80 citations as recorded by crossref.

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3. Dynamic Monthly Population-Exposure-Based Flash-Flood Risk Mapping Using an Explainable XGBoost Framework J. Jia et al. https://doi.org/10.3390/rs18183253
4. The seismic hazard from the Lembang Fault, Indonesia, derived from InSAR and GNSS data E. Hussain et al. https://doi.org/10.5194/nhess-23-3185-2023
5. Temporally Consistent Present Population from Mobile Network Signaling Data for Official Statistics M. Suarez Castillo et al. https://doi.org/10.2478/jos-2023-0025
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8. Digital Mapping and Resilience Indicators, as Pillars of Bucharest’s Seismic Resilience Strategy M. Paunescu et al. https://doi.org/10.3390/infrastructures10020039
9. Risk assessment of people trapped in earthquake based on km grid: a case study of the 2014 Ludian earthquake, China B. Wei et al. https://doi.org/10.1080/19475705.2017.1318795
10. MobRISK: a model for assessing the exposure of road users to flash flood events S. Shabou et al. https://doi.org/10.5194/nhess-17-1631-2017
11. Health-integrated heat risk assessment in Australian cities S. Wang et al. https://doi.org/10.1016/j.eiar.2023.107176
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15. Identification and evaluation of flood-avoidance routes in Tucson, Arizona A. Coles https://doi.org/10.1016/j.ijdrr.2020.101597
16. The framework of public security spatial planning from the perspective of 'Human-Space-Time' interaction S. ZHOU et al. https://doi.org/10.31497/zrzyxb.20210906
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18. Assessing the impact of Syrian refugees on earthquake fatality estimations in southeast Turkey B. Wilson & T. Paradise https://doi.org/10.5194/nhess-18-257-2018
19. Assessment of urban vulnerability to earthquake hazards in Kermanshah Province, Western Iran H. Ganjaeian et al. https://doi.org/10.1016/j.rines.2026.100180
20. Rapid Population Growth throughout Asia’s Earthquake-Prone Areas: A Multiscale Analysis Y. Dou et al. https://doi.org/10.3390/ijerph15091893
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24. Spatio-temporal population modelling as improved exposure information for risk assessments tested in the Autonomous Province of Bolzano K. Renner et al. https://doi.org/10.1016/j.ijdrr.2017.11.011
25. Reviews of Geospatial Information Technology and Collaborative Data Delivery for Disaster Risk Management H. Miyazaki et al. https://doi.org/10.3390/ijgi4041936
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27. A Remote Sensing Method to Assess the Future Multi-Hazard Exposure of Urban Areas C. Salvo & A. Vitale https://doi.org/10.3390/rs15174288
28. Assessment of Population Exposure to Urban Flood at the Building Scale S. Zhu et al. https://doi.org/10.3390/w12113253
29. Spatiotemporal Population Distribution Method for Emergency Evacuation R. Bian & C. Wilmot https://doi.org/10.3141/2532-12
30. Understanding the interacting factors that influence social vulnerability: a case study of the 2016 central Italy earthquake I. Frigerio et al. https://doi.org/10.1111/disa.12403
31. A big data-driven dynamic estimation model of relief supplies demand in urban flood disaster A. Lin et al. https://doi.org/10.1016/j.ijdrr.2020.101682
32. Optimizing warning siren placement for audibility coverage using acoustic modelling and genetic algorithms P. Aumond et al. https://doi.org/10.1080/19475705.2026.2663131
33. Open space suitability analysis for emergency shelter after an earthquake J. Anhorn & B. Khazai https://doi.org/10.5194/nhess-15-789-2015
34. Estimation of Real-time Population Distribution and Implications for Disaster Risk Reduction in Xining City, China B. Wei et al. https://doi.org/10.1007/s11769-026-1650-6
