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.

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.

Bangladesh data available from WorldPop here.

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.

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Bangladesh: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tentative IAPP Locations: Source: Project Appraisal Document (PAD). Population: (Total population) (2011): Total 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. Source: Government of the People’s Republic of Bangladesh -Ministry of Planning - Bangladesh Bureau of Statistics. “Population and Housing Census 2011.Preliminary Results.” Population Density (Persons per 1 square kilometer) (2011): Population divided by land area in square kilometers. Source: Government of the People’s Republic of Bangladesh -Ministry of Planning - Bangladesh Bureau of Statistics. “Population and Housing Census 2011.Preliminary Results.” Poverty (Proportion of population below the poverty line) (2010): Proportion of the population living on less than US$1.25 a day, measured at 2005 international prices, adjusted forpurchasing power parity (PPP). Source: Government of the People’s Republic of Bangladesh -Ministry of Planning - Bangladesh Bureau of Statistics. “HIES Survey 2010, Chapter 6.” Malnutrition (Proportion of underweight children under 5 years) (2011): Prevalence of severely underweight children is the percentage of children aged 0-59 months whose weight for age is less than minus 3 standard deviations below the median weight for age of the international reference population. Source: “Bangladesh Demographic and Health Survey 2011. Preliminary Report.”Measure DHS. MEASURE DHS (Demographic and Health Surveys) Project is responsible for collecting and disseminating accurate, nationally representative data on health and population in developing countries. The project is implemented by Macro International, Inc. and is funded by the United States Agency for International Development (USAID) with contributions from other donors such as UNICEF, UNFPA, WHO, UNAIDS. Irrigation (2009/10): Total Irrigated Area in Acres (Thousands). Source: Government of the People’s Republic of Bangladesh -Ministry of Planning - Bangladesh Bureau of Statistics.2010 Yearbook of Agricultural Statistics of Bangladesh.

Digital polygon dataset of Population Distribution per District of Chittagong Hill Tracts of Bangladesh. This dataset is basic vector layer based on LGED Administrative Base Map and Bangladesh Bureau of Statistics (BBS) 2001.

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).

In this analysis we have combined several data sources around the floods in Bangladesh in August 2017.

Visualization

• See attached map for a map visualization of this analysis.
• See http://bit.ly/2uFezkY for a more interactive visualization in Carto.

Situation

Currently, in Bangladesh many water level measuring stations measure water levels that are above danger levels. This sets in triggers in motion for the partnership of the 510 Data Intitiative and the Red Cross Climate Centre to get into action.

Indicators and sources

In the attached map, we combined several sources:

• Locations of waterlevel stations and their respective excess water levels (cms above danger level) at 14/08/2017 (Source: http://www.ffwc.gov.bd/index.php/googlemap?id=20)
• Population density in Bangladesh to quickly see where many people live in comaprison to these higher water-level stations. (Source: http://www.worldpop.org.uk/data/summary/?doi=10.5258/SOTON/WP00018 >> the People per hectare 2015 UN-adjusted totals file is used.)
• Vulnerability Index: we constructed a Vulnerability Index (0-10) based on two sources. First poverty incidence was collected from Worldpop (Source: http://www.worldpop.org.uk/data/summary/?doi=10.5258/SOTON/WP00020 >> The estimated likelihood of living below $2.50/day). Second, we used a Deprivation Index which is estimated in the report Lagging District Reports 2015 (Source: http://www.plancomm.gov.bd/wp-content/uploads/2015/02/15_Lagging-Regions-Study.pdf > Appendices > Table 20), which combines many socio-economic variables into one Deprivation Index through PCA analysis.

Detailed methodology Vulnerability

• The above-mentioned poverty source file is on a raster level. This raster level poverty was transformed to admin-4 level geographic areas (source: https://data.humdata.org/dataset/bangladesh-admin-level-4-boundaries), by taking a population-weighted average. (Source population also Worldpop).
• The district-level PCA components from abovementioned reports were matched to the geodata based on district names, and thus joined to the admin-4 level areas, which now contain a poverty value as well as Deprivation Index value. Note that all admin-4 areas within one district (admin-2) obviously all have the same value. The poverty rates do differ between all admin-4 areas.
• Lastly, both variables were transformed to a 0-10 score (linearly), and a geomean was taken to calculate the final index of the two. A geomean (as opposed to an arithmetic mean) is often used in calculating composite risk indices, for example in the widely used INFORM-framework (www.inform-index.org).

Following an outbreak of violence on 25 August 2017 in Rakhine State, Myanmar, a new massive influx of Rohingya refugees to Cox’s Bazar, Bangladesh started in late August 2017. Most of the Rohingya refugees settled in Ukhia and Teknaf Upazilas of Cox’s Bazar, a district bordering Myanmar identified as the main entry area for border crossings.

