Geospatial modelling of post-cyclone Shaheen recovery using nighttime light data and MGWR
文献类型：期刊论文
| 作者 | Mansour, Shawky2,3; Alahmadi, Mohammed4; Darby, Stephen5; Leyland, Julian1; Atkinson, Peter M.1,5,6 |
| 刊名 | INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
 |
| 出版日期 | 2023-06-01 |
| 卷号 | 93页码:19 |
| ISSN号 | 2212-4209 |
| 关键词 | Post-Shaheen cyclone recovery GIS MGWR Night time light NTL Data Community resilience |
| DOI | 10.1016/j.ijdrr.2023.103761 |
| 通讯作者 | Mansour, Shawky(shmansour@squ.edu.om) |
| 英文摘要 | Tropical cyclones are a highly destructive natural hazard that can cause extensive damage to as-sets and loss of life. This is especially true for the many coastal cities and communities that lie in their paths. Despite their significance globally, research on post-cyclone recovery rates has gener-ally been qualitative and, crucially, has lacked spatial definition. Here, we used freely available satellite nighttime light data to model spatially the rate of post-cyclone recovery and selected sev-eral spatial covariates (socioeconomic, environmental and topographical factors) to explain the rate of recovery. We fitted three types of regression model to characterize the relationship be-tween rate of recovery and the selected covariates; one global model (linear regression) and two local models (geographically weighted regression, GWR, and multiscale geographically weighted regression, MGWR). Despite the rate of recovery being a challenging variable to predict, the two local models explained 42% (GWR) and 51% (MGWR) of the variation, compared to the global linear model which explained only 13% of the variation. Importantly, the local models revealed which covariates were explanatory at which places; information that could be crucial to policy -makers and local decision-makers in relation to disaster preparedness and recovery planning. |
| WOS关键词 | GEOGRAPHICALLY WEIGHTED REGRESSION ; COMMUNITY RESILIENCE ; DISASTER RESILIENCE ; HURRICANE KATRINA ; SATELLITE IMAGERY ; VULNERABILITY ; REMOTE ; HAZARDS |
| WOS研究方向 | Geology ; Meteorology & Atmospheric Sciences ; Water Resources |
| 语种 | 英语 |
| 出版者 | ELSEVIER |
| WOS记录号 | WOS:001009112600001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/194849]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Mansour, Shawky |
| 作者单位 | 1.Univ Lancaster, Lancaster Environm Ctr, Lancaster LA1 4YR, England 2.Sultan Qaboos Univ, Coll Arts & Social Sci, Geog Dept, POB 42, Muscat 123, Oman 3.Alexandria Univ, Fac Arts, Dept Geog & GIS, Al Shatby POB 21526, Alexandria, Egypt 4.King Abdulaziz City Sci & Technol KACST, Earth & Space Sci Inst, Future Econ Sect, POB 6086, Riyadh 11442, Saudi Arabia 5.Univ Southampton, Sch Geog & Environm Sci, Southampton SO17 1BJ, England 6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, 11A Datun Rd, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Mansour, Shawky,Alahmadi, Mohammed,Darby, Stephen,et al. Geospatial modelling of post-cyclone Shaheen recovery using nighttime light data and MGWR[J]. INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION,2023,93:19. |
| APA | Mansour, Shawky,Alahmadi, Mohammed,Darby, Stephen,Leyland, Julian,&Atkinson, Peter M..(2023).Geospatial modelling of post-cyclone Shaheen recovery using nighttime light data and MGWR.INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION,93,19. |
| MLA | Mansour, Shawky,et al."Geospatial modelling of post-cyclone Shaheen recovery using nighttime light data and MGWR".INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION 93(2023):19. |
入库方式： OAI收割
来源：地理科学与资源研究所
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