Bibliometric Analysis of Global Research Progress on Coastal Flooding 1995-2016

GAO Chao; RUAN Tian

doi:10.1007/s11769-018-0996-9

Volume 28 Issue 6

Turn off MathJax

Article Contents

Article Navigation > Chinese Geographical Science > 2018 > 28(6): 998-1008

GAO Chao, RUAN Tian. Bibliometric Analysis of Global Research Progress on Coastal Flooding 1995-2016[J]. Chinese Geographical Science, 2018, 28(6): 998-1008. doi: 10.1007/s11769-018-0996-9

Citation:

GAO Chao, RUAN Tian. Bibliometric Analysis of Global Research Progress on Coastal Flooding 1995-2016[J]. Chinese Geographical Science, 2018, 28(6): 998-1008. doi: 10.1007/s11769-018-0996-9

Bibliometric Analysis of Global Research Progress on Coastal Flooding 1995-2016

doi: 10.1007/s11769-018-0996-9

GAO Chao^1
,,
RUAN Tian²

1.
Department of Geography & Spatial Information Techniques, Ningbo University, Ningbo 315211, China;
2.
College of Territorial Resources and Tourism, Anhui Normal University, Wuhu 241000, China

Funds: Under the auspices of National Natural Science Foundation of China (No. 41571018)

More Information

Corresponding author: GAO Chao.E-mail:gaoqinchao1@163.com
Received Date: 2018-01-29
Rev Recd Date: 2018-04-17
Publish Date: 2018-12-27

Abstract

Global research progress on coastal flooding was studied using a bibliometric evaluation of publications listed in the Web of Science extended scientific citation index. There was substantial growth in coastal flooding research output, with increasing publications, a higher collaboration index, and more references during the 1995-2016 period. The USA has taken a dominant position in coastal flooding research, with the US Geological Survey leading the publications ranking. Research collaborations at institutional scales have become more important than those at global scales. International collaborative publications consistently drew more citations than those from a single country. Furthermore, coastal flooding research included combinations of multi-disciplinary categories, including ‘Geology’ and ‘Environmental Sciences & Ecology’. The most important coastal flooding research sites were wetlands and estuaries. While numerical modeling and 3S (Remote sensing, RS; Geography information systems, GIS; Global positioning systems, GPS) technology were the most commonly used methods for studying coastal flooding, Lidar gained in popularity. The vulnerability and adaptation of coastal environments, their resilience after flooding, and ecosystem services function showed increases in interest.
- coastal flood,
- scientific outputs,
- bibliometric analysis,
- research trends,
- Web of Science

