Wind disasters adaptation in cities in a changing climate: A systematic review

43. Vera-Baceta M-A, Thelwall M, Kousha K. Web of Science and Scopus language coverage. Sciento- metrics. 2019; 121: 1803–1813. https://doi.org/10.1007/s11192-019-03264-z 44. Falagas ME, Pitsouni EI, Malietzis GA, Pappas G. Comparison of PubMed, Scopus, Web of Science, and Google Scholar: Strengths and weaknesses. FASEB j. 2008; 22: 338–342. https://doi.org/10. 1096/fj.07-9492LSF PMID: 17884971 45. Jelodar H, Wang Y, Yuan C, Feng X, Jiang X, Li Y, et al. Latent dirichlet allocation (LDA) and topic modeling: Models, applications, a survey. Multimed Tools Appl. 2019; 78: 15169–15211. https://doi. org/10.1007/s11042-018-6894-4 46. Blei DM, NG AY, Jordan MI. Latent dirichlet allocation. J Mach Learn Res. 2003; 3: 993–1022. 47. Lamb WF, Callaghan MW, Creutzig F, Khosla R, Minx JC. The literature landscape on 1.5˚C climate change and cities. Current Opinion in Environmental Sustainability. 2018; 30: 26–34. https://doi.org/ 10.1016/j.cosust.2018.02.008 48. Lamb WF, Creutzig F, Callaghan MW, Minx JC. Learning about urban climate solutions from case studies. Nat Clim Chang. 2019; 9: 279–287. https://doi.org/10.1038/s41558-019-0440-x 49. Wang Y-X, Zhang Y-J. Nonnegative matrix factorization: A comprehensive review. IEEE Trans Knowl Data Eng. 2013; 25: 1336–1353. https://doi.org/10.1109/TKDE.2012.51 50. McCallum A, Mimno DM, Wallach HM. Rethinking LDA: Why priors matter. In: Bengio Y, Schuurmans D, Lafferty JD, Williams CKI, Culotta A, editors. Advances in neural information processing systems 22. 2009. pp. 1973–1981.

51. Climate change 2014: synthesis report. Contribution of working groups I, II and III to the fifth assess- ment report of the intergovernmental panel on climate change. Geneva, Switzerland; 2015. 52. Chan J, DuBois B, Tidball KG. Refuges of local resilience: Community gardens in post-Sandy New York City. Urban For Urban Green. 2015; 14: 625–635. https://doi.org/10.1016/j.ufug.2015.06.005 53. Amante CJ. Uncertain seas: Probabilistic modeling of future coastal flood zones. Int J Geogr Inf Sci. 2019; 33: 2188–2217. https://doi.org/10.1080/13658816.2019.1635253 54. Lontone A, Ernsˇteins R, Lagzdin¸a E¯ , Vanaga M, Sˇ teinberga Z. Flood risk governance and communica- tion development for coastal municipalities: Information and education, participation and practise self- experience. 2017. pp. 373–385. https://doi.org/10.5593/sgem2017/52 55. Gopalakrishnan T, Hasan MK, Haque ATMS, Jayasinghe SL, Kumar L. Sustainability of coastal agri- culture under climate change. Sustainability. 2019; 11: 7200. https://doi.org/10.3390/su11247200 56. Lee Y-J. A synthesized biophysical and social vulnerability assessment for Taiwan. IOP Conf Ser: Earth Environ Sci. 2017; 94: 012161. https://doi.org/10.1088/1755-1315/94/1/012161 57. Ayeb-Karlsson S, van der Geest K, Ahmed I, Huq S, Warner K. A people-centred perspective on cli- mate change, environmental stress, and livelihood resilience in Bangladesh. Sustain Sci. 2016; 11: 679–694. https://doi.org/10.1007/s11625-016-0379-z PMID: 30174739

58. Chuang W-C, Eason T, Garmestani A, Roberts C. Impact of Hurricane Katrina on the coastal systems of southern Louisiana. Front Environ Sci. 2019; 7: 68. https://doi.org/10.3389/fenvs.2019.00068 PMID: 32601598 59. Hopper T, Meixler MS. Modeling coastal vulnerability through space and time. PLoS ONE. 2016; 11: e0163495. https://doi.org/10.1371/journal.pone.0163495 PMID: 27732674 60. Lane K, Charles-Guzman K, Wheeler K, Abid Z, Graber N, Matte T. Health effects of coastal storms and flooding in urban areas: A review and vulnerability assessment. J Environ Public Health. 2013; 2013: 1–13. https://doi.org/10.1155/2013/913064 PMID: 23818911 61. Ghaffarian S, Kerle N, Filatova T. Remote sensing-based proxies for urban disaster risk management and resilience: A Review. Remote Sens. 2018; 10: 1760. https://doi.org/10.3390/rs10111760 62. Kim HG, Lee DK, Jung H, Kil S-H, Park JH, Park C, et al. Finding key vulnerable areas by a climate change vulnerability assessment. Nat Hazards. 2016; 81: 1683–1732. https://doi.org/10.1007/ s11069-016-2151-1 63. Estember RD, Abiog MCM. Vulnerability assessment of Pangasinan province to typhoons, floods and landslides. Bandung, Indonesia; 2018. p. 020060. https://doi.org/10.1063/1.5080873 64. Serafim MB, Bonetti J. Vulnerability of Santa Catarina Beaches to coastal erosion and flooding: A methodological approach based on a multicriterial index. Quat Environ Geosci. 2017; 8: 36–54. https://doi.org/10.5380/abequa.v8i2.47281 65. Mallari Ezra CA. Climate change vulnerability assessment in the agriculture sector: Typhoon Santi

experience. Procedia Soc Behav Sci. 2016; 216: 440–451. https://doi.org/10.1016/j.sbspro.2015.12. 058 PLOS ONE Review on wind adaptation in cities PLOS ONE | https://doi.org/10.1371/journal.pone.0248503 March 17, 2021 19 / 26