address citizens’ interests. At its core, environmental democracy involves three mutually reinforcing rights:the right to freely access information on environmental quality and problemsthe right to participate meaningfully in decision-makingthe right to seek enforcement of environmental laws or compensation for harm.Protecting these rights, especially for the most marginalized and vulnerable, is the first step to promoting equity and fairness in sustainable development. Without essential rights, information exchange between governments and the public is stifled and decisions that harm communities and the environment cannot be challenged or remedied. Establishing a strong legal foundation is the starting point for recognizing, protecting and enforcing environmental democracy. "The population estimate comes from the Esri 2016 World Population Estimate.

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

Environmental Democracy Index (EDI) consists of 75 legal indicators developed under 23 of the UNEP Bali Guidelines that are concerned with the development and implementation of legislation. In addition to the legal indicators, EDI includes 24 supplemental indicators that assess whether there is evidence that environmental democracy is being implemented in practice. The EDI legal indicators assess laws, constitutions, regulations and other legally binding, enforceable rules at the national level scores. TRANSPARENCY Pillar contains following Guidelines:- Guideline 1: "Accessibility of Environmental Information Requests" ? Guideline 2: "Environmental Information in Public Domain" ? Guideline 3: "Grounds for Refusal" ? Guideline 4: "Environmental Information Collection and Management" ? Guideline 5: "State of the Environment Report" ? Guideline 6: "Early Warning Information" ? Guideline 7: "Capacity-building for access to information (There are no indicators for this guideline)" Quality/Lineage: The data is downloaded from the above link http://environmentaldemocracyindex.org/rank-countries#all and manipulated only table format keeping the value same for all the countries as the requirement of the Strive database. The map is created based on the values of the country using rworldmap package in R.

This activity uses Map Viewer. ResourcesMapTeacher guide Student worksheetGet startedOpen the map.Use the teacher guide to explore the map with your class or have students work through it on their own with the worksheet.New to GeoInquiriesTM? See Getting to Know GeoInquiries.Social Studies standardsC3: D2.Civ.8.9-12 – Evaluate social and political systems in different contexts, times, and places that promote civic virtues and enact democratic principles.C3: D2.Civ.2.9-12 – Analyze the role of citizens in the U.S. political system, with attention to various theories of democracy, changes in Americans’ participation over time, and alternative models from other countries, past and present.C3: D2.Civ.4.9-12 – Explain how the U.S. Constitution establishes a system of government that has powers, responsibilities, and limits that have changed over time and that are still contested.Learning outcomesStudents will explain where philosophical ideals regarding our government originated, and how they have been incorporated into the U.S. Constitution.More activitiesAll Government GeoInquiriesAll GeoInquiries

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator)

-Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method.
-Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method.

Data for earlier dates is available directly from WorldPop.

WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674

The Covid-19 pandemic was a stress test to democracies. To date, literature lacks a comprehensive assessment of the political legitimacy of governments’ crisis responses in the context of multi-level political decision-making systems. LEGITIMULT aims to fill this gap in literature by analyzing the relationship between multilevel governance and political legitimacy from different angles. Work package 3 focuses on the role of democratic participation and the rule of law in a politically legitimate crisis governance. This working paper aims to develop a model of a democratic crisis governance and its empirical indicators based on the example of the Covid19 crisis. Thereby, it draws on the insights from a review of the extant literature on the democratic quality of the Covid-19 crisis governance. In addition, it presents an overview of the available datasets which assess the democratic quality and political legitimacy of governments’ Covid-19 crisis responses. Finally, it formulates first ideas on case selection for more in-depth analyses. Thus, this first deliverable provides the conceptual foundations of work package 3. Based on the suggested conceptualization and indicators of a democratic crisis governance, we will map the democratic quality of the Covid-19 crisis governance in 31 countries. To study the patterns of the results of this mapping, we will select a set of countries for an in-depth analysis of the impact of multi-level governance on the political legitimacy of Covid-19 crisis governance.