References

[1]	Belter C W, Seidel D J, 2013. A bibliometric analysis of climate engineering research. Wiley Interdisciplinary Reviews-Climate Change 4(5):417-427. doi: 10.1002/wcc.229
[2]	Cobo M J, López-Herrera A G, Herrera-Viedma E et al., 2011. Science mapping software tools:review, analysis, and cooper-ative study among tools. Journal of the American Society for Information Science and Technology, 62(7):1382-1402. doi: 10.1002/asi.21525
[3]	Deb M, Ferreira C M, 2017. Potential impacts of the Sunderban mangrove degradation on future coastal flooding in Bangladesh. Journal of Hydro-Environment Research, 17:30-46. doi: 10.1016/j.jher.2016.11.005
[4]	Freire P, Tavares A O, Sá L et al., 2016. A local-scale approach to estuarine flood risk management. Natural Hazards, 84(3):1705-1739. doi: 10.1007/s11069-016-2510-y
[5]	Fu H Z, Wang M H, Ho Y S, 2013. Mapping of drinking water research:a bibliometric analysis of research output during 1992-2011. Science of the Total Environment, 443:757-765. doi: 10.1016/j.scitotenv.2012.11.061
[6]	Garner A J, Mann M E, Emanuel K A et al., 2017. Impact of cli-mate change on New York City's coastal flood hazard:in-creasing flood heights from the preindustrial to 2300 CE. Pro-ceedings of the National Academy of Sciences of the United States of America, 114(45):11861-11866. doi:10.1073/pnas. 1703568114
[7]	Herrera-Pantoja M, Hiscock K M, 2015. Projected impacts of climate change on water availability indicators in a semi-arid region of central Mexico. Environmental Science & Policy, 54:81-89. doi: 10.1016/j.envsci.2015.06.020
[8]	Hirsch J E, 2005. An index to quantify an individual's scientific research output. Proceedings of the National Academy of Sci-ences of the United States of America, 102(46):16569-16572. doi: 10.1073/pnas.0507655102
[9]	Horton B P, Rahmstorf S, Engelhart S E et al., 2014. Expert as-sessment of sea-level rise by AD 2100 and AD 2300. Quater-nary Science Reviews, 84:1-6. doi:10.1016/j.quascirev. 2013.11.002
[10]	Karamouz M, Ahmadvand F, Zahmatkesh Z, 2017. Distributed hydrologic modeling of coastal flood inundation and damage:nonstationary approach. Journal of Irrigation and Drainage Engineering, 143(8). doi:10.1061/(ASCE)IR.1943-4774.000 1173
[11]	Keiser J, Utzinger J, 2005. Trends in the core literature on tropical medicine:a bibliometric analysis from 1952-2002. Scien-tometrics, 62(3):351-365. doi: 10.1007/s11192-005-0027-3
[12]	Kelly B D, Lundon D, Glynn R et al., 2012. A bibliometric analysis of urological oncology research output over 55 years. BJU International, 109:66-67.
[13]	Levermann A, Clark P U, Marzeion B et al., 2013. The multimil-lennial sea-level commitment of global warming. Proceedings of the National Academy of Sciences of the United States of America, 110(34):13745-13750. doi:10.1073/pnas.121941 4110
[14]	Li L L, Ding G H, Feng N et al., 2009. Global stem cell research trend:bibliometric analysis as a tool for mapping of trends from 1991 to 2006. Scientometrics, 80(1):39-58. doi:10. 1007/s11192-008-1939-5
[15]	Lin N, Shullman E, 2017. Dealing with hurricane surge flooding in a changing environment:part I. Risk assessment considering storm climatology change, sea level rise, and coastal de-velopment. Stochastic Environmental Research and Risk As-sessment, 31(9):2379-2400. doi: 10.1007/s00477-016-1377-5
[16]	Liu X J, Zhang L, Hong S, 2011. Global biodiversity research during 1900-2009:a bibliometric analysis. Biodiversity and Conservation, 20(4):807-826. doi: 10.1007/s10531-010-9981-z
[17]	McCune B, Mefford M J, 1999. Multivariate Analysis of Ecolog-ical Data, Version 4.20. Gleneden Beach:MjM Software De-sign.
[18]	Mentzafou A, Markogianni V, Dimitriou E et al., 2017. The use of geospatial technologies in flood hazard mapping and assess-ment:case study from river Evros. Pure and Applied Geo-physics, 174(2):679-700. doi: 10.1007/s00024-016-1433-6
[19]	Morel C M, Serruya S J, Penna G O et al., 2009. Co-authorship network analysis:a powerful tool for strategic planning of re-search, development and capacity building programs on ne-glected diseases. PLoS Neglected Tropical Diseases, 3(8):e501. doi: 10.1371/journal.pntd.0000501
[20]	Muis S, Güneralp B, Jongman B et al., 2015. Flood risk and ad-aptation strategies under climate change and urban expansion:a probabilistic analysis using global data. Science of the Total Environment, 538:445-457. doi:10.1016/j.scitotenv.2015. 08.068
[21]	Pritchar A, 1969. Statistical bibliography or bibliometrics. Journal of Documentation, 25(4):348-349.
[22]	Qian F, He M C, Song Y H et al., 2015. A bibliometric analysis of global research progress on pharmaceutical wastewater treat-ment during 1994-2013. Environmental Earth Sciences, 73(9):4995-5005. doi: 10.1007/s12665-015-4183-3
[23]	Riahi K, Rao S, Krey V et al., 2011. RCP 8.5-a scenario of comparatively high greenhouse gas emissions. Climatic Change, 109(1-2):33-57. doi: 10.1007/s10584-011-0149-y
[24]	Silva S F, Martinho M, Capitão R et al., 2017. An index-based method for coastal-flood risk assessment in low-lying areas (Costa de Caparica, Portugal). Ocean & Coastal Management, 144:90-104. doi: 10.1016/j.ocecoaman.2017.04.010
[25]	Wadey M, Brown S, Nicholls R J et al., 2017. Coastal flooding in the Maldives:an assessment of historic events and their im-plications. Natural Hazards, 89(1):131-159. doi:10.1007/s 11069-017-2957-5
[26]	Wong T E, Bakker A M R, Keller K, 2017a. Impacts of Antarctic fast dynamics on sea-level projections and coastal flood de-fense. Climatic Change, 144(2):347-364. doi:10.1007/s 10584-017-2039-4
[27]	Wong T E, Bakker A M R, Ruckert K et al., 2017b. Brick v0.2, A simple, accessible, and transparent model framework for climate and regional sea-level projections. Geoscientific Model Development, 10(7):2741-2760. doi: 10.5194/gmd-10-2741-2017
[28]	Wong T E, Keller K, 2017. Deep uncertainty surrounding coastal flood risk projections:a case study for New Orleans. Earth's Future, 5(10):1015-1026. doi: 10.1002/2017EF000607
[29]	Xie S D, Zhang J, Ho Y S, 2008. Assessment of world aerosol research trends by bibliometric analysis. Scientometrics, 77(1):113-130. doi: 10.1007/s11192-007-1928-0
[30]	Xu Y Y, Boeing W J, 2013. Mapping biofuel field:a bibliometric evaluation of research output. Renewable and Sustainable En-ergy Reviews, 28:82-91. doi: 10.1016/j.rser.2013.07.027
[31]	Zahmatkesh Z, Karamouz M, 2017. An uncertainty-based framework to quantifying climate change impacts on coastal flood vulnerability:case study of New York City. Environ-mental Monitoring and Assessment, 189(11):567. doi:10. 1007/s10661-017-6282-y

