Proportion of population in Pacific Island Countries and Territories (PICTs) living in Low Elevation Coastal Zones (LECZ) of 0-10 and 0-20 meters above sea level. LECZ were delineated using the bathub method overlaid on the Advanced Land Observing Satellite (ALOS) Global Digital Surface Model (AW3D30). Populations within the LECZs were estimated using the Pacific Community (SPC) Statistics for Development Division’s 100m2 population grids.

Find more Pacific data on PDH.stat.

Ivory Coast CI: Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data was reported at 3.765 % in 2010. This records an increase from the previous number of 3.640 % for 2000. Ivory Coast CI: Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data is updated yearly, averaging 3.765 % from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 3.874 % in 1990 and a record low of 3.640 % in 2000. Ivory Coast CI: Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank.WDI: Land Use, Protected Areas and National Wealth. Population below 5m is the percentage of the total population living in areas where the elevation is 5 meters or less.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Weighted average;

Ivory Coast CI: Rural Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data was reported at 0.228 % in 2010. This records a decrease from the previous number of 0.233 % for 2000. Ivory Coast CI: Rural Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data is updated yearly, averaging 0.228 % from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 0.233 % in 2000 and a record low of 0.209 % in 1990. Ivory Coast CI: Rural Population Living in Areas Where Elevation is Below 5 Meters: % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank: Land Use, Protected Areas and National Wealth. Rural population below 5m is the percentage of the total population, living in areas where the elevation is 5 meters or less.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Weighted Average;

A collaborative project between SPC, the World Fish Centre and the University of Wollongong has produced the first detailed population estimates of people living close to the coast in the 22 Pacific Island Countries and Territories (PICTs). These estimates are stratified into 1, 5, and 10km zones. More information about this dataset: https://sdd.spc.int/mapping-coastal

Access this dataset from the Pacific Data Hub

Ivory Coast CI: Population: as % of Total: Male: Aged 15-64 data was reported at 54.805 % in 2017. This records an increase from the previous number of 54.729 % for 2016. Ivory Coast CI: Population: as % of Total: Male: Aged 15-64 data is updated yearly, averaging 54.032 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 55.430 % in 1960 and a record low of 53.589 % in 1982. Ivory Coast CI: Population: as % of Total: Male: Aged 15-64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank: Population and Urbanization Statistics. Male population between the ages 15 to 64 as a percentage of the total male population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average;

In 2023, Washington, D.C. had the highest population density in the United States, with 11,130.69 people per square mile. As a whole, there were about 94.83 residents per square mile in the U.S., and Alaska was the state with the lowest population density, with 1.29 residents per square mile. The problem of population density Simply put, population density is the population of a country divided by the area of the country. While this can be an interesting measure of how many people live in a country and how large the country is, it does not account for the degree of urbanization, or the share of people who live in urban centers. For example, Russia is the largest country in the world and has a comparatively low population, so its population density is very low. However, much of the country is uninhabited, so cities in Russia are much more densely populated than the rest of the country. Urbanization in the United States While the United States is not very densely populated compared to other countries, its population density has increased significantly over the past few decades. The degree of urbanization has also increased, and well over half of the population lives in urban centers.

This data base contains gridded (one degree by one degree) information on the world-wide distribution of the population for 1990 and country-specific information on the percentage of the country's population present in each grid cell (Li, 1996a). Secondly, the data base contains the percentage of a country's total area in a grid cell and the country's percentage of the grid cell that is terrestrial (Li, 1996b). Li (1996b) also developed an indicator signifying how many countries are represented in a grid cell and if a grid cell is part of the sea; this indicator is only relevant for the land, countries, and sea-partitioning information of the grid cell. Thirdly, the data base includes the latitude and longitude coordinates of each grid cell; a grid code number, which is a translation of the latitude/longitude value and is used in the Global Emission Inventory Activity (GEIA) data bases; the country or region's name; and the United Nations three-digit country code that represents that name. For access to the data files, click this link to the CDIAC data transition website: http://cdiac.ess-dive.lbl.gov/ftp/db1016/