This activity uses Map Viewer. ResourcesMapTeacher guide Student worksheetGet startedOpen the map.Use the teacher guide to explore the map with your class or have students work through it on their own with the worksheet.New to GeoInquiriesTM? See Getting to Know GeoInquiries.Social Studies standardsC3: D2.Civ.2.3-5 – Explain how a democracy relies on people’s responsible participation, and draws implications for how individuals should participate. C3:D2.Civ.2.9-12 – Analyze the role of citizens in the U.S. political system, with attention to various theories of democracy, changes in Americans’ participation over time, and alternative models from other countries, past and present.Learning outcomesStudents will compare voter participation rates for presidential and congressional elections.Students will examine reasons for not voting and characteristics of those who vote.More activitiesAll Government GeoInquiriesAll GeoInquiries

Abstract

Round 1 of the Afrobarometer survey was conducted from July 1999 through June 2001 in 12 African countries, to solicit public opinion on democracy, governance, markets, and national identity. The full 12 country dataset released was pieced together out of different projects, Round 1 of the Afrobarometer survey,the old Southern African Democracy Barometer, and similar surveys done in West and East Africa.

The 7 country dataset is a subset of the Round 1 survey dataset, and consists of a combined dataset for the 7 Southern African countries surveyed with other African countries in Round 1, 1999-2000 (Botswana, Lesotho, Malawi, Namibia, South Africa, Zambia and Zimbabwe). It is a useful dataset because, in contrast to the full 12 country Round 1 dataset, all countries in this dataset were surveyed with the identical questionnaire

Geographic coverage

Botswana Lesotho Malawi Namibia South Africa Zambia Zimbabwe

Analysis unit

Basic units of analysis that the study investigates include: individuals and groups

Kind of data

Sample survey data [ssd]

Sampling procedure

A new sample has to be drawn for each round of Afrobarometer surveys. Whereas the standard sample size for Round 3 surveys will be 1200 cases, a larger sample size will be required in societies that are extremely heterogeneous (such as South Africa and Nigeria), where the sample size will be increased to 2400. Other adaptations may be necessary within some countries to account for the varying quality of the census data or the availability of census maps.

The sample is designed as a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of selection for interview. We strive to reach this objective by (a) strictly applying random selection methods at every stage of sampling and by (b) applying sampling with probability proportionate to population size wherever possible. A randomly selected sample of 1200 cases allows inferences to national adult populations with a margin of sampling error of no more than plus or minus 2.5 percent with a confidence level of 95 percent. If the sample size is increased to 2400, the confidence interval shrinks to plus or minus 2 percent.

Sample Universe

The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

What to do about areas experiencing political unrest? On the one hand we want to include them because they are politically important. On the other hand, we want to avoid stretching out the fieldwork over many months while we wait for the situation to settle down. It was agreed at the 2002 Cape Town Planning Workshop that it is difficult to come up with a general rule that will fit all imaginable circumstances. We will therefore make judgments on a case-by-case basis on whether or not to proceed with fieldwork or to exclude or substitute areas of conflict. National Partners are requested to consult Core Partners on any major delays, exclusions or substitutions of this sort.

Sample Design

The sample design is a clustered, stratified, multi-stage, area probability sample.

To repeat the main sampling principle, the objective of the design is to give every sample element (i.e. adult citizen) an equal and known chance of being chosen for inclusion in the sample. We strive to reach this objective by (a) strictly applying random selection methods at every stage of sampling and by (b) applying sampling with probability proportionate to population size wherever possible.

In a series of stages, geographically defined sampling units of decreasing size are selected. To ensure that the sample is representative, the probability of selection at various stages is adjusted as follows:

The sample is stratified by key social characteristics in the population such as sub-national area (e.g. region/province) and residential locality (urban or rural). The area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. And the urban/rural stratification is a means to make sure that these localities are represented in their correct proportions. Wherever possible, and always in the first stage of sampling, random sampling is conducted with probability proportionate to population size (PPPS). The purpose is to guarantee that larger (i.e., more populated) geographical units have a proportionally greater probability of being chosen into the sample. The sampling design has four stages

A first-stage to stratify and randomly select primary sampling units;

A second-stage to randomly select sampling start-points;

A third stage to randomly choose households;

A final-stage involving the random selection of individual respondents

We shall deal with each of these stages in turn.