This dataset presents the result of the NPM Round 11 exercise, which collected information related to the Rohingya refugee population distribution and needs during the months of June and July 2018.

• The data collection for NPM baseline survey was conducted between 2 and 14 June 2018: it provides an update about the population distribution and movements.
• The data collection for NPM Site Assessment survey was conducted between 1 and 22 July 2018: in addition to an update about the population figures, this includeds a multi-sectoral needs assessment.

The full maps and GIS packages by camp produced based on NPM Baseline and Site Assessment 11 are available at the links below:

• Please click here to access the data by camp as of May 2018.
• Please click here to access the data by camp as of July 2018.

Rohingya refugee population distribution by para in Teknaf upazila. - Please click here.

Following an outbreak of violence on 25 August 2017 in Rakhine State, Myanmar, a new massive influx of Rohingya refugees to Cox’s Bazar, Bangladesh started in late August 2017. Most of the Rohingya refugees settled in Ukhia and Teknaf Upazilas of Cox’s Bazar, a district bordering Myanmar identified as the main entry area for border crossings.

This dataset presents the result of the NPM Round 12 Site Assessment exercise, which collected information related to the Rohingya refugee population distribution and needs during the months of August, September and October 2018.

• The data collection for NPM baseline survey was conducted between 9 August and 4 September 2018: it provides an update about the population distribution and movements.
• The data collection for NPM Site Assessment survey was conducted between 23 September and 10 October 2018: in addition to an update about the population figures, this includes a multi-sectoral needs assessment.

The full maps and GIS packages by camp produced based on NPM Baseline and Site Assessment 12 are available at the links below:

• Please click here to access the data by camp as of September/October 2018.
• Please click here to access the data by camp as of August 2018.

Rohingya refugee population distribution by para in Teknaf upazila. - Please click here.

The raster dataset consists of a 500m score grid for vegetables storage location, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The location score is achieved by processing sub-model outputs that characterize logistical factors for selected crop warehouse locations: • Supply: Crop. • Demand: Human population density, Major cities population (national and bordering countries). • Infrastructure/accessibility: main transportation infrastructure. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + (“Major Cities Accessibility” * 0.1) + (”Regional Cities Accessibility” *0.1 ) + (”Port Accessibility” *0. 2)

Abstract

Following an outbreak of violence on 25 August 2017 in Rakhine State, Myanmar, a new massive influx of Rohingya refugees to Cox’s Bazar, Bangladesh started in late August 2017. Most of the Rohingya refugees settled in Ukhia and Teknaf Upazilas of Cox’s Bazar, a district bordering Myanmar identified as the main entry area for border crossings.

This dataset presents the result of the NPM Round 11 exercise, which collected information related to the Rohingya refugee population distribution and needs during the months of June and July 2018.

• The data collection for NPM baseline survey was conducted between 2 and 14 June 2018: it provides an update about the population distribution and movements.
• The data collection for NPM Site Assessment survey was conducted between 1 and 22 July 2018: in addition to an update about the population figures, this includeds a multi-sectoral needs assessment.

The full maps and GIS packages by camp produced based on NPM Baseline and Site Assessment 11 are available at the links below:

• Please click here to access the data by camp as of May 2018.
• Please click here to access the data by camp as of July 2018.

Rohingya refugee population distribution by para in Teknaf upazila. - Please click here.

Geographic coverage

Bangladesh

Kind of data

Observation data/ratings [obs]

The raster dataset consists of a 500 m score grid for dairy processing industry facilities siting, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The analysis is based on sheep dairy production intensification potential, defined using crop production, livestock production systems, and goat distribution. The score is achieved by processing sub-model outputs that characterize logistical factors: 1. Supply - Feed, livestock production systems, dairy distribution. 2. Demand - Human population density, large cities, urban areas. 3. Infrastructure - Transportation network (accessibility) It consists of an arithmetic weighted sum of normalized grids (0 to 100): (”Dairy Intensification” * 0.4) + ("Crop Production" * 0.3) + (“Major Cities Accessibility” * 0.2) + (“Population Density” * 0.1)

The raster dataset consists of a 500m score grid for rice storage location, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The location score is achieved by processing sub-model outputs that characterize logistical factors for selected crop warehouse locations: • Supply: Crop. • Demand: Human population density, Major cities population (national and bordering countries). • Infrastructure/accessibility: main transportation infrastructure. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + (“Major Cities Accessibility” * 0.1) + (”Regional Cities Accessibility” *0.1 ) + (”Port Accessibility” *0. 2)