Ivory Coast CI: Population: Male: Ages 20-24: % of Male Population data was reported at 9.285 % in 2017. This records an increase from the previous number of 9.211 % for 2016. Ivory Coast CI: Population: Male: Ages 20-24: % of Male Population data is updated yearly, averaging 8.532 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 9.285 % in 2017 and a record low of 8.055 % in 1970. Ivory Coast CI: Population: Male: Ages 20-24: % of Male Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank: Population and Urbanization Statistics. Male population between the ages 20 to 24 as a percentage of the total male population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

VITAL SIGNS INDICATOR Vulnerability to Sea Level Rise (EN11)

FULL MEASURE NAME Share of population living in zones at risk from various sea level rise forecast scenarios

LAST UPDATED July 2017

DESCRIPTION Vulnerability to sea level rise refers to the share of the historical and current Bay Area population located in areas at risk from forecasted sea level rise over the coming decades. Given that there are varying forecasts for the heightened high tides (i.e., mean highest high water mark), projected sea level impacts are presented for six scenarios ranging from a one foot rise to six feet. A neighborhood is considered vulnerable to sea level rise when at least 10 percent of its land area is forecasted to be inundated by peak high tides in the coming years. The dataset includes at-risk population and population share data for the region, counties, and neighborhoods.

DATA SOURCE San Francisco Bay Conservation and Development Commission 2017 Sea Level Rise Maps http://www.adaptingtorisingtides.org/project/regional-sea-level-rise-mapping-and-shoreline-analysis/

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Projected areas of inundation were developed by BCDC and NOAA at one-foot intervals ranging from one foot to four feet of sea level rise. Regional and local sea level rise analysis is based on data from BCDC’s ART (Adapting to Rising Tides) Bay Area Sea Level Rise and Mapping Project. This data reflects the most up-to-date and detailed sea level rise mapping for the Bay Area. Sea level rise analysis for metro areas is based on national sea level rise mapping from NOAA, which is best for metro-to-metro comparison. To determine the impacts on historical and current populations, inundation areas were overlaid on a U.S. Census shapefile of 2010 Census tracts using Census Bureau population data.

Because census tracts can extend beyond the coastline, the baseline scenario of zero feet was used to determine existing sea level coverage of census tracts. Sea level rise refers to the change from this level. The area of the tract was determined by measuring the component of the tract area not currently under water. This area, rather than the total tract area, was used as the denominator to determine the percentage of the census tract that is inundated under future sea level rise projection scenarios. When at least 10 percent of tract land area is inundated with a given sea level, its residents are considered to be affected by sea level rise.

For the purpose of this analysis, SLR scenarios were assumed not to reflect periodic inundation due to extreme weather events, which may lead to an even greater share of residents affected on a less frequent basis. Prior to the impacts from sea level rise, neighborhoods will experience temporary flooding from extreme weather events which can create significant damage to homes and neighborhoods. It should be noted that by directly reviewing maps and tools through the ART (Adapting to Rising Tides) program, regular inundation sea level rise and temporary flooding from extreme weather events are both available. More information on this approach is available here: http://www.adaptingtorisingtides.org/project/regional-sea-level-rise-mapping-and-shoreline-analysis/

Sea level rise analysis for metro areas reflects local, as opposed to global, sea level rise. Recent data has shown sea level is rising faster in the southeast region of the United States. Regional differences in the rate of sea level rise. More information and data related to the rate of sea level rise for different coastal regions is available here: https://oceanservice.noaa.gov/facts/sealevel-global-local.html