STAGE ONE: Selection of Primary Sampling Units (PSUs)

The primary sampling units (PSU's) are the smallest, well-defined geographic units for which reliable population data are available. In most countries, these will be Census Enumeration Areas (or EAs). Most national census data and maps are broken down to the EA level. In the text that follows we will use the acronyms PSU and EA interchangeably because, when census data are employed, they refer to the same unit.

We strongly recommend that NIs use official national census data as the sampling frame for Afrobarometer surveys. Where recent or reliable census data are not available, NIs are asked to inform the relevant Core Partner before they substitute any other demographic data. Where the census is out of date, NIs should consult a demographer to obtain the best possible estimates of population growth rates. These should be applied to the outdated census data in order to make projections of population figures for the year of the survey. It is important to bear in mind that population growth rates vary by area (region) and (especially) between rural and urban localities. Therefore, any projected census data should include adjustments to take such variations into account.

Indeed, we urge NIs to establish collegial working relationships within professionals in the national census bureau, not only to obtain the most recent census data, projections, and maps, but to gain access to sampling expertise. NIs may even commission a census statistician to draw the sample to Afrobarometer specifications, provided that provision for this service has been made in the survey budget.

Regardless of who draws the sample, the NIs should thoroughly acquaint themselves with the strengths and weaknesses of the available census data and the availability and quality of EA maps. The country and methodology reports should cite the exact census data used, its known shortcomings, if any, and any projections made from the data. At minimum, the NI must know the size of the population and the urban/rural population divide in each region in order to specify how to distribute population and PSU's in the first stage of sampling. National investigators should obtain this written data before they attempt to stratify the sample.

Once this data is obtained, the sample population (either 1200 or 2400) should be stratified, first by area (region/province) and then by residential locality (urban or rural). In each case, the proportion of the sample in each locality in each region should be the same as its proportion in the national population as indicated by the updated census figures.

Having stratified the sample, it is then possible to determine how many PSU's should be selected for the country as a whole, for each region, and for each urban or rural locality.

The total number of PSU's to be selected for the whole country is determined by calculating the maximum degree of clustering of interviews one can accept in any PSU. Because PSUs (which are usually geographically small EAs) tend to be socially homogenous we do not want to select too many people in any one place. Thus, the Afrobarometer has established a standard of no more than 8 interviews per PSU. For a sample size of 1200, the sample must therefore contain 150 PSUs/EAs (1200 divided by 8). For a sample size of 2400, there must be 300 PSUs/EAs.

These PSUs should then be allocated proportionally to the urban and rural localities within each regional stratum of the sample. Let's take a couple of examples from a country with a sample size of 1200. If the urban locality of Region X in this country constitutes 10 percent of the current national population, then the sample for this stratum should be 15 PSUs (calculated as 10 percent of 150 PSUs). If the rural population of Region Y constitutes 4 percent of the current national population, then the sample for this stratum should be 6 PSU's.

The next step is to select particular PSUs/EAs using random methods. Using the above example of the rural localities in Region Y, let us say that you need to pick 6 sample EAs out of a census list that contains a total of 240 rural EAs in Region Y. But which 6? If the EAs created by the national census bureau are of equal or roughly equal population size, then selection is relatively straightforward. Just number all EAs consecutively, then make six selections using a table of random numbers. This procedure, known as simple random sampling (SRS), will

Data collected and prepared from the Democratic Republic of Congo Power–Mining Map, for a WBG open knowledge repository book The Power of the Mine A Transformative Opportunity for Sub-Saharan Africa. Citation: “Banerjee, Sudeshna Ghosh; Romo, Zayra; McMahon, Gary; Toledano, Perrine; Robinson, Peter; Pérez Arroyo, Inés. 2015. The Power of the Mine : A Transformative Opportunity for Sub-Saharan Africa. Directions in DevelopmentEnergy and Mining;. Washington, DC: World Bank. © World Bank. https://openknowledge.worldbank.org/handle/10986/21402 License: CC BY 3.0 IGO.” This data is based on a digitized PDF map, and so is intended as a schematic of rough locations of the power network. It is not suitable for applications requiring high accuracy.

Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. This dataset provides index values for small spatial units within urban areas in Democratic Republic of the Congo. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.