This interactive map of Bangladesh highlights the project locations of the Integrated Agricultural Productivity Project (IAPP) and PRAN. Bangladesh is divided into seven administrative divisions, which are broken down into 64 districts, and further divided into 485 upazilas. This map overlays sub-national poverty data, demographic indicators, and other information relevant to the program. IAPP will target the districts of Rangpur, Kurigram, Lalmonirhat, and Nilfamari in the north and the districts of Barisal, Patuakhali, Barguna and Jhalokathi in the south. The project is expected to increase the productivity of major crops like cereals and pulses, increase the productivity of fish and livestock, increase the availability of certified seed, increase the irrigated area, and the income of farmers in all 54 upazilas in these eight districts. The project areas were selected for their high rates of poverty, food insecurity, and their vulnerability to natural shocks such as tidal surge in the south, and flash flood and drought in the north. GAFSP is financing the expansion of food processing and manufacturing capacity of Natore Agro Limited from PRAN group. PRAN group is the largest food and nutrition company in Bangladesh, with more than 40,000 employees and over 200 different products. The enhancement of operations is creating new jobs (over 1,200 expected), in a region severely affected by unemployment and is increasing the opportunities for local producers as raw material suppliers for the company. Data Sources: PRAN Project LocationSource: GAFSP Documents. IAPP Project Areas

Source: Project Appraisal Document (PAD). Poverty Incidence (Proportion of population below the poverty line) (2010): Proportion of the population living on less than US$1.25 a day, measured at 2005 international prices, adjusted for purchasing power parity (PPP).Source: Bangladesh Bureau of Statistics. “HIES Survey 2010 Chapter 6.” Malnutrition (Proportion of underweight children under 5 years) (2011): Prevalence of severely underweight children is the percentage of children under age 5 whose weight-for-age is more than 3 standard deviations below the median for the international reference population ages 0-59 months.Source: Measure DHS. “Bangladesh Demographic and Health Survey 2011. Preliminary Report.” Total Population (2011): Total 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.Source: Bangladesh Bureau of Statistics. “Population and Housing Census 2011. Preliminary Results.” Population Density (2011): Population divided by land area in square kilometers.Source: Bangladesh Bureau of Statistics. “Population and Housing Census 2011. Preliminary Results.” Irrigated Area (2009/10): Total irrigated area in hectares.Source: Bangladesh Bureau of Statistics. 2010 Yearbook of Agricultural Statistics of Bangladesh. Potato Production (2009-10 and 2010-11): Total production in tons by variety and total production in tons per hectare by variety.Source: Bangladesh Bureau of Statistics. “2012 Yearbook of Agricultural Statistics of Bangladesh.” Boro Rice (2009-10 and 2010-11): Total production in tons by variety and total production in tons per hectare by variety.Source: Bangladesh Bureau of Statistics. “2012 Yearbook of Agricultural Statistics of Bangladesh.” Bangladesh Soil Salinity (2009): Saline soils, salinity boundary, and coastlines.

Source: Soil Resource Development Institute SRMAF Project – Bangladesh Ministry of Agriculture. “Saline Soils in Bangladesh 2010.”The maps displayed on this website are for reference only. The boundaries, colors, denominations and any other information shown on these maps do not imply, on the part of GAFSP (and the World Bank Group), any judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.

The raster dataset consists of a 500 m score grid for dairy processing industry facilities siting, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The analysis is based on sheep dairy production intensification potential, defined using crop production, livestock production systems, and cattle distribution. The score is achieved by processing sub-model outputs that characterize logistical factors: 1. Supply - Feed, livestock production systems, dairy distribution. 2. Demand - Human population density, large cities, urban areas. 3. Infrastructure - Transportation network (accessibility) It consists of an arithmetic weighted sum of normalized grids (0 to 100): (”Dairy Intensification” * 0.4) + ("Crop Production" * 0.3) + (“Major Cities Accessibility” * 0.2) + (“Population Density” * 0.1)