Sea-level rise (SLR) due to climate change is a serious global threat: The scientific evidence is now overwhelming. Continued growth of greenhouse gas emissions and associated global warming could well promote SLR of 1m in this century, and unexpectedly rapid breakup of the Greenland and West Antarctic ice sheets might produce a 3-5m SLR. In this research, we have assessed the consequences of continued SLR for 84 coastal developing countries. Geographic Information System (GIS) software has been used to overlay the best available, spatially-disaggregated global data on critical impact elements (land, population, agriculture, urban extent, wetlands, and GDP), with the inundation zones projected for 1-5m SLR.Country-level impacts have been summarized in the Excel Workbook “SLR-Impacts”.The Excel Workbook is divided into Worksheets to match the major critical impact elements: land, population, GDP, agriculture, urban extent, and wetlands.Absolute impacts of 1-5m SLR are presented in Columns D-H.Percentage Impacts are presented in Columns I-M.Original data sources for assessments of impacts:DimensionDataset nameUnitResolutionSource(s)Coastline and country boundaryWVS1:250,000NOAA/NASAElevationSRTM 90m DEM V2km2 90mCIAT PopulationGPW-3Population counts1kmCIESINEconomic activityGDP2000million US dollars5kmWorld Bank, based on Sachs et al. (2001)Urban areasGRUMP V1km21kmCIESINAgricultural LandGAE-2km21kmIFPRI WetlandsGLWD-3km21kmCESR, Lehner, B. and Döll, P. (2004)Limitations of the research: The digital elevation (90m DEM V2) data used in this analysis gives altitude in 1-meter increments, preventing us from sub-meter SLR modeling. One can interpolate the elevation data we have used for sub-meter SLR modeling, but in that case, precision of the estimates would be difficult to justify. The potential use of LIDAR survey (laser-based elevation measurement from low-flying aircraft) was beyond scope of our analysis.Lack of spatially disaggregated secondary information on indicators prevented us from including small islands in this analysis.The impacts of SLR have been assessed using existing population, socio-economic conditions and patterns of land use, rather than attempting to predict their future states. Human activity is generally increasing more rapidly in coastal areas and thus the impacts of SLR will be more pronounced in these areas. This effect is countered by adaptation measures, which we also do not attempt to estimate in this exercise. Adaptation measures from the purely technological (e.g., sea defenses), to managerial (e.g., altering land-use planning, relocation), to policy (e.g., planning regulations) are often context, location and community-specific. Thus in our analysis, we refrain from generalizing any adaptive measures across our sub-set of developing countries.This research was carried out by the World Bank in 2006, and was funded by the Canadian Trust Fund (TF030569) sponsored by the Canadian International Development Agency (CIDA). Access to DatasetSLR dataset (MS Excel file, 205kb)

Ivory Coast CI: Population: as % of Total: Female data was reported at 49.343 % in 2017. This records an increase from the previous number of 49.295 % for 2016. Ivory Coast CI: Population: as % of Total: Female data is updated yearly, averaging 48.369 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 49.343 % in 2017 and a record low of 47.872 % in 1983. Ivory Coast CI: Population: as % of Total: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank.WDI: Population and Urbanization Statistics. Female population is the percentage of the population that is female. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average;

Ivory Coast CI: Population: Female: Ages 25-29: % of Female Population data was reported at 7.708 % in 2017. This records an increase from the previous number of 7.654 % for 2016. Ivory Coast CI: Population: Female: Ages 25-29: % of Female Population data is updated yearly, averaging 7.330 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 7.799 % in 1960 and a record low of 6.736 % in 1976. Ivory Coast CI: Population: Female: Ages 25-29: % of Female Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank: Population and Urbanization Statistics. Female population between the ages 25 to 29 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

Ivory Coast CI: Population: as % of Total: Male: Aged 0-14 data was reported at 42.034 % in 2017. This records a decrease from the previous number of 42.133 % for 2016. Ivory Coast CI: Population: as % of Total: Male: Aged 0-14 data is updated yearly, averaging 43.244 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 43.960 % in 1982 and a record low of 42.034 % in 2017. Ivory Coast CI: Population: as % of Total: Male: Aged 0-14 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank: Population and Urbanization Statistics. Male population between the ages 0 to 14 as a percentage of the total male population. Population is based on the de facto definition of population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average;