In the aftermath of the German Federal Election of 2025, the CDU were polling at around 28 percent of the vote as of March 7, 2025, with the party receiving 28.5 percent of the vote in the election held the previous month. The Ampel's woes continue in 2024 The Ampel coalition came to power in 2021 due to the surprise surge in support for the Social Democrats, who secured almost 26 percent of the vote in that election. Unwilling to re-enter a 'grand coalition' with the Christian Democrats, the SPD instead opted to create a coalition with the center-left environmentalist party, the Greens, and the free-market neoliberal party, the FDP. This unlikely coalition which promised to "dare to make more progress" (mehr Fortschritt wagen) has instead been mired by constant infighting between the three parties, as well as being hit by several external crises, most notably Russia's war of aggression against Ukraine. At the same time, the German economy's post-pandemic recovery has faltered, with the country being one of the few European countries to experience a recession in 2023, while one of the government's key economic plans - a special investment fund designed to bypass the constitutional debt brake - was struck down by the constitutional court in Karlsruhe. These factors have led to consistently declining support for the three governing parties, with the latest poll showing their combined share of the vote being only 33 percent, slightly more than the vote share of the Christian Democrats. While the Greens' vote share would remain roughly equal to what they achieved in 2021, the popularity of the SPD and FDP has collapsed compared to their 2021 levels. The Social Democrats are now the third most popular party in Germany, with Chancellor Olaf Scholz's party on track to achieve their worst election result since 1887. The Liberals (FDP), on the other hand, look likely to not gain any seats in the parliament at all in the next election, as they are currently falling below the five percent threshold to enter the Bundestag (federal parliament). The rise of the far-right in German politics The Ampel's loss has been the far-right's gain, as the Alternative for Germany (AfD) party has seen its fortunes rise consistently in opinion polls since the 2021 election. The party was originally founded to oppose plans for the EU to provide bailouts to struggling member states during the Eurozone debt crisis in the early 2010s, however, following the 2015 Syrian refugee crisis the party pivoted towards a hardline anti-immigration stance. Since then, the AfD has drifted consistently to the right, with one of the dominant factions, known as Der Flügel ("the wing"), being labelled far-right extremists and even, in some cases, fascists. While the federal-level party is currently led by Alice Weidel and Tino Chrupulla, members of the more moderate faction of the party, at the regional-level the party is often led by more extreme figures, such as in the state of Thuringia where party leader Björn Höcke has been labelled in the media as a far-right extremist. In January 2024, an article by investigative journalists brought to light secret meetings between AfD members and far-right supporters to discuss plans for mass deportations of foreigners from Germany, were the AfD to come to power. The scandal led to the largest street protests in the country so far this century, with estimates showing as many as 1.4 million people turning out across the country. Some protesters have even gone so far as to call for a constitutional ban against the AfD, claiming that they pose a threat to German democracy. The party suffered a drop in support in the aftermath of the scandal, with their share of prospective voters declining by four percent from their high-point in January of 2024. The Alternative for Germany currently is the party of choice for 18 percent of German voters, which would make them the second largest party in parliament after the Christian Democrats. While no other party currently says they would work with the AfD on a national level, this Brandmauer ("fire wall") may be tested in regional parliaments during 2024, as the party looks set to come first in several states in East Germany during the year.

This map highlights 8962 stations with monthly discharge data, including data derived daily up to 20 December 2013. The GRDB (Global Runoff DataBase) is built on an initial dataset collected in the early 1980s from the responses to WMO (World Meteorological Organization request to its member countries to provide a global hydrological data set to complement a specific set of atmospheric data in the framework of the First Global GARP Experiment (FCGE). The initial dataset of monthly river discharge data over a period of several years around 1980 was supplemented with the UNESCO monthly river discharge data collection 1965-85. Today the database comprises discharge data of nearly 9.000 gauging stations from all over the world. Since 1993 the total number of station-years has increased by a factor of around 10.Credits and partnerships:OSU - College of Earth, Ocean and Atmospheric SciencesCarniege Corporation of New YGloabl orkNASCE - Northwest Alliance for Computational Science & EngineeringInternational Water Management InstituteUNESCO - United Nations Educational, Scientific and Cultural OrganisationUSGS - United States Geological Survey