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Get Citation

PDF

XML

Article Metrics

Article views(393) PDF downloads(357) Cited by()

Proportional views

Bibliometric Analysis of Global Research Progress on Coastal Flooding 1995-2016

1. Department of Geography & Spatial Information Techniques, Ningbo University, Ningbo 315211, China;

2. College of Territorial Resources and Tourism, Anhui Normal University, Wuhu 241000, China

Funds: Under the auspices of National Natural Science Foundation of China (No. 41571018)

Corresponding author: GAO Chao.E-mail:gaoqinchao1@163.com

Received Date: 2018-01-29

Rev Recd Date: 2018-04-17

Publish Date: 2018-12-27

Key words:

Abstract: Global research progress on coastal flooding was studied using a bibliometric evaluation of publications listed in the Web of Science extended scientific citation index. There was substantial growth in coastal flooding research output, with increasing publications, a higher collaboration index, and more references during the 1995-2016 period. The USA has taken a dominant position in coastal flooding research, with the US Geological Survey leading the publications ranking. Research collaborations at institutional scales have become more important than those at global scales. International collaborative publications consistently drew more citations than those from a single country. Furthermore, coastal flooding research included combinations of multi-disciplinary categories, including ‘Geology’ and ‘Environmental Sciences & Ecology’. The most important coastal flooding research sites were wetlands and estuaries. While numerical modeling and 3S (Remote sensing, RS; Geography information systems, GIS; Global positioning systems, GPS) technology were the most commonly used methods for studying coastal flooding, Lidar gained in popularity. The vulnerability and adaptation of coastal environments, their resilience after flooding, and ecosystem services function showed increases in interest.

