Please wait a minute...
Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

CN 11-5982/P

Postal Subscription Code 80-963

2018 Impact Factor: 1.205

Front. Earth Sci.    2022, Vol. 16 Issue (2) : 340-351    https://doi.org/10.1007/s11707-021-0875-z
RESEARCH ARTICLE
A novel bibliometric and visual analysis of global geoscience research using landscape indices
Xin AI1,2, Mingguo MA1,2, Xuemei WANG2(), Honghai KUANG3()
1. Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China
2. Southwest University Library, Southwest University, Chongqing 400715, China
3. Chongqing Engineering Research Center for Remote Sensing Big Data Application, Southwest University, Chongqing 400715, China
 Download: PDF(15287 KB)   HTML
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

The landscape index is a quantitative index which reflects characteristics of structure composition and spatial pattern in landscape studies, it is, therefore, expected to describe the spatial pattern of scientific research in bibliometric analysis. In this study, a novel attempt to regard scientific research as a kind of ‘landscape’ was made, and landscape indices were improved for bibliometric analysis to measure the spatial pattern of scientific research. For illustrating the feasibility of our method, global geoscience research from 1994 to 2018 was presented as a case. Moreover, spatiotemporal migration of landscape centroids was visualized. The results indicated that global geoscience publications increased steadily and articles were highly concentrated at the country level. The top 10 countries published 69.93% of total articles and 84.68% of geoscience articles were from top 20 productive countries. The spatial migration of centroids was mainly reflected in the longitude because of significant increasing of articles in eastern countries, especially in China with the growth rate of 747.14%. At the patch scale, the change trend of improved landscape indices verified the spatiotemporal changes of global distribution of geoscience articles. At the landscape scale, the strengthening of global international collaboration is the main driving forces of spatial heterogeneity of global geoscience research. This study is expected to help readers to understand global trends of geoscience research in the past 25 years, and to promote the development of bibliometric analysis towards the directions of spatialization and visualization.

