Global research trends in landslides during 1991–2014: a bibliometric analysis
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A bibliometric analysis was conducted to evaluate landslide research from different perspectives during the period 1991–2014 based on the Science Citation Index-Expanded and Social Sciences Citation Index databases. Based on a sample of 10,567 articles that were related to landslides, the bibliometric analysis revealed the scientific outputs, science categories, source titles, global geographical distribution of the authors, productive authors, international collaborations, institutions, and temporal evolution of keyword frequencies. Landslide-related research has undergone notable growth during the past two decades. Multidisciplinary Geosciences, Geological Engineering, and Water Resources were the three major science categories, and Geomorphology was the most active journal during the surveyed period. The major author clusters and research regions are located in North America, Western Europe, and East Asia. The USA was a leading contributor to global landslide research, with the most independent and collaborative articles, and its dominance was also confirmed in the national/regional collaboration network. The Chinese Academy of Sciences, US Geological Survey, and Italian National Research Council were the three major contributing institutions. Guzzetti F from the Italian National Research Council was the most productive author, with the most high-quality articles. A keyword analysis found that landslide susceptibility assessment, rainfall- and earthquake-induced landslide stability, and effective research technologies and methods were consistent topics that attracted the most attention during the study period. Several keywords, such as “landslide susceptibility”, “earthquake”, “GIS”, “remote sensing”, and “logistic regression”, received dramatically increased attention during the study period, possibly signalling future research trends.
KeywordsLandslides Bibliometrics Research trends Collaboration network Author keywords
This study is jointly supported by the NSFC (41271455), the Open Fund of the Key Laboratory of Urban Land Resources Monitoring and Simulation, the Ministry of Land and Resources (KF-2015-01-006), and the Open Research Fund of the State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing (13S01), the State Key Laboratory of Resources and Environmental Information System, and the Changjiang Soil and Water Conservation Monitoring Centre, WRC, China.
- Althuwaynee OF, Pradhan B, Park HJ, Lee JH (2014) A novel ensemble decision tree-based chi-squared automatic interaction detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping. Landslides 11(6):1063–1078. doi: 10.1007/s10346-014-0466-0 CrossRefGoogle Scholar
- Antolini F, Barla M (2015) Combining finite-discrete numerical modelling and radar interferometry for rock landslide early warning systems. In: Lollino G, Giordan D, Thuro K, Carranza-Torres C, Wu F, Marinos P, Delgado C (eds) Engineering geology for society and territory 6. Springer International Publishing, Switzerland, pp 705–708Google Scholar
- Bois T, Tric E, Lebourg T (2014) Influence of inherited topography on gravitational slope failure: three-dimensional numerical modelling of the La Clapière slope, Alpes—Maritimes, France. Terra Nov. 26(5):354–362. doi: 10.1111/ter.12105
- Corominas J, van Westen C, Frattini P, Cascini L, Malet JP, Fotopoulou S, Catani F, Van Den Eeckhaut M, Mavrouli O, Agliardi F, Pitilakis K, Winter MG, Pastor M, Ferlisi S, Tofani V, Hervás J, Smith JT (2014) Recommendations for the quantitative analysis of landslide risk. Bull Eng Geol Environ 73(2):209–263. doi: 10.1007/s10064-013-0538-8 Google Scholar
- Cruden DM, Varnes DJ (1996) Landslide types and processes. In: Turner AK, Schuster RL (eds) Landslides, investigation and mitigation, special report 247. Transportation Research Board, Washington, DC, pp 36–75Google Scholar
- Notti D, Meisina C, Zucca F, Balduzzi G, Colombo A (2015) Map numerical modelling of landslides using data from different monitoring systems: the example of Rosone (Western Alps). In: Lollino G, Giordan D, Crosta GB, Corominas J, Azzam R, Wasowski J, Sciarra N (eds) Engineering geology for society and territory 2. Springer International Publishing, Switzerland, pp 1455–1459Google Scholar
- Palladino MR, Turconi L, Luino F, Brunetti MT, Peruccacci S, Guzzetti F (2015) Influence of geological, morphological and climatic factors in the initiation of shallow landslides in north western Italy. In: Lollino G, Giordan D, Crosta GB, Corominas J, Azzam R, Wasowski J, Sciarra N (eds) Engineering geology for society and territory 2. Springer International Publishing, Switzerland, pp 1389–1392Google Scholar
- Pritchard A (1969) Statistical bibliography or bibliometrics? J Doc 25(4):348–349Google Scholar
- Varnes DJ (1984) Landslide hazard zonation: a review of principles and practice. In: Natural hazards 3. United Nations Educational, Scientific and Cultural Organization, Paris 63Google Scholar
- Zakaria Z, Hirnawan F, Widayati S (2015) Rain and earthquake-induced landslides in west Java, Indonesia, case study in Subang area near the Baribis Fault, with implications for an early warning system. In: Lollino G, Giordan D, Crosta GB, Corominas J, Azzam R, Wasowski J, Sciarra N (eds) Engineering geology for society and territory 2. Springer International Publishing, Switzerland, pp 637–640Google Scholar