HTML

Reference (31)

[1]	Belter C W, Seidel D J, 2013. A bibliometric analysis of climate engineering research. Wiley Interdisciplinary Reviews-Climate Change 4(5):417-427. doi:10.1002/wcc.229
[2]	Cobo M J, López-Herrera A G, Herrera-Viedma E et al., 2011. Science mapping software tools:review, analysis, and cooper-ative study among tools. Journal of the American Society for Information Science and Technology, 62(7):1382-1402. doi:10.1002/asi.21525
[3]	Deb M, Ferreira C M, 2017. Potential impacts of the Sunderban mangrove degradation on future coastal flooding in Bangladesh. Journal of Hydro-Environment Research, 17:30-46. doi:10.1016/j.jher.2016.11.005
[4]	Freire P, Tavares A O, Sá L et al., 2016. A local-scale approach to estuarine flood risk management. Natural Hazards, 84(3):1705-1739. doi:10.1007/s11069-016-2510-y
[5]	Fu H Z, Wang M H, Ho Y S, 2013. Mapping of drinking water research:a bibliometric analysis of research output during 1992-2011. Science of the Total Environment, 443:757-765. doi:10.1016/j.scitotenv.2012.11.061
[6]	Garner A J, Mann M E, Emanuel K A et al., 2017. Impact of cli-mate change on New York City's coastal flood hazard:in-creasing flood heights from the preindustrial to 2300 CE. Pro-ceedings of the National Academy of Sciences of the United States of America, 114(45):11861-11866. doi:10.1073/pnas. 1703568114
[7]	Herrera-Pantoja M, Hiscock K M, 2015. Projected impacts of climate change on water availability indicators in a semi-arid region of central Mexico. Environmental Science & Policy, 54:81-89. doi:10.1016/j.envsci.2015.06.020
[8]	Hirsch J E, 2005. An index to quantify an individual's scientific research output. Proceedings of the National Academy of Sci-ences of the United States of America, 102(46):16569-16572. doi:10.1073/pnas.0507655102
[9]	Horton B P, Rahmstorf S, Engelhart S E et al., 2014. Expert as-sessment of sea-level rise by AD 2100 and AD 2300. Quater-nary Science Reviews, 84:1-6. doi:10.1016/j.quascirev. 2013.11.002
[10]	Karamouz M, Ahmadvand F, Zahmatkesh Z, 2017. Distributed hydrologic modeling of coastal flood inundation and damage:nonstationary approach. Journal of Irrigation and Drainage Engineering, 143(8). doi:10.1061/(ASCE)IR.1943-4774.000 1173
[11]	Keiser J, Utzinger J, 2005. Trends in the core literature on tropical medicine:a bibliometric analysis from 1952-2002. Scien-tometrics, 62(3):351-365. doi:10.1007/s11192-005-0027-3
[12]	Kelly B D, Lundon D, Glynn R et al., 2012. A bibliometric analysis of urological oncology research output over 55 years. BJU International, 109:66-67.
[13]	Levermann A, Clark P U, Marzeion B et al., 2013. The multimil-lennial sea-level commitment of global warming. Proceedings of the National Academy of Sciences of the United States of America, 110(34):13745-13750. doi:10.1073/pnas.121941 4110
[14]	Li L L, Ding G H, Feng N et al., 2009. Global stem cell research trend:bibliometric analysis as a tool for mapping of trends from 1991 to 2006. Scientometrics, 80(1):39-58. doi:10. 1007/s11192-008-1939-5
[15]	Lin N, Shullman E, 2017. Dealing with hurricane surge flooding in a changing environment:part I. Risk assessment considering storm climatology change, sea level rise, and coastal de-velopment. Stochastic Environmental Research and Risk As-sessment, 31(9):2379-2400. doi:10.1007/s00477-016-1377-5
