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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2,847
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5,625
200
233
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PDF: 2,847
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EndNote: 233
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Total article views: 4,405 (including HTML, PDF, and XML)
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1,939
2,263
203
4,405
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159
HTML: 1,939
PDF: 2,263
XML: 203
Total: 4,405
BibTeX: 164
EndNote: 159
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Total article views: 1,220 (including HTML, PDF, and XML)
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593
584
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1,220
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HTML: 593
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BibTeX: 36
EndNote: 74
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Cumulative views and downloads
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Viewed (geographical distribution)
Total article views: 5,625 (including HTML, PDF, and XML)
Thereof 5,405 with geography defined
and 220 with unknown origin.
Total article views: 4,405 (including HTML, PDF, and XML)
Thereof 4,269 with geography defined
and 136 with unknown origin.
Total article views: 1,220 (including HTML, PDF, and XML)
Thereof 1,136 with geography defined
and 84 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....
