Human Development Index by country for 2013. This is a filtered layer based on the "Human Development Index by country, 1980-2010 time-series" layer.The Human Development Index measures achievement in 3 areas of human development: long life, good education and income. Specifically, the index is computed using life expectancy at birth, Mean years of schooling, expected years of schooling, and gross national income (GNI) per capita (PPP $).The United Nations categorizes the HDI values into 4 groups. In 2013 these groups were defined by the following HDI values:

Very High Human Development: 0.736 and higher High Human Development: 0.615 to 0.735 Medium Human Development: 0.494 to 0.614 Low Human Development: 0.493 and lower

Country shapes from Natural Earth 50M scale data. Human Development Index attributes are from The World Bank: HDRO calculations based on data from UNDESA (2013a), Barro and Lee (2013), UNESCO Institute for Statistics (2013), UN Statistics Division (2014), World Bank (2014) and IMF (2014).

******* had the highest level of the Human Development Index (HDI) worldwide in 2023 with a value of *****. With a score of ****, ****** followed closely behind *********** and had the second-highest level of human development in that year. The rise of the Asian tigers In the decades after the Cold War, the four so-called Asian tigers, South Korea, Singapore, Taiwan, and Hong Kong (now a Special Administrative Region of China) experienced rapid economic growth and increasing human development. At number eight and number 13 of the HDI, respectively, *********************** are the only Asian locations within the top-15 highest HDI scores. Both locations have experienced tremendous economic growth since the 1980’s and 1990’s. In 1980, the per capita GDP of Hong Kong was ***** U.S. dollars, increasing throughout the decades until reaching ****** in 2023, which is expected to continue to increase in the future. Meanwhile, in 1989, Singapore had a GDP of nearly ** billion U.S. dollars, which has risen to nearly *** billion U.S. dollars today and is also expected to keep increasing. Growth of the UAE The United Arab Emirates (UAE) is the only Middle Eastern country besides Israel within the highest ranking HDI scores globally. Within the Middle East and North Africa (MENA) region, the UAE has the third-largest GDP behind Saudi Arabia and Israel, reaching nearly *** billion U.S. dollars by 2022. Per capita, the UAE GDP was around ****** U.S. dollars in 1989, and has nearly doubled to ****** U.S. dollars by 2021. Moreover, this is expected to reach over ****** U.S. dollars by 2029. On top of being a major oil producer, the UAE has become a hub for finance and business and attracts millions of tourists annually.

Countries from Natural Earth 50M scale data with a Human Development Index attribute, repeated for each of the following years: 1980, 1985, 1990, 1995, 2000, 2005, 2010, & 2013, to enable time-series display using the YEAR attribute. The Human Development Index measures achievement in 3 areas of human development: long life, good education and income. Specifically, the index is computed using life expectancy at birth, Mean years of schooling, expected years of schooling, and gross national income (GNI) per capita (PPP $). The United Nations categorizes the HDI values into 4 groups. In 2013 these groups were defined by the following HDI values: Very High: 0.736 and higher High: 0.615 to 0.735 Medium: 0.494 to 0.614 Low: 0.493 and lower

Human Development Index attributes are from The World Bank: HDRO calculations based on data from UNDESA (2013a), Barro and Lee (2013), UNESCO Institute for Statistics (2013), UN Statistics Division (2014), World Bank (2014) and IMF (2014).

Compared to other African countries, Seychelles scored the highest in the Human Development Index (HDI) in 2022. The country also ranked 67th globally, as one of the countries with a very high human development. This was followed by Mauritius, Libya, Egypt, and Tunisia, with scores ranging from 0.80 to 0.73 points. On the other hand, Central African Republic, South Sudan, and Somalia were among the countries in the region with the lowest index scores, indicating a low level of human development.

This activity uses interactive web maps to visualise and explore the human development index (HDI), crime rates, fertility rates, gender inequality, and economic indicators. The patterns that you see in these web maps will help to shape your understanding of global development patterns and the impact they have on people.Read through the material and answer the questions in yellow.

The Gross Domestic Product per capita (gross domestic product divided by mid-year population converted to international dollars, using purchasing power parity rates) has been identified as an important determinant of susceptibility and vulnerability by different authors and used in the Disaster Risk Index 2004 (Peduzzi et al. 2009, Schneiderbauer 2007, UNDP 2004) and is commonly used as an indicator for a country's economic development (e.g. Human Development Index). Despite some criticisms (Brooks et al. 2005) it is still considered useful to estimate a population's susceptibility to harm, as limited monetary resources are seen as an important factor of vulnerability. However, collection of data on economic variables, especially sub-national income levels, is problematic, due to various shortcomings in the data collection process. Additionally, the informal economy is often excluded from official statistics. Night time lights satellite imagery of NOAA grid provides an alternative means for measuring economic activity. NOAA scientists developed a model for creating a world map of estimated total (formal plus informal) economic activity. Regression models were developed to calibrate the sum of lights to official measures of economic activity at the sub-national level for some target Country and at the national level for other countries of the world, and subsequently regression coefficients were derived. Multiplying the regression coefficients with the sum of lights provided estimates of total economic activity, which were spatially distributed to generate a 30 arc-second map of total economic activity (see Ghosh, T., Powell, R., Elvidge, C. D., Baugh, K. E., Sutton, P. C., & Anderson, S. (2010).Shedding light on the global distribution of economic activity. The Open Geography Journal (3), 148-161). We adjusted the GDP to the total national GDPppp amount as recorded by IMF (International Monetary Fund) for 2010 and we divided it by the population layer from Worldpop Project. Further, we ran a focal statistics analysis to determine mean values within 10 cell (5 arc-minute, about 10 Km) of each grid cell. This had a smoothing effect and represents some of the extended influence of intense economic activity for local people. Finally we apply a mask to remove the area with population below 1 people per square Km.