35. Research on the estimation of the real-time population in an earthquake area based on phone signals: A case study of the Jiuzhaigou earthquake C. Xia et al. https://doi.org/10.1007/s12145-019-00418-8
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37. Increase of Elderly Population in the Rainstorm Hazard Areas of China P. Liang et al. https://doi.org/10.3390/ijerph14090963
38. A Rapid Public Health Needs Assessment Framework for after Major Earthquakes Using High-Resolution Satellite Imagery J. Zhao et al. https://doi.org/10.3390/ijerph15061111
39. Risk assessment of people trapped in earthquake disasters based on a single building: a case study in Xichang city, Sichuan Province, China B. Wei et al. https://doi.org/10.1080/19475705.2021.2017358
40. An analysis of the temporal and spatial gathering and dispersion patterns of crowds at the community level after the 2020 M5.1 Tangshan Guye earthquake D. Li et al. https://doi.org/10.1016/j.ijdrr.2021.102331
41. Seismic risk assessment for the downtown of the city of Blida, Algeria F. Bellalem et al. https://doi.org/10.1016/j.ijdrr.2024.104314
42. Informality Creep in Formal Housing: A Data-Driven Risk Prioritization Framework for Global South Peripheries E. Elmas & M. Uğural https://doi.org/10.3390/land15071116
43. Unpacking seismic risk in Italian historic centres: A critical overview for disaster risk reduction F. Giuliani et al. https://doi.org/10.1016/j.ijdrr.2021.102260
44. A decision support model for robust allocation and routing of search and rescue resources after earthquake: a case study G. Ahmadi et al. https://doi.org/10.1007/s12351-020-00591-5
45. Dynamic Assessment of Spatiotemporal Population Distribution Based on Mobile Phone Data: A Case Study in Xining City, China B. Wei et al. https://doi.org/10.1007/s13753-023-00480-3
46. An agent-based model to investigate the effects of urban segregation around the clock on inequalities in health behaviour C. Cottineau-Mugadza et al. https://doi.org/10.1140/epjds/s13688-025-00603-4
47. Rapid Population Growth in Chinese Floodplains from 1990 to 2015 Y. Fang et al. https://doi.org/10.3390/ijerph15081602
48. Uncovering temporal changes in Europe’s population density patterns using a data fusion approach F. Batista e Silva et al. https://doi.org/10.1038/s41467-020-18344-5
49. Research on Fine Estimation of People Trapped after Earthquake on Single Building Level Based on Multi-Source Data S. Xie et al. https://doi.org/10.3390/app13095430
50. Border-independent multi-functional, multi-hazard exposure modelling in Alpine regions M. Pittore et al. https://doi.org/10.1007/s11069-023-06134-3
51. Population and Landslide Risk Evolution in Long Time Series: Case Study of the Valencian Community (1920–2021) I. Cantarino Martí et al. https://doi.org/10.3390/land14061148
52. Seismic loss dynamics in three Asian megacities using a macro-level approach based on socioeconomic exposure indicators G. Mestav Sarica & T. Pan https://doi.org/10.1038/s43247-022-00430-9
53. Spatio-temporal aspects and dimensions in integrated disaster risk management C. Aubrecht et al. https://doi.org/10.1007/s11069-013-0619-9
54. What if the 25 October 2011 event that struck Cinque Terre (Liguria) had happened in Genoa, Italy? Flooding scenarios, hazard mapping and damage estimation F. Silvestro et al. https://doi.org/10.5194/nhess-16-1737-2016
55. Dynamic Assessment of Global Maize Exposure to Extremely High Temperatures Y. Gao et al. https://doi.org/10.1007/s13753-021-00360-8
56. Speeding up the clock in remote sensing: identifying the ‘black spots’ in exposure dynamics by capitalizing on the full spectrum of joint high spatial and temporal resolution C. Aubrecht et al. https://doi.org/10.1007/s11069-015-1857-9
57. The population in China’s earthquake-prone areas has increased by over 32 million along with rapid urbanization C. He et al. https://doi.org/10.1088/1748-9326/11/7/074028