Keywords geoscience      landscape index      visualization      Geographical Information System      bibliometric analysis     
Corresponding Author(s): Xuemei WANG,Honghai KUANG   
About author: Tongcan Cui and Yizhe Hou contributed equally to this work.
Online First Date: 02 June 2021    Issue Date: 26 August 2022
 Cite this article:   
Xin AI,Mingguo MA,Xuemei WANG, et al. A novel bibliometric and visual analysis of global geoscience research using landscape indices[J]. Front. Earth Sci., 2022, 16(2): 340-351.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-021-0875-z
https://academic.hep.com.cn/fesci/EN/Y2022/V16/I2/340
Fig.1  Characteristics by year of geoscience publications.
Country TA R/% TC Single country International collaboration??
SA % CA % MC(n)
USA 240234 1(25.63) 8438483 134124 0.56 106110 0.44 China (18682)
China 104285 2(11.13) 1709506 63844 0.61 40441 0.39 USA (18682)
UK 76597 3(8.17) 2529759 27809 0.36 48788 0.64 USA (17093)
Germany 70167 4(7.49) 2091571 22760 0.32 47407 0.68 USA (14435)
France 62696 6(6.69) 1895582 20409 0.33 42287 0.67 USA (12687)
Canada 50773 7(5.42) 1401954 22300 0.44 28473 0.56 USA (12975)
Russia 47835 8(5.10) 468937 33454 0.70 14381 0.30 USA (3737)
Japan 42213 9(4.50) 996393 22439 0.53 19774 0.47 USA (7661)
Australia 39681 10(4.23) 1228738 15088 0.38 24593 0.62 USA (7768)
Italy 39439 11(4.21) 974046 18251 0.46 21188 0.54 USA (5694)
India 26641 12(2.84) 362335 19639 0.74 7002 0.26 USA (2331)
Spain 24875 13(2.65) 581668 9307 0.37 15568 0.63 USA (3721)
Switzerland 21240 14(2.27) 749589 4986 0.23 16254 0.77 USA (5089)
Netherlands 19385 15(2.07) 675857 5642 0.29 13743 0.71 USA (3973)
Norway 15160 16(1.62) 413244 4277 0.28 10883 0.72 USA (3391)
Sweden 14087 17(1.50) 403501 3899 0.28 10188 0.72 USA (3086)
Brazil 12583 18(1.34) 244730 5825 0.46 6758 0.54 USA (2343)
South Korea 10037 20(1.07) 188733 4542 0.45 5495 0.55 USA (2880)
Poland 9808 21(1.05) 118691 5733 0.58 4075 0.42 USA (852)
Austria 9399 22(1.00) 249192 2083 0.22 7316 0.78 Germany (2611)
Tab.1  Top 20 productive countries in geoscience research
Patch type Number of articles in
global geoscience research
I No published articles
II Less than 100
III 101?500
IV 501?1000
V 1001?2500
VI 2501?5000
VII 5001?10000
VIII More than 10000
Tab.2  Classification and definition of the patch types
Fig.2  The number of countries of each patch.
Fig.3  The number of articles of each patch.
Type Year NP PD (×103) LPI/% PLAND/%
I 1994 82 5.72
1998 80 3.73
2002 77 2.92
2006 75 1.98
2010 74 1.49
2014 55 0.78
2018 55 0.66
II 1994 23 1.68 3.01 8.51
1998 21 1.38 1.27 5.24
2002 35 1.23 1.19 5.14
2006 35 1.09 1.21 4.93
2010 36 0.78 1.04 4.52
2014 54 0.74 0.88 3.69
2018 56 0.60 0.69 2.60
III 1994 7 0.45 3.71 16.45
1998 10 0.45 3.24 17.17
2002 11 0.36 3.26 13.84
2006 13 0.34 3.04 15.01
2010 13 0.25 3.48 13.19
2014 14 0.21 1.56 7.33
2018 15 0.17 1.29 7.13
IV 1994 6 0.17 5.34 12.46
1998 5 0.12 4.51 11.21
2002 4 0.13 2.16 7.68
2006 4 0.10 2.48 8.20
2010 4 0.08 2.68 6.78
2014 9 0.15 3.32 12.69
2018 10 0.11 2.53 9.37
V 1994 5 0.22 8.91 29.41
1998 5 0.20 12.82 37.64
2002 6 0.19 16.33 47.72
2006 5 0.13 16.63 41.11
2010 8 0.14 7.45 26.77
2014 7 0.10 5.63 23.06
2018 7 0.08 2.67 13.67
VI 1994 0
1998 0
2002 0
2006 1 0.03 7.47 7.47
2010 3 0.06 12.49 27.87
2014 3 0.04 11.51 21.54
2018 2 0.06 7.99 21.27
VII 1994 1 0.06 33.17 33.17
1998 1 0.04 28.74 28.74
2002 1 0.03 25.62 25.62
2006 1 0.03 23.27 23.27
2010 0
2014 1 0.01 12.72 12.72
2018 2 0.02 6.03 12.02
VIII 1994 0
1998 0
2002 0
2006 0
2010 1 0.02 20.87 20.87
2014 1 0.01 18.96 18.96
2018 2 0.02 17.19 33.93
Tab.3  Patch-scale publication pattern index
Year ARTICLE-MN SHDI SHEI
1994 120.42 1.49 0.92
1998 168.71 1.43 0.89
2002 205.23 1.33 0.82
2006 270.15 1.54 0.86
2010 354.17 1.63 0.91
2014 489.15 1.82 0.94
2018 576.62 1.73 0.92
Tab.4  Landscape-scale publication pattern index
Fig.4  Spatiotemporal changes of the landscape centroids of the geoscience articles during 1994 to 2018.
Fig.5  Relationship between SHDI and number of ICAs.
Fig.6  Relationship between SHEI and number of ICAs.
Landscape index Type Equations R2
SHDI Linear fit y = 1.926×10-5x + 1.3637 0.6582
SHEI Polynomial fit y = 2.11×10-10x2- 2.86×10-6x + 0.8916 0.2406
Tab.5  The correlation between ICAs and SHDI and SHEI
1 P Ahlgren, O Persson, R Tijssen (2013). Geographical distance in bibliometric relations within epistemic communities. Scientometrics, 95(2): 771–784
https://doi.org/10.1007/s11192-012-0819-1
2 R S Allen (2001). Interdisciplinary Research: a literature-based examination of disciplinary intersections using a common tool, geographic information system (GIS). Sci Tech Libr, 21(3–4): 191–209
