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"provider": "WorldPop, University of Southampton",
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"tags": "Population mapping, Demographics, Settlement patterns, Dasymetric mapping, Random Forest, Gridded population, Census data, Population projections, Human geography, Spatial analysis",
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This dataset provides the first global analysis of surface water transition timing at annual resolution, tracking when and where water bodies have advanced or receded from 1984 to 2022. Using Landsat satellite imagery and novel algorithms developed for Google Earth Engine, this dataset identifies persistent changes in surface water features by filtering out seasonal or shorter-term fluctuations. The dataset captures transitions across diverse water environments including rivers, lakes, reservoirs, flooded agriculture, and coastal regions.
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Each 30m×30m pixel records whether water advance or recession occurred and specifies the year of transition. Unlike previous global surface water datasets that focus on net changes over multi-decade periods, this dataset emphasizes the timing of transitions, enabling clearer assessment of causation by linking surface water changes to their driving factors. The dataset reveals both natural processes (river meandering, delta dynamics, floodplain evolution) and anthropogenic interventions (dam construction, land reclamation, agricultural expansion), with human interventions typically driving rapid transitions while natural processes show more gradual patterns.
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The dataset demonstrates high accuracy with a Mean Absolute Percentage Error (MAPE) of 14.9%, coefficient of determination (R²) of 0.80, and Critical Success Index (CSI) of 96.7%. Coastal regions and lakes show the highest accuracy (MAPE: 12.7-15.9%, CSI: 96-98.9%), while rivers also demonstrate strong performance (MAPE: 15.5%, CSI: 95.5%). Water advance events are detected with higher precision than recession events, with exact year matches in 26.5% of advance cases and 19.2% of recession cases, improving to 64.5% and 46.3% respectively within ±1 year tolerance.
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You can read the [open access paper here](https://www.nature.com/articles/s41597-025-06013-5) and download the data and supplementary materials from [Figshare](https://springernature.figshare.com/articles/dataset/Surface_Water_Transitions_1984-2022_A_Global_Dataset_at_Annual_Resolution/28138643/1).
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#### Dataset Structure
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**Raster Bands:**
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-**Band 1 (b1):** Year of water advance (1984-2022) - pixels that transitioned from dry to persistently wet
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-**Band 2 (b2):** Year of water recession (1984-2022) - pixels that transitioned from wet to persistently dry
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). You are free to copy and redistribute the material in any medium or format, and to transform and build upon the material for any purpose, even commercially. You must give appropriate credit, provide a link to the license, and indicate if changes were made.
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Curated by: Gustavo Willy Nagel, Stephen E. Darby, Julian Leyland (University of Southampton)
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Curated in GEE by: Gustavo Willy Nagel and Samapriya Roy
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Keywords: Surface water, Water dynamics, Rivers, Lakes, Reservoirs, Wetlands, Erosion, Sedimentation, Dams, Water resources, Hydrology, Coastal change, Climate change, Land use change, Remote sensing, Landsat, Time series analysis, Floodplains, Deltas, River meandering
Copy file name to clipboardExpand all lines: docs/projects/worldpop.md
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The **WorldPop** collection provides population estimates at 100m resolution with the following characteristics:
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**Total Population Dataset**
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| Asset Name | Description | Band | Units |
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|------------|-------------|------|--------|
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|`pop`| Annual population estimates (2015-2030) |`population`| Number of people per grid cell |
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The dataset includes:
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-**Total Population**: Overall population counts per grid cell
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**Age-Sex Disaggregated Dataset**
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??? example "Expand to show the age-sex dataset provides population estimates broken down by gender and age groupings at 100m resolution"
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| Band Name | Description |
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|-----------|-------------|
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| `f_00`/`m_00` | Female/male population under 1 year old |
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| `f_01`/`m_01` | Female/male population aged 1-4 years |
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| `f_05`/`m_05` | Female/male population aged 5-9 years |
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| `f_10`/`m_10` | Female/male population aged 10-14 years |
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| `f_15`/`m_15` | Female/male population aged 15-19 years |