This dataset has been produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 4 (WP4). More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

Data publication: 2014-06-01

Supplemental Information:

ClimAfrica was an international project funded by European Commission under the 7th Framework Programme (FP7) for the period 2010-2014. The ClimAfrica consortium was formed by 18 institutions, 9 from Europe, 8 from Africa, and the Food and Agriculture Organization of United Nations (FAO).

ClimAfrica was conceived to respond to the urgent international need for the most appropriate and up-to-date tools and methodologies to better understand and predict climate change, assess its impact on African ecosystems and population, and develop the correct adaptation strategies. Africa is probably the most vulnerable continent to climate change and climate variability and shows diverse range of agro-ecological and geographical features. Thus the impacts of climate change can be very high and can greatly differ across the continent, and even within countries.

The project focused on the following specific objectives:

1. Develop improved climate predictions on seasonal to decadal climatic scales, especially relevant to SSA;

2. Assess climate impacts in key sectors of SSA livelihood and economy, especially water resources and agriculture;

3. Evaluate the vulnerability of ecosystems and civil population to inter-annual variations and longer trends (10 years) in climate;

4. Suggest and analyse new suited adaptation strategies, focused on local needs;

5. Develop a new concept of 10 years monitoring and forecasting warning system, useful for food security, risk management and civil protection in SSA;

6. Analyse the economic impacts of climate change on agriculture and water resources in SSA and the cost-effectiveness of potential adaptation measures.

The work of ClimAfrica project was broken down into the following work packages (WPs) closely connected. All the activities described in WP1, WP2, WP3, WP4, WP5 consider the domain of the entire South Sahara Africa region. Only WP6 has a country specific (watershed) spatial scale where models validation and detailed processes analysis are carried out.

Contact points:

Metadata Contact: FAO-Data

Resource Contact: Selvaraju Ramasamy

Resource constraints:

copyright

Online resources:

GDP per capita

Project deliverable D4.1 - Scenarios of major production systems in Africa

Climafrica Website - Climate Change Predictions In Sub-Saharan Africa: Impacts And Adaptations

Human development index of Mali decreased by 3.33% from 0.42 score in 2019 to 0.41 score in 2020. Since the 0.70% rise in 2018, human development index dropped by 5.35% in 2020. A composite index measuring average achievement in three basic dimensions of human development—a long and healthy life, knowledge and a decent standard of living

Countries from Natural Earth 50M scale data with a Human Development Index attribute for each of the following years: 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2013, 2015, & 2017. The Human Development Index measures achievement in 3 areas of human development: long life, good education and income. Specifically, the index is computed using life expectancy at birth, Mean years of schooling, expected years of schooling, and gross national income (GNI) per capita (PPP $). The United Nations categorizes the HDI values into 4 groups. In 2013 these groups were defined by the following HDI values: Very High: 0.736 and higher High: 0.615 to 0.735 Medium: 0.494 to 0.614 Low: 0.493 and lower

In 2015 & 2017 these groups were defined by the following HDI values: Very High: 0.800 and higher High: 0.700 to 0.799 Medium: 0.550 to 0.699 Low: 0.549 and lower

Human Development Index attributes are from The World Bank: HDRO calculations based on data from UNDESA (2013a), Barro and Lee (2013), UNESCO Institute for Statistics (2013), UN Statistics Division(2014), World Bank (2014) and IMF (2014). 2015 & 2017 values source: HDRO calculations based on data from UNDESA (2017a), UNESCO Institute for Statistics (2018), United Nations Statistics Division (2018b), World Bank (2018b), Barro and Lee (2016) and IMF (2018).

Population data are from (1) United Nations Population Division. World Population Prospects, (2) United Nations Statistical Division. Population and Vital Statistics Report (various years), (3) Census reports and other statistical publications from national statistical offices, (4) Eurostat: Demographic Statistics, (5) Secretariat of the Pacific Community: Statistics and Demography Programme, and (6) U.S. Census Bureau: International Database.

ම ය ම නව ස වර ධන දර ශකය අන ව රටවල ල ය ස ත වක World map of countries by Human Development Index categories in increments

Human development index of Paraguay decreased by 0.54% from 0.75 score in 2019 to 0.74 score in 2020. Since the 0.14% rise in 2018, human development index rose by 2.06% in 2020. A composite index measuring average achievement in three basic dimensions of human development—a long and healthy life, knowledge and a decent standard of living. 1=the most developed.

