Review article
11 Sep 2019
Review article
| 11 Sep 2019
The spatial allocation of population: a review of large-scale gridded population data products and their fitness for use
Stefan Leyk et al.
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Total article views: 10,801 (including HTML, PDF, and XML)
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Cited
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87 citations as recorded by crossref.
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- Asset exposure data for global physical risk assessment S. Eberenz et al. 10.5194/essd-12-817-2020
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- Assessing OSM building completeness using population data Y. Zhang et al. 10.1080/13658816.2021.2023158
- Incorporating Geographic Information Science and Technology in Response to the COVID-19 Pandemic C. Smith & J. Mennis 10.5888/pcd17.200246
- Accounting for internal migration in spatial population projections—a gravity-based modeling approach using the Shared Socioeconomic Pathways L. Reimann et al. 10.1088/1748-9326/ac0b66
- Estimating Chinese residential populations from analysis of impervious surfaces derived from satellite images S. Wei et al. 10.1080/01431161.2020.1841322
- Which Gridded Population Data Product Is Better? Evidences from Mainland Southeast Asia (MSEA) X. Yin et al. 10.3390/ijgi10100681
- An introduction to DUIA: The database on urban inequality and amenities F. Ramos et al. 10.1371/journal.pone.0253824
- Improving the accuracy of extant gridded population maps using multisource map fusion P. Gao et al. 10.1080/15481603.2021.2012371
- High-Resolution Gridded Population Datasets: Exploring the Capabilities of the World Settlement Footprint 2019 Imperviousness Layer for the African Continent D. Palacios-Lopez et al. 10.3390/rs13061142
- Mapping Gridded Gross Domestic Product Distribution of China Using Deep Learning With Multiple Geospatial Big Data Y. Chen et al. 10.1109/JSTARS.2022.3148448
- A review of freely accessible global datasets for the study of floods, droughts and their interactions with human societies S. Lindersson et al. 10.1002/wat2.1424
- Mapping Human Activity Volumes Through Remote Sensing Imagery X. Xing et al. 10.1109/JSTARS.2020.3023730
- Using satellite imagery to understand and promote sustainable development M. Burke et al. 10.1126/science.abe8628
- U-Net-Id, an Instance Segmentation Model for Building Extraction from Satellite Images—Case Study in the Joanópolis City, Brazil F. Wagner et al. 10.3390/rs12101544
- Spatial access inequities and childhood immunisation uptake in Kenya N. Joseph et al. 10.1186/s12889-020-09486-8
- Measuring the accuracy of gridded human population density surfaces: A case study in Bioko Island, Equatorial Guinea B. Fries et al. 10.1371/journal.pone.0248646
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- Global Harmonization of Urbanization Measures: Proceed with Care D. Balk et al. 10.3390/rs13244973
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- A 100 m population grid in the CONUS by disaggregating census data with open-source Microsoft building footprints X. Huang et al. 10.1080/20964471.2020.1776200
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- Evaluating the Accuracy of Gridded Population Estimates in Slums: A Case Study in Nigeria and Kenya D. Thomson et al. 10.3390/urbansci5020048
- Unraveling Long-Term Flood Risk Dynamics Across the Murray-Darling Basin Using a Large-Scale Hydraulic Model and Satellite Data S. Ceola et al. 10.3389/frwa.2021.797259
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- First year with COVID-19: Assessment and prospects R. Bergquist et al. 10.4081/gh.2020.953
- Evaluation of NLDAS-2 and Downscaled Air Temperature data in Florida J. Jung et al. 10.1080/02723646.2021.1928878
- Satellite imaging reveals increased proportion of population exposed to floods B. Tellman et al. 10.1038/s41586-021-03695-w
- Spatially explicit reconstruction of the population distribution in the Tuojiang River Basin during 1911–2010 using random forest regression Q. Wang et al. 10.1007/s10113-021-01872-1
- Understanding dynamics of population flood exposure in Canada with multiple high-resolution population datasets M. Mohanty & S. Simonovic 10.1016/j.scitotenv.2020.143559
- Implications for Tracking SDG Indicator Metrics with Gridded Population Data C. Tuholske et al. 10.3390/su13137329
