Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen, 518055, China
Institute of Risk Analysis, Prediction and Management (Risks-X), Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen, 518055, China
Key Laboratory of Earthquake Forecasting and Risk Assessment, Ministry of Emergency Management, Southern University of Science and Technology, Shenzhen, 518055, China
Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen, 518055, China
Institute of Risk Analysis, Prediction and Management (Risks-X), Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen, 518055, China
Key Laboratory of Earthquake Forecasting and Risk Assessment, Ministry of Emergency Management, Southern University of Science and Technology, Shenzhen, 518055, China
Center for Disaster Management and Risk Reduction Technology (CEDIM), Karlsruhe Institute of Technology (KIT), Karlsruhe, 76344, Germany
Geophysical Institute, Karlsruhe Institute of Technology, Karlsruhe, 76187, Germany
Shaun Shuxun Wang
Institute of Risk Analysis, Prediction and Management (Risks-X), Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen, 518055, China
Department of Finance, Southern University of Science and Technology, Shenzhen, 518055, China
Xiaofei Chen
Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen, 518055, China
Institute of Risk Analysis, Prediction and Management (Risks-X), Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen, 518055, China
Key Laboratory of Earthquake Forecasting and Risk Assessment, Ministry of Emergency Management, Southern University of Science and Technology, Shenzhen, 518055, China
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1,650
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92
3,463
90
120
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PDF: 1,721
XML: 92
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BibTeX: 90
EndNote: 120
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Cumulative views and downloads
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Total article views: 2,703 (including HTML, PDF, and XML)
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EndNote
1,202
1,445
56
2,703
62
68
HTML: 1,202
PDF: 1,445
XML: 56
Total: 2,703
BibTeX: 62
EndNote: 68
Views and downloads (calculated since 07 May 2025)
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Total article views: 760 (including HTML, PDF, and XML)
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448
276
36
760
28
52
HTML: 448
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Total: 760
BibTeX: 28
EndNote: 52
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Cumulative views and downloads
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Total article views: 3,463 (including HTML, PDF, and XML)
Thereof 3,382 with geography defined
and 81 with unknown origin.
Total article views: 2,703 (including HTML, PDF, and XML)
Thereof 2,681 with geography defined
and 22 with unknown origin.
Total article views: 760 (including HTML, PDF, and XML)
Thereof 701 with geography defined
and 59 with unknown origin.
A high-resolution fixed-asset model can help improve the accuracy of earthquake loss assessment. We develop a grid-level fixed-asset model for China from 1951 to 2020. We first compile the provincial-level fixed asset from yearbook-related statistics. Then, this dataset is disaggregated into 1 km × 1 km grids by using multiple remote sensing data as the weight indicator. We find that the fixed-asset value increased rapidly after the 1980s and reached CNY 589.31 trillion in 2020.
A high-resolution fixed-asset model can help improve the accuracy of earthquake loss assessment....