Ivory Coast CI: Population: Female: Ages 30-34: % of Female Population data was reported at 6.388 % in 2017. This records an increase from the previous number of 6.375 % for 2016. Ivory Coast CI: Population: Female: Ages 30-34: % of Female Population data is updated yearly, averaging 6.134 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 6.641 % in 1965 and a record low of 5.723 % in 1981. Ivory Coast CI: Population: Female: Ages 30-34: % of Female Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank: Population and Urbanization Statistics. Female population between the ages 30 to 34 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

Ivory Coast CI: Population: as % of Total: Male data was reported at 50.657 % in 2017. This records a decrease from the previous number of 50.705 % for 2016. Ivory Coast CI: Population: as % of Total: Male data is updated yearly, averaging 51.631 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 52.128 % in 1983 and a record low of 50.657 % in 2017. Ivory Coast CI: Population: as % of Total: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank: Population and Urbanization Statistics. Male population is the percentage of the population that is male. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average;

Ivory Coast CI: Population: Female: Ages 0-4: % of Female Population data was reported at 16.339 % in 2017. This records a decrease from the previous number of 16.413 % for 2016. Ivory Coast CI: Population: Female: Ages 0-4: % of Female Population data is updated yearly, averaging 18.768 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 20.485 % in 1978 and a record low of 16.339 % in 2017. Ivory Coast CI: Population: Female: Ages 0-4: % of Female Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank: Population and Urbanization Statistics. Female population between the ages 0 to 4 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

Ivory Coast CI: Age Dependency Ratio: % of Working-Age Population: Young data was reported at 77.667 % in 2017. This records a decrease from the previous number of 78.103 % for 2016. Ivory Coast CI: Age Dependency Ratio: % of Working-Age Population: Young data is updated yearly, averaging 83.224 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 88.527 % in 1982 and a record low of 77.667 % in 2017. Ivory Coast CI: Age Dependency Ratio: % of Working-Age Population: Young data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank.WDI: Population and Urbanization Statistics. Age dependency ratio, young, is the ratio of younger dependents--people younger than 15--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.; ; World Bank staff estimates based on age distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average;

Ivory Coast CI: Urban Land Area Where Elevation is Below 5 Meters: % of Total Land Area data was reported at 0.041 % in 2010. This stayed constant from the previous number of 0.041 % for 2000. Ivory Coast CI: Urban Land Area Where Elevation is Below 5 Meters: % of Total Land Area data is updated yearly, averaging 0.041 % from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 0.041 % in 2010 and a record low of 0.041 % in 2010. Ivory Coast CI: Urban Land Area Where Elevation is Below 5 Meters: % of Total Land Area data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank: Land Use, Protected Areas and National Wealth. Urban land area below 5m is the percentage of total land where the urban land elevation is 5 meters or less.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Weighted Average;

Ivory Coast Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 31.900 % in 2021. This records a decrease from the previous number of 34.300 % for 2018. Ivory Coast Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 37.500 % from Dec 1985 (Median) to 2021, with 12 observations. The data reached an all-time high of 44.900 % in 2008 and a record low of 28.600 % in 1986. Ivory Coast Poverty Headcount Ratio at Societal Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank.WDI: Social: Poverty and Inequality. The poverty headcount ratio at societal poverty line is the percentage of a population living in poverty according to the World Bank's Societal Poverty Line. The Societal Poverty Line is expressed in purchasing power adjusted 2017 U.S. dollars and defined as max($2.15, $1.15 + 0.5*Median). This means that when the national median is sufficiently low, the Societal Poverty line is equivalent to the extreme poverty line, $2.15. For countries with a sufficiently high national median, the Societal Poverty Line grows as countries’ median income grows.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Ivory Coast CI: Population: Male: Ages 30-34: % of Male Population data was reported at 6.243 % in 2017. This records an increase from the previous number of 6.216 % for 2016. Ivory Coast CI: Population: Male: Ages 30-34: % of Male Population data is updated yearly, averaging 6.565 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 7.236 % in 1965 and a record low of 6.136 % in 2005. Ivory Coast CI: Population: Male: Ages 30-34: % of Male Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank: Population and Urbanization Statistics. Male population between the ages 30 to 34 as a percentage of the total male population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;