- Towards an Improved Large-Scale Gridded Population Dataset: A Pan-European Study on the Integration of 3D Settlement Data into Population Modelling D. Palacios-Lopez et al. 10.3390/rs14020325
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- The uncertainty of flood frequency analyses in hydrodynamic model simulations X. Zhou et al. 10.5194/nhess-21-1071-2021
- Violent conflict exacerbated drought-related food insecurity between 2009 and 2019 in sub-Saharan Africa W. Anderson et al. 10.1038/s43016-021-00327-4
- Fine-grained, spatiotemporal datasets measuring 200 years of land development in the United States J. Uhl et al. 10.5194/essd-13-119-2021
- Satellite-Based Human Settlement Datasets Inadequately Detect Refugee Settlements: A Critical Assessment at Thirty Refugee Settlements in Uganda J. Van Den Hoek & H. Friedrich 10.3390/rs13183574
- Disaggregating Population Data and Evaluating the Accuracy of Modeled High-Resolution Population Distribution—The Case Study of Germany S. Eichhorn 10.3390/su12103976
- Mapping Impervious Surface Areas Using Time-Series Nighttime Light and MODIS Imagery Y. Tang et al. 10.3390/rs13101900
- Need for an Integrated Deprived Area “Slum” Mapping System (IDEAMAPS) in Low- and Middle-Income Countries (LMICs) D. Thomson et al. 10.3390/socsci9050080
- Looking Back, Looking Forward: Progress and Prospect for Spatial Demography S. Matthews et al. 10.1007/s40980-021-00084-9
- Mapping hourly population dynamics using remotely sensed and geospatial data: a case study in Beijing, China X. Zhao et al. 10.1080/15481603.2021.1935128
- Global flood exposure from different sized rivers M. Bernhofen et al. 10.5194/nhess-21-2829-2021
- Disaggregating population data for assessing progress of SDGs: methods and applications Y. Qiu et al. 10.1080/17538947.2021.2013553
- Measuring the contribution of built-settlement data to global population mapping J. Nieves et al. 10.1016/j.ssaho.2020.100102
- The Ratio of the Land Consumption Rate to the Population Growth Rate: A Framework for the Achievement of the Spatiotemporal Pattern in Poland and Lithuania B. Calka et al. 10.3390/rs14051074
- Two centuries of settlement and urban development in the United States S. Leyk et al. 10.1126/sciadv.aba2937
- GHS-POP Accuracy Assessment: Poland and Portugal Case Study B. Calka & E. Bielecka 10.3390/rs12071105
- Combining expert and crowd-sourced training data to map urban form and functions for the continental US M. Demuzere et al. 10.1038/s41597-020-00605-z
- Gridded population survey sampling: a systematic scoping review of the field and strategic research agenda D. Thomson et al. 10.1186/s12942-020-00230-4
- High-resolution population estimation using household survey data and building footprints G. Boo et al. 10.1038/s41467-022-29094-x
- Elucidating the impacts of rapid urban expansion on air quality in the Yangtze River Delta, China X. Zhang et al. 10.1016/j.scitotenv.2021.149426
- Mapping Changing Population Distribution on the Qinghai–Tibet Plateau since 2000 with Multi-Temporal Remote Sensing and Point-of-Interest Data L. Li et al. 10.3390/rs12244059
- Mapping Multi-Temporal Population Distribution in China from 1985 to 2010 Using Landsat Images via Deep Learning H. Zhuang et al. 10.3390/rs13173533
- Local Population Mapping Using a Random Forest Model Based on Remote and Social Sensing Data: A Case Study in Zhengzhou, China G. Qiu et al. 10.3390/rs12101618
- Population spatialization with pixel-level attribute grading by considering scale mismatch issue in regression modeling Y. Mei et al. 10.1080/10095020.2021.2021785
- Emergency flood bulletins for Cyclones Idai and Kenneth: A critical evaluation of the use of global flood forecasts for international humanitarian preparedness and response R. Emerton et al. 10.1016/j.ijdrr.2020.101811
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Latest update: 31 Jan 2023
Short summary
Population data are essential for studies on human–nature relationships, disaster or environmental health. Several global and continental gridded population data have been produced but have never been systematically compared. This article fills this gap and critically compares these gridded population datasets. Through the lens of the
fitness for useconcept it provides users with the knowledge needed to make informed decisions about appropriate data use in relation to the target application.
Population data are essential for studies on human–nature relationships, disaster or...