Bangladesh is a South Asian country located at the crossroads of the Indochina and Indo-Himalayan subregions, making it a country of rich faunal diversity. Bangladesh's high population density paired with rapid habitat alteration leaving only 6% of its natural habitats threatens its faunal diversity. Over 1,455 bat species live on earth, providing immense ecological services to maintain biodiversity. The paucity of bat research in Bangladesh and the lack of comprehensive work has led us to set the goal of checking how many species are present in Bangladesh, and the possibility of bat species yet to have occurred. Here we compiled species occurrence data on the bats of Bangladesh and states in neighboring countries (India – states are West Bengal, Sikkim, Meghalaya, Assam, Tripura, Mizoram; Myanmar – states are Chin, Rakhine) from the museums (American Museum of Natural History, Smithsonian National Museum of Natural History, Natural History Museum at United Kingdom, Field Museum of Natural History, Hungarian Natural History Museum, and Royal Ontario Museum), Global Biodiversity Information Facility, and literature, and constructed distribution maps for each species. The maps depicted both the fine-scale and coarse-scale distribution of the species. We confirmed 31 species are occurring in Bangladesh – among them, 22 species are confirmed with the voucher specimen, 15 species are associated with the preserved tissues, and one is confirmed with the morphometric data and key characteristics. Based on the species occurrence in the states of India and Myanmar, along with the habitat preference, an additional 83 species are yet to have occurred in Bangladesh. Among them, 38 species are categorized as Highly Probable, 33 species are Probable, and 10 species are Possible. We recommend bat surveys are urgent in Bangladesh using all complementary capture techniques that will contribute to voucher specimen collections and confirm the presence of bats. In addition, echolocation calls of bats can help establish call libraries.

Following an outbreak of violence on 25 August 2017 in Rakhine State, Myanmar, a new massive influx of Rohingya refugees to Cox’s Bazar, Bangladesh started in late August 2017. Most of the Rohingya refugees settled in Ukhia and Teknaf Upazilas of Cox’s Bazar, a district bordering Myanmar identified as the main entry area for border crossings.

These datasets present the result of the NPM Round 10 Baseline and Site Assessment exercises, which collected information related to the Rohingya population distribution and needs during the months of April and May 2018.

The data collection for NPM baseline survey was conducted between 1 and 17 April 2018: this provides an update about the population distribution and movements; The data collection for NPM Site Assessment survey was conducted between 1 and 20 May 2018: in addition to an update about the population figures, this includeds a multi-sectoral needs assessment.

The full maps and GIS packages by camp produced based on NPM Baseline and Site Assessment 10 are available at the links below:

• Please click here to access the data by camp as of May 2018.
• Please click here to access the data by camp as of April 2018.

Rohingya refugee population distribution by para in Teknaf upazila. Data collected during NPM Site Assessment 10 between 1 and 20 May 2018.

• Please click here.

this project graph is : ourworldindata

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For the vast majority of human existence, our global population remained a mere fraction of what it is today. However, the last few centuries have borne witness to an extraordinary transformation in human demography. In the year 1800, the global population stood at a modest one billion individuals. Fast forward to the present day, and we find ourselves amidst a staggering figure of over 8 billion people inhabiting our planet.

Yet, despite this exponential growth trajectory, demographers now project a fascinating shift on the horizon: the expectation that global population growth will plateau by the close of this century.

Within the vast repository of Our World in Data, we delve deeply into the intricacies of population dynamics, offering a comprehensive array of data, charts, and analyses elucidating the nuanced changes in population growth. From the geographical distribution of populations to temporal shifts and future projections, our platform serves as a rich tapestry of insights into this paramount aspect of human civilization.

One of the most illuminating tools at our disposal is the population cartogram—a unique visualization method that transcends traditional geographical maps to provide a more accurate depiction of global population distribution. Unlike conventional maps, which delineate territories based solely on landmass, population cartograms offer a perspective where countries are resized according to their respective populations.

In our exploration of the population cartogram for the year 2018, we uncover a myriad of revelations. Small nations characterized by high population densities manifest as enlarged entities, accentuating their significance on the global stage. Bangladesh, Taiwan, and the Netherlands emerge prominently, their amplified proportions underscoring their demographic density. Conversely, vast territories with comparatively sparse populations undergo a visual reduction in size. Countries like Canada, Mongolia, Australia, and Russia, despite their expansive landmasses, shrink in relative stature, highlighting the intriguing interplay between territory and population.

This innovative approach to mapping not only challenges conventional perceptions but also provides invaluable insights into the complex mosaic of human settlement patterns and demographic trends. By transcending the limitations of traditional cartography, population cartograms offer a nuanced lens through which to perceive the evolving dynamics of our global community.

To delve deeper into the nuances of this population cartogram and its implications, we invite you to explore our comprehensive article dedicated to this fascinating subject. Within its pages, you will find a detailed analysis, accompanied by captivating visuals and insightful commentary, elucidating the significance of population cartograms in understanding our world.

At Our World in Data, we remain committed to unraveling the complexities of global population dynamics, offering a platform that fosters informed discourse and deepens our understanding of the forces shaping our collective future. Join us on this illuminating journey as we navigate the ever-changing landscape of human demography, charting a course towards a more enlightened tomorrow.