The population density in Sri Lanka saw no significant changes in 2022 in comparison to the previous year 2021 and remained at around 358.57 inhabitants per square kilometer. Still, the population density reached its highest value in the observed period in 2022. Population density refers to the number of people living in a certain country or area, given as an average per square kilometer. It is calculated by dividing the total midyear population by the total land area.Find more key insights for the population density in countries like India and Bhutan.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available. Sri Lanka data available from WorldPop here.

Sri Lanka LK: Population Density: People per Square Km data was reported at 341.955 Person/sq km in 2017. This records an increase from the previous number of 338.112 Person/sq km for 2016. Sri Lanka LK: Population Density: People per Square Km data is updated yearly, averaging 272.855 Person/sq km from Dec 1961 (Median) to 2017, with 57 observations. The data reached an all-time high of 341.955 Person/sq km in 2017 and a record low of 161.245 Person/sq km in 1961. Sri Lanka LK: Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sri Lanka – Table LK.World Bank: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.; ; Food and Agriculture Organization and World Bank population estimates.; Weighted Average;

Population density (people per sq. km of land area) in Sri Lanka was reported at 359 sq. Km in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Sri Lanka - Population density (people per sq. km) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Sri Lanka: Population density, people per square km: The latest value from 2021 is 358 people per square km, an increase from 354 people per square km in 2020. In comparison, the world average is 456 people per square km, based on data from 196 countries. Historically, the average for Sri Lanka from 1961 to 2021 is 269 people per square km. The minimum value, 160 people per square km, was reached in 1961 while the maximum of 358 people per square km was recorded in 2021.

The population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery.

A database (NDP-068) was generated from estimates of geographically referenced carbon densities of forest vegetation in tropical Southeast Asia for 1980. A geographic information system (GIS) was used to incorporate spatial databases of climatic, edaphic, and geomorphological indices and vegetation to estimate potential (i.e., in the absence of human intervention and natural disturbance) carbon densities of forests. The resulting map was then modified to estimate actual 1980 carbon density as a function of population density and climatic zone. The database covers the following 13 countries: Bangladesh, Brunei, Cambodia (Campuchea), India, Indonesia, Laos, Malaysia, Myanmar (Burma), Nepal, the Philippines, Sri Lanka, Thailand, and Vietnam.

The data sets within this database are provided in three file formats: ARC/INFOTM exported integer grids; ASCII (American Standard Code for Information Interchange) files formatted for raster-based GIS software packages; and generic ASCII files with x, y coordinates for use with non-GIS software packages.

The database includes ten ARC/INFO exported integer grid files (five with the pixel size 3.75 km x 3.75 km and five with the pixel size 0.25 degree longitude x 0.25 degree latitude) and 27 ASCII files. The first ASCII file contains the documentation associated with this database. Twenty-four of the ASCII files were generated by means of the ARC/INFO GRIDASCII command and can be used by most raster-based GIS software packages. The 24 files can be subdivided into two groups of 12 files each.

The files contain real data values representing actual carbon and potential carbon density in Mg C/ha (1 megagram = 10^6 grams) and integer-coded values for country name, Weck's Climatic Index, ecofloristic zone, elevation, forest or non- forest designation, population density, mean annual precipitation, slope, soil texture, and vegetation classification. One set of 12 files contains these data at a spatial resolution of 3.75 km, whereas the other set of 12 files has a spatial resolution of 0.25 degree. The remaining two ASCII data files combine all of the data from the 24 ASCII data files into 2 single generic data files. The first file has a spatial resolution of 3.75 km, and the second has a resolution of 0.25 degree. Both files also provide a grid-cell identification number and the longitude and latitude of the centerpoint of each grid cell.

The 3.75-km data in this numeric data package yield an actual total carbon estimate of 42.1 Pg (1 petagram = 10^15 grams) and a potential carbon estimate of 73.6 Pg; whereas the 0.25-degree data produced an actual total carbon estimate of 41.8 Pg and a total potential carbon estimate of 73.9 Pg.

Fortran and SASTM access codes are provided to read the ASCII data files, and ARC/INFO and ARCVIEW command syntax are provided to import the ARC/INFO exported integer grid files. The data files and this documentation are available without charge on a variety of media and via the Internet from the Carbon Dioxide Information Analysis Center (CDIAC).

Comprehensive socio-economic dataset for Sri Lanka including population demographics, economic indicators, geographic data, and social statistics. This dataset covers key metrics such as GDP, population density, area, capital city, and regional classifications.

In 2022, the population density in Bhutan remained nearly unchanged at around 20.47 inhabitants per square kilometer. Nevertheless, 2022 still represents a peak in the population density in Bhutan with 20.47 inhabitants per square kilometer. Population density is calculated by dividing the total population by the total land area, to show the average number of people living there per square kilometer of land.Find more key insights for the population density in countries like Sri Lanka and Nepal.

The population density in Nepal saw no significant changes in 2022 in comparison to the previous year 2021 and remained at around 207.29 inhabitants per square kilometer. Still, the population density reached its highest value in the observed period in 2022. Population density refers to the average number of residents per square kilometer of land across a given country or region. It is calculated by dividing the total midyear population by the total land area.Find more key insights for the population density in countries like Sri Lanka and Pakistan.

Accuracy of population density estimates.