In this lesson, students will create a map to present components of the HDI and to consider how they relate to assessing quality of life around the world. You will use the built-in geoprocessing tools in ArcGIS Online to perform analysis that shows how these indicators work together to provide a comprehensive snapshot of life quality.Learning Outcomes:By completing this lesson, students will gain the following curriculum-focused knowledge:

1. Understanding the interrelationships between population distribution, population density, and quality of life.

(Ontario – Grade 12 Geography; British Columbia – Grade 11 Social Studies; Alberta – Grade 9 Social Studies; Manitoba – Grade 7 Social Studies, Grade 12 Social Studies; New Brunswick – Grade 12 Geography; Nova Scotia – Grade 8 Social Studies, Grade 12 Geography; Prince Edward Island – Grade 9 Social Studies, Grade 12 Social Studies; Newfoundland & Labrador – Grade 10 Geography, Grade 12 Geography; Saskatchewan – Grade 7 Social Studies; Northwest Territories – Grade 9 Social Studies; Yukon– Grade 11 Social Studies)

1. Using indicators and other criteria to classify countries into a variety of groupings on the basis of common characteristics.

(Ontario – Grade 12 Geography; British Columbia – Grade 11 Social Studies; Alberta – Grade 9 Social Studies; Manitoba – Grade 7 Social Studies, Grade 12 Social Studies; New Brunswick – Grade 12 Geography; Nova Scotia – Grade 8 Social Studies, Grade 12 Geography; Prince Edward Island – Grade 9 Social Studies, Grade 12 Social Studies; Newfoundland & Labrador – Grade 10 Geography, Grade 12 Geography; Saskatchewan – Grade 7 Social Studies; Northwest Territories – Grade 9 Social Studies; Yukon – Grade 11 Social Studies)

1. Demonstrating an understanding of patterns in the factors that affect world economic development and quality of life in different regions of the world.

(Ontario – Grade 12 Geography; British Columbia – Grade 11 Social Studies; Alberta – Grade 9 Social Studies; Manitoba – Grade 7 Social Studies, Grade 12 Social Studies; New Brunswick – Grade 12 Geography; Nova Scotia – Grade 8 Social Studies, Grade 12 Geography; Prince Edward Island – Grade 9 Social Studies, Grade 12 Social Studies; Newfoundland & Labrador – Grade 10 Geography, Grade 12 Geography; Saskatchewan – Grade 7 Social Studies; Northwest Territories – Grade 9 Social Studies; Yukon– Grade 11 Social Studies)

The FGGD degree of human development map is a global vector datalayer at scale 1:5 000 000. The map depicts national statistical data and highlights differences among countries with respect to the human development index for the year 2000. Data are from UNDP, 2002, Human Development Report.

Human development index of Colombia decreased by 1.56% from 0.77 score in 2019 to 0.76 score in 2020. Since the 0.39% rise in 2017, human development index fell by 0.92% in 2020. A composite index measuring average achievement in three basic dimensions of human development—a long and healthy life, knowledge and a decent standard of living. 1=the most developed.

0,51 (Punktzahl, höchste Punktzahl = beste Punktzahl) in 2020. A composite index measuring average achievement in three basic dimensions of human development—a long and healthy life, knowledge and a decent standard of living. 1=the most developed.

Human development index of China increased by 0.77% from 0.78 score in 2019 to 0.78 score in 2020. Since the 1.60% rise in 2010, human development index surged by 11.89% in 2020. A composite index measuring average achievement in three basic dimensions of human development—a long and healthy life, knowledge and a decent standard of living

0,63 (Punktzahl, höchste Punktzahl = beste Punktzahl) in 2020. A composite index measuring average achievement in three basic dimensions of human development—a long and healthy life, knowledge and a decent standard of living. 1=the most developed.

Human development index of Turkey decreased by 0.83% from 0.84 score in 2019 to 0.84 score in 2020. Since the 3.07% rise in 2018, human development index fell by 0.48% in 2020. A composite index measuring average achievement in three basic dimensions of human development—a long and healthy life, knowledge and a decent standard of living. 1=the most developed.

0,79 (Punktzahl, höchste Punktzahl = beste Punktzahl) in 2020. A composite index measuring average achievement in three basic dimensions of human development—a long and healthy life, knowledge and a decent standard of living. 1=the most developed.

Human development index of Micronesia (Federated States of) decreased by 0.62% from 0.64 score in 2019 to 0.64 score in 2020. Since the 2.76% rise in 2018, human development index rose by 0.47% in 2020. A composite index measuring average achievement in three basic dimensions of human development—a long and healthy life, knowledge and a decent standard of living

0,48 (Punktzahl, höchste Punktzahl = beste Punktzahl) in 2020. Ein zusammengesetzter Index, der den durchschnittliche Fortschritt dreier grundlegender Dimensionen der menschlichen Entwicklung misst - ein langes und gesundes Leben, Wissen und einen annehmbaren Lebensstandard