58. Dynamic assessment of earthquake entrapped occupant risk using building-scale population modeling: A case study of Yuxi City, China F. Zhang et al. https://doi.org/10.1016/j.pdisas.2026.100668
59. Representative population distribution layer for Czechia: from methodology to automated solutions O. Rypl et al. https://doi.org/10.1080/17538947.2026.2616577
60. Spatial–temporal human exposure modeling based on land-use at a regional scale in China Z. Qie & L. Rong https://doi.org/10.1016/j.ssci.2016.04.016
61. Modeling the Hourly Distribution of Population at a High Spatiotemporal Resolution Using Subway Smart Card Data: A Case Study in the Central Area of Beijing Y. Ma et al. https://doi.org/10.3390/ijgi6050128
62. Narrowing the gap for city building height predictions C. Watson & J. Elliott https://doi.org/10.1038/s41598-025-15929-2
63. Influence of urban form and function on daytime-nighttime population differences and hazard risk assessments Y. Zhu et al. https://doi.org/10.1038/s42949-025-00282-0
64. GIS-based assessment of population and dwelling exposure to landslide-prone areas in the Valencian Community (Spain) I. Cantarino Martí et al. https://doi.org/10.1080/19475705.2026.2731732
65. Influence of Environmental Factors on the Site Selection and Layout of Ancient Military Towns (Zhejiang Region) L. Tan et al. https://doi.org/10.3390/su14052572
66. Dynamic Relief Items Distribution Model with Sliding Time Window in the Post-Disaster Environment B. Mishra et al. https://doi.org/10.3390/app12168358
67. Assessing population exposure for landslide risk analysis using dasymetric cartography R. Garcia et al. https://doi.org/10.5194/nhess-16-2769-2016
68. Estimating Hilly Areas Population Using a Dasymetric Mapping Approach: A Case of Sri Lanka’s Highest Mountain Range A. Karunarathne & G. Lee https://doi.org/10.3390/ijgi8040166
69. Multi-Hazard Population Exposure in Low-Elevation Coastal Zones of China from 1990 to 2020 S. Feng et al. https://doi.org/10.3390/su151712813
70. Relief Supply-Demand Estimation Based on Social Media in Typhoon Disasters Using Deep Learning and a Spatial Information Diffusion Model S. Li et al. https://doi.org/10.3390/ijgi13010029
71. Designing a cross-regional emergency response network considering spatiotemporal evolution: A smart predict-then-optimise method X. Chen et al. https://doi.org/10.1016/j.tre.2025.104547
72. A new regionally consistent exposure database for Central Asia: population and residential buildings C. Scaini et al. https://doi.org/10.5194/nhess-24-929-2024
73. Mobility behaviors shift disparity in flood exposure in U.S. population groups B. Li et al. https://doi.org/10.1016/j.ijdrr.2024.104545
74. Reprint of: Spatial–temporal human exposure modeling based on land-use at a regional scale in China Z. Qie & L. Rong https://doi.org/10.1016/j.ssci.2016.04.027
75. Risk and space: modelling the accessibility of stroke centers using day- & nighttime population distribution and different transportation scenarios S. Rauch et al. https://doi.org/10.1186/s12942-021-00284-y
76. VGDI – Advancing the Concept: Volunteered Geo‐Dynamic Information and its Benefits for Population Dynamics Modeling C. Aubrecht et al. https://doi.org/10.1111/tgis.12203
77. Impact of Temporal Population Distribution on Earthquake Loss Estimation: A Case Study on Sylhet, Bangladesh S. Ara https://doi.org/10.1007/s13753-014-0033-2
78. Migration as a hidden risk factor in seismic fatality: spatial modeling of the Chi-Chi earthquake and suburban syndrome T. Chen et al. https://doi.org/10.5194/nhess-24-4457-2024
79. Assessing spatial benefits of urban regeneration programs in a highly vulnerable urban context: A case study in Catania, Italy D. La Rosa et al. https://doi.org/10.1016/j.landurbplan.2016.05.031
80. Impact of population spatiotemporal patterns on earthquake human losses J. Dabbeek et al. https://doi.org/10.1016/j.ijdrr.2025.105455