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| `f_20`/`m_20` | Female/male population aged 20-24 years |
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| `f_25`/`m_25` | Female/male population aged 25-29 years |
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| `f_30`/`m_30` | Female/male population aged 30-34 years |
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| `f_35`/`m_35` | Female/male population aged 35-39 years |
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| `f_40`/`m_40` | Female/male population aged 40-44 years |
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| `f_45`/`m_45` | Female/male population aged 45-49 years |
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| `f_50`/`m_50` | Female/male population aged 50-54 years |
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| `f_55`/`m_55` | Female/male population aged 55-59 years |
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| `f_60`/`m_60` | Female/male population aged 60-64 years |
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| `f_65`/`m_65` | Female/male population aged 65-69 years |
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| `f_70`/`m_70` | Female/male population aged 70-74 years |
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| `f_75`/`m_75` | Female/male population aged 75-79 years |
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| `f_80`/`m_80` | Female/male population aged 80-84 years |
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| `f_85`/`m_85` | Female/male population aged 85-89 years |
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| `f_90`/`m_90` | Female/male population aged 90 years and over |
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#### Citation
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```
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WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie,
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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
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Melinda Gates Foundation (OPP1134076).
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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).
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```
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#### Dataset Citation
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#### Dataset Citations
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**Total Population Dataset:**
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```
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Bondarenko M., Priyatikanto R., Tejedor-Garavito N., Zhang W., McKeen T., Cunningham A., Woods T., Hilton J., Cihan D., Nosatiuk B., Brinkhoff T., Tatem A., Sorichetta A.. 2025 Constrained estimates of 2015-
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2030 total number of people per grid square at a resolution of 3 arc (approximately 100m at the equator) R2024B version v1. Global Demographic Data Project - Funded by The Bill and Melinda Gates Foundation
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(INV-045237). WorldPop - School of Geography and Environmental Science, University of Southampton. DOI:10.5258/SOTON/WP00803
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Bondarenko M., Priyatikanto R., Tejedor-Garavito N., Zhang W., McKeen T., Cunningham A., Woods T., Hilton J., Cihan D., Nosatiuk B., Brinkhoff T., Tatem A., Sorichetta A.. 2025 Constrained estimates of 2015- 2030 total number of people per grid square at a resolution of 3 arc (approximately 100m at the equator) R2024B version v1. Global Demographic Data Project - Funded by The Bill and Melinda Gates Foundation (INV-045237). WorldPop - School of Geography and Environmental Science, University of Southampton. DOI:10.5258/SOTON/WP00803
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```
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**Age-Sex Dataset:**
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```
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Bondarenko M., Priyatikanto R., Tejedor-Garavito N., Zhang W., McKeen T., Cunningham A., Woods T., Hilton J., Cihan D., Nosatiuk B., Brinkhoff T., Tatem A., Sorichetta A.. 2025. The spatial distribution of population broken down by gender and age groupings in 2015-2030 at a resolution of 3 arc (approximately 100m at the equator) R2025A version v1. Global Demographic Data Project - Funded by The Bill and Melinda Gates Foundation (INV-045237). WorldPop - School of Geography and Environmental Science, University of Southampton.
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```
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#### Earth Engine Snippet
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**Total Population:**
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```javascript
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var worldpop =ee.ImageCollection("projects/sat-io/open-datasets/WORLDPOP/pop");
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
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#### Changelog
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**2026-02-03** Added Age-Sex 100m dataset to the WorldPop collections
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Provided by: WorldPop, University of Southampton
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Keywords: Population mapping, Demographics, Settlement patterns, Dasymetric mapping, Random Forest, Gridded population, Census data, Population projections, Human geography, Spatial analysis
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Curated in GEE by: Samapriya Roy
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Curated in GEE by: Samapriya Roy and Rhorom Priyatikanto
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