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29. Identification of Industrial Land Parcels and Its Implications for Environmental Risk Management in the Beijing–Tianjin–Hebei Urban Agglomeration Z. Wang et al. 10.3390/su12010174
30. Advances on the Global Human Settlement Layer by joint assessment of Earth Observation and population survey data M. Pesaresi et al. 10.1080/17538947.2024.2390454
31. 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
32. Multi-Scale Dynamics and Spatial Consistency of Economy and Population Based on NPP/VIIRS Nighttime Light Data and Population Imagery: A Case Study of the Yangtze River Delta Y. Xu et al. 10.3390/rs16152806
33. First year with COVID-19: Assessment and prospects R. Bergquist et al. 10.4081/gh.2020.953
34. Population, land use and economic exposure estimates for Europe at 100 m resolution from 1870 to 2020 D. Paprotny & M. Mengel 10.1038/s41597-023-02282-0
35. Global population datasets overestimate flood exposure in Sweden K. Karagiorgos et al. 10.1038/s41598-024-71330-5
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37. Geospatial analysis of food waste generation at the consumer-level in high-income regions, 2000–2023 – A scoping review V. Thaore et al. 10.1016/j.envres.2024.120247
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39. Fine-grained, spatiotemporal datasets measuring 200 years of land development in the United States J. Uhl et al. 10.5194/essd-13-119-2021
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45. Assessing the relative accuracy of gridded population sampling: results from an election survey experiment S. Ford & M. Kirwin 10.1080/13645579.2022.2091200
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47. GHS-POP Accuracy Assessment: Poland and Portugal Case Study B. Calka & E. Bielecka 10.3390/rs12071105
48. 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
49. High-resolution population estimation using household survey data and building footprints G. Boo et al. 10.1038/s41467-022-29094-x
50. The Missing Millions in Maps: Exploring Causes of Uncertainties in Global Gridded Population Datasets M. Kuffer et al. 10.3390/ijgi11070403
51. Exploring spatial feedbacks between adaptation policies and internal migration patterns due to sea-level rise L. Reimann et al. 10.1038/s41467-023-38278-y
52. Improvement of a Dasymetric Method for Implementing Sustainable Development Goal 11 Indicators at an Intra-Urban Scale M. Aquilino et al. 10.3390/rs13142835
53. Different Spatiotemporal Patterns in Global Human Population and Built‐Up Land J. Gao & B. O'Neill 10.1029/2020EF001920
54. Estimation of pixel-level seismic vulnerability of the building environment based on mid-resolution optical remote sensing images X. Fan et al. 10.1016/j.jag.2021.102339
55. Multiple Global Population Datasets: Differences and Spatial Distribution Characteristics R. Chen et al. 10.3390/ijgi9110637
56. A novel urban population-land coupling simulation model: Integrating spatial equilibrium and macro-micro strategies Y. Guo et al. 10.1016/j.jag.2024.104002
57. Warming-induced cryosphere changes predict drier Andean eco-regions A. Al-Yaari et al. 10.1088/1748-9326/ad6ea6
58. Asset exposure data for global physical risk assessment S. Eberenz et al. 10.5194/essd-12-817-2020
59. Global population profile of tropical cyclone exposure from 2002 to 2019 R. Jing et al. 10.1038/s41586-023-06963-z
60. Spatiotemporal dynamics of population density in China using nighttime light and geographic weighted regression method* W. Guo et al. 10.1080/17538947.2023.2233493
61. Incorporating Geographic Information Science and Technology in Response to the COVID-19 Pandemic C. Smith & J. Mennis 10.5888/pcd17.200246
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63. Dasymetric population mapping based on US census data and 30-m gridded estimates of impervious surface R. Swanwick et al. 10.1038/s41597-022-01603-z
64. Population development as a driver of coastal risk: Current trends and future pathways L. Reimann et al. 10.1017/cft.2023.3
65. 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
66. Experimentelle georeferenzierte Bevölkerungszahl auf Basis der Bevölkerungsfortschreibung und Mobilfunkdaten S. Hadam 10.1007/s11943-023-00320-2
67. Using satellite imagery to understand and promote sustainable development M. Burke et al. 10.1126/science.abe8628
68. Improving intelligent dasymetric mapping population density estimates at 30 m resolution for the conterminous United States by excluding uninhabited areas J. Baynes et al. 10.5194/essd-14-2833-2022
69. Spatial access inequities and childhood immunisation uptake in Kenya N. Joseph et al. 10.1186/s12889-020-09486-8
70. Approaches and tools for user-driven provenance and data quality information in spatial data infrastructures J. Fischer et al. 10.1080/17538947.2023.2198778
71. Global riverine flood risk – how do hydrogeomorphic floodplain maps compare to flood hazard maps? S. Lindersson et al. 10.5194/nhess-21-2921-2021
72. Global Harmonization of Urbanization Measures: Proceed with Care D. Balk et al. 10.3390/rs13244973
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74. Climatic Criteria of the Need for Preventive Adaptation A. Ginzburg et al. 10.1134/S0001433822060068
75. Impact of state weights on national vaccination coverage estimates from household surveys in Nigeria T. Dong et al. 10.1016/j.vaccine.2020.05.026
76. Stability and Changes in the Spatial Distribution of China’s Population in the Past 30 Years Based on Census Data Spatialization X. Xu et al. 10.3390/rs15061674
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84. Disaggregating census data for population mapping using a Bayesian Additive Regression Tree model O. Yankey et al. 10.1016/j.apgeog.2024.103416
85. Evaluating the Accuracy of Gridded Population Estimates in Slums: A Case Study in Nigeria and Kenya D. Thomson et al. 10.3390/urbansci5020048
86. Human and infrastructure exposure to large wildfires in the United States A. Modaresi Rad et al. 10.1038/s41893-023-01163-z
87. Evaluation of NLDAS-2 and Downscaled Air Temperature data in Florida J. Jung et al. 10.1080/02723646.2021.1928878
88. 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
89. A simulated ‘sandbox’ for exploring the modifiable areal unit problem in aggregation and disaggregation J. Nieves et al. 10.1038/s41597-024-03061-1
90. Implications for Tracking SDG Indicator Metrics with Gridded Population Data C. Tuholske et al. 10.3390/su13137329
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92. How accurate are WorldPop-Global-Unconstrained gridded population data at the cell-level?: A simulation analysis in urban Namibia D. Thomson et al. 10.1371/journal.pone.0271504
93. The Unseen Population: Underestimation of Slum Dwellers in Cities of the Global South J. Breuer et al. 10.2139/ssrn.4098362
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95. Cropland abandonment in the context of drought, economic restructuring, and migration in northeast Syria L. Eklund et al. 10.1088/1748-9326/ad1723
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98. 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
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100. 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
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108. Walkability der Stadt Regensburg – eine Mixed-methods-Untersuchung mittels QGIS und Walk Audits M. Heudobler et al. 10.1007/s11553-024-01165-5
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163. Delimitation of rural and urban areas from spatial data in statistical grids: the province of Jaén (Spain) as a case study J. Sánchez-Martínez & A. Garrido-Almonacid 10.1080/17445647.2024.2301980
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