The population density in Pakistan increased by *** inhabitants per square kilometer (+**** percent) in 2022. Therefore, the population density in Pakistan reached a peak in 2022 with ****** inhabitants per square kilometer. Notably, the population density continuously increased over the last years.Population density refers to the number of people living in a certain country or area, given as an average per square kilometer. It is calculated by dividing the total midyear population by the total land area.Find more key insights for the population density in countries like India and Sri Lanka.

The refined population spatial distribution data set of Hambantota port area is generated by reanalysis based on hrsl data of Sri Lanka. Hrsl data provides an estimate of the population distribution in 2015 at a resolution of 1 arcsec (about 30 meters). The latest census information and built-up area information based on satellite images are used in hrsl data. This data set is based on hrsl data. Firstly, the boundary of buildings is extracted from the 0.5m resolution remote sensing image by computer vision technology, and the building types (high-rise buildings, medium and low rise buildings, bungalows, etc.) are determined by combining with manual visual interpretation and field sampling. The population distribution area mask is constructed in the building area, and the 10 meter grid is used as the analysis unit to calculate the population distribution in the unit According to the proportion of different building types, the proportion of main land use types, building density, distance from road and other related indicators, the average density of building type consistent area is calculated from hrsl data, and the corresponding population density of each building is obtained by machine learning method. Then, the population data in the area is allocated to the corresponding unit by proportional allocation method, and the 10 meter resolution is obtained Population distribution products. The data is distributed in the form of GeoTIFF files. Population GeoTIFF represents population estimates (in person) and provides detailed estimates for population, infrastructure and Sustainability Studies in the humanitarian field.

Out-of-sample accuracy of HIES-based village population density estimates using open-source and commercially-procured satellite data, 55 sub-districts.

In 2022, the population density in India remained nearly unchanged at around 479.43 inhabitants per square kilometer. Still, the population density reached its highest value in the observed period in 2022. Population density refers to the number of people living in a certain country or area, given as an average per square kilometer. It is calculated by dividing the total midyear population by the total land area.Find more key insights for the population density in countries like Sri Lanka and Pakistan.

Satellite indicators by resolution and availability.

We estimated the population density and investigated the social organization of sambar (Rusa unicolor unicolor) in Horton Plains National Park (HPNP), Sri Lanka. Distance sampling was conducted along six strip transects every month for a period over three years (2018–2020) to estimate the density of the sambar population in grasslands of HPNP (9.4 km2), while the antler stage of males and the behaviour of individuals were recorded to describe the population’s reproductive stage and hence the social organization. Population density estimates showed relative stability over the three years and varied over the seasons but with consistent peaks from year to year with the highest population densities recorded in November-December (212.93 ± 25.38 animals/km2 in 2018, 187.91 ± 28.51 in 2019, and 179.76 ± 31.85 in 2020). The highest percentage of males in hard antlers was observed from November through January, while the percentage of antlers cast sambar peaked from March to April each year. Hinds were observed with newborn calves throughout the year, but the highest number of newborn calves were recorded from July to August each year, while the number of calves counted each year varied from 210–267 individuals. The mean group size was variable throughout each year with the largest groups recorded from September to December (up to 52), the period accompanied by the most observations of mating and sparring behaviour. Although on a tropical island, HPNP is situated on a rolling plateau landscape in the highlands, where sambar showed a degree of reproductive seasonality somewhat similar to temperate cervid species. Methods The study was conducted within the grasslands of HPNP (Figure 1) using transects to count sambar deer and to estimate their density using a distance sampling technique (Buckland et al., 2013). However, our methodology was biased on the grassland habitat that provides high-quality feeding grounds for sambar, with no distance transect counts taken in patches of cloud forests within HPNP, and the counts were conducted in peak grazing hours of sambar during the dusk, with the assumption that the entire population is in the grasslands during that time. Hence, the resulting density estimation is only valid for the grassland habitat and presented here as the ecological density of sambar in grasslands of HPNP.

Dengue is one of the major hurdles to the public health in Sri Lanka, causing high morbidity and mortality. The present study focuses on the use of geographical information systems (GIS) to map and evaluate the spatial and temporal distribution of dengue in Sri Lanka from 2009 to 2014 and to elucidate the association of climatic factors with dengue incidence. Epidemiological, population and meteorological data were collected from the Epidemiology Unit, Department of Census and Statistics and the Department of Meteorology of Sri Lanka. Data were analyzed using SPSS (Version 20, 2011) and R studio (2012) and the maps were generated using Arc GIS 10.2. The dengue incidence showed a significant positive correlation with rainfall (p

LK：人口密度：每平方公里人口在12-01-2017达341.955Person/sq km，相较于12-01-2016的338.112Person/sq km有所增长。LK：人口密度：每平方公里人口数据按年更新，12-01-1961至12-01-2017期间平均值为272.855Person/sq km，共57份观测结果。该数据的历史最高值出现于12-01-2017，达341.955Person/sq km，而历史最低值则出现于12-01-1961，为161.245Person/sq km。CEIC提供的LK：人口密度：每平方公里人口数据处于定期更新的状态，数据来源于World Bank，数据归类于Global Database的斯里兰卡 – 表 LK.世界银行：人口和城市化进程统计。

Summary statistics for villages in the national sample.