[16]	Liu X J, Zhang L, Hong S, 2011. Global biodiversity research during 1900-2009:a bibliometric analysis. Biodiversity and Conservation, 20(4):807-826. doi:10.1007/s10531-010-9981-z
[17]	McCune B, Mefford M J, 1999. Multivariate Analysis of Ecolog-ical Data, Version 4.20. Gleneden Beach:MjM Software De-sign.
[18]	Mentzafou A, Markogianni V, Dimitriou E et al., 2017. The use of geospatial technologies in flood hazard mapping and assess-ment:case study from river Evros. Pure and Applied Geo-physics, 174(2):679-700. doi:10.1007/s00024-016-1433-6
[19]	Morel C M, Serruya S J, Penna G O et al., 2009. Co-authorship network analysis:a powerful tool for strategic planning of re-search, development and capacity building programs on ne-glected diseases. PLoS Neglected Tropical Diseases, 3(8):e501. doi:10.1371/journal.pntd.0000501
[20]	Muis S, Güneralp B, Jongman B et al., 2015. Flood risk and ad-aptation strategies under climate change and urban expansion:a probabilistic analysis using global data. Science of the Total Environment, 538:445-457. doi:10.1016/j.scitotenv.2015. 08.068
[21]	Pritchar A, 1969. Statistical bibliography or bibliometrics. Journal of Documentation, 25(4):348-349.
[22]	Qian F, He M C, Song Y H et al., 2015. A bibliometric analysis of global research progress on pharmaceutical wastewater treat-ment during 1994-2013. Environmental Earth Sciences, 73(9):4995-5005. doi:10.1007/s12665-015-4183-3
[23]	Riahi K, Rao S, Krey V et al., 2011. RCP 8.5-a scenario of comparatively high greenhouse gas emissions. Climatic Change, 109(1-2):33-57. doi:10.1007/s10584-011-0149-y
[24]	Silva S F, Martinho M, Capitão R et al., 2017. An index-based method for coastal-flood risk assessment in low-lying areas (Costa de Caparica, Portugal). Ocean & Coastal Management, 144:90-104. doi:10.1016/j.ocecoaman.2017.04.010
[25]	Wadey M, Brown S, Nicholls R J et al., 2017. Coastal flooding in the Maldives:an assessment of historic events and their im-plications. Natural Hazards, 89(1):131-159. doi:10.1007/s 11069-017-2957-5
[26]	Wong T E, Bakker A M R, Keller K, 2017a. Impacts of Antarctic fast dynamics on sea-level projections and coastal flood de-fense. Climatic Change, 144(2):347-364. doi:10.1007/s 10584-017-2039-4
[27]	Wong T E, Bakker A M R, Ruckert K et al., 2017b. Brick v0.2, A simple, accessible, and transparent model framework for climate and regional sea-level projections. Geoscientific Model Development, 10(7):2741-2760. doi:10.5194/gmd-10-2741-2017
[28]	Wong T E, Keller K, 2017. Deep uncertainty surrounding coastal flood risk projections:a case study for New Orleans. Earth's Future, 5(10):1015-1026. doi:10.1002/2017EF000607
[29]	Xie S D, Zhang J, Ho Y S, 2008. Assessment of world aerosol research trends by bibliometric analysis. Scientometrics, 77(1):113-130. doi:10.1007/s11192-007-1928-0
[30]	Xu Y Y, Boeing W J, 2013. Mapping biofuel field:a bibliometric evaluation of research output. Renewable and Sustainable En-ergy Reviews, 28:82-91. doi:10.1016/j.rser.2013.07.027
[31]	Zahmatkesh Z, Karamouz M, 2017. An uncertainty-based framework to quantifying climate change impacts on coastal flood vulnerability:case study of New York City. Environ-mental Monitoring and Assessment, 189(11):567. doi:10. 1007/s10661-017-6282-y

Bibliometric Analysis of Global Research Progress on Coastal Flooding 1995-2016

doi: 10.1007/s11769-018-0996-9

Abstract

References

Proportional views

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Proportional views

Related