https://doi.org/10.1300/J122v21n03_12
3 S A Azer (2017). Top-cited articles in problem-based learning: a bibliometric analysis and quality of evidence assenssment. J Dent Educ, 81(4): 458–478
https://doi.org/10.21815/JDE.016.011
4 S A Azer, S Azer (2019). Top-cited articles in medical professionalism: a bibliometric analysis versus altmetric scores. BMJ Open, 9(7): e029433
https://doi.org/10.1136/bmjopen-2019-029433 pmid: 31371297
5 S A Azer, S Azer (2018). What can we learn from top-cited articles in inflammatory bowel disease? A bibliometric analysis and assessment of the level of evidence. BMJ Open, 8(7): e021233
https://doi.org/10.1136/bmjopen-2017-021233 pmid: 30002009
6 M Batty (2003). The geography of scientific citation. Environ Plan, 35(5): 761–765
https://doi.org/10.1068/a3505com
7 A Bonaccorsi, C Daraio (2005). Exploring size and agglomeration effects on public research productivity. Scientometrics, 63(1): 87–120
https://doi.org/10.1007/s11192-005-0205-3
8 L Bornmann, L Waltman (2011). The detection of “hot regions” in the 515 geography of science—a visualization approach by using density maps. J Informetrics, 5(4): 547–553
https://doi.org/10.1016/j.joi.2011.04.006
9 R Carvalho, M Batty (2006). The geography of scientific productivity: scaling in U.S. computer science. J Stat Mech, 2006(10): P10012
https://doi.org/10.1088/1742-5468/2006/10/P10012
10 C Chen, Z Jia, S Wu, X Tong, W Zhou, R Chen, C Zhang (2017). A bibliometric review of Chinese studies on the application of landscape connectivity. Acta Ecol Sin, 37: 3243–3255
11 W Chen, D Xiao, X Li (2002). Classification, application, and creation of landscape indices. Acta Ecol Sin, 13(1): 121–125 (in Chinese)
pmid: 11962310
12 L Egghe (2006). Theory and practice of the g-index. Scientometrics, 69(1): 131–152
https://doi.org/10.1007/s11192-006-0144-7
13 J D Frame, N Francis, P C Mark (1977). The distribution of world science. Soc Stud Sci, 7(4): 400–400
14 K Frenken, S Hardeman, J Hoekman (2009). Spatial scientometrics: towards a cumulative research program. J Informetrics, 3(3): 222–232
https://doi.org/10.1016/j.joi.2009.03.005
15 P Hassan S U, Haddawy (2013). Measuring international knowledge flows and scholarly impact of scientific research. Scientometrics, 94(1): 163–179
https://doi.org/10.1007/s11192-012-0786-6
16 H S He, B E Dezonia, D J Mladenoff (2000). An aggregation index (AI) to quantify spatial patterns of landscapes. Landsc Ecol, 15(7): 591–601
https://doi.org/10.1023/A:1008102521322
17 T Hengl, B Minasny, M Gould (2009). A geostatistical analysis of geostatistics. Scientometrics, 80(2): 491–514
https://doi.org/10.1007/s11192-009-0073-3
18 A M Hersperger, M Bürgi (2009). Going beyond landscape change description: quantifying the importance of driving forces of landscape change in a Central Europe case study. Land Use Policy, 26(3): 640–648
https://doi.org/10.1016/j.landusepol.2008.08.015
19 J E Hirsch (2010). An index to quantify an individual’s scientific research output that takes into account the effect of multiple co-authorship. Scientometrics, 85(3): 741–754
https://doi.org/10.1007/s11192-010-0193-9
20 H B Li, J G Wu (2004). Use and misuse of landscape indices. Landsc Ecol, 19(4): 389–399
https://doi.org/10.1023/B:LAND.0000030441.15628.d6
21 J X Li, Y J Wang, X H Shen, Y C Song (2004a). Landscape pattern analysis along on urban-rural gradient in the Shanghai metropolitan region. Acta Ecol Sin, 24(9): 1973–1980
22 L Li, Y Liu, H Zhu, S Ying, Q Luo, H Luo, X Kuai, H Xia, H Shen (2017). A bibliometric and visual analysis of global geo-ontology research. Comput Geosci, 99: 1–8
https://doi.org/10.1016/j.cageo.2016.10.006
23 X Z Li, R C Bu, Y Chang (2004). The response of landscape metrics against pattern scenarios Acta Ecol Sin, 24(1): 123–134
24 Y Liu, Y H Lu, B J Fu (2011). Implication and limitation of landscape metrics in delineating relationship between landscape pattern and soil erosion. Acta Ecol Sin, 31(1): 267–275
25 F Liu, A Lin, H Wang, Y Peng, S Hong (2016). Global research trends of geographical information system from 1961 to 2010: a bibliometric analysis. Scientometrics, 106(2): 751–768
https://doi.org/10.1007/s11192-015-1789-x
26 X Liu, L Zhang, S Hong (2011a). Global biodiversity research during 1900–2009: a bibliometric analysis. Biodivers Conserv, 20(4): 807–826
https://doi.org/10.1007/s10531-010-9981-z
27 D Manicacci, I Olivieri, V Perrot, A Atlan, P H Gouyon, J M Prosperi, D Couvet (1992). Landscape ecology: population genetics at the metapopulation level. Landsc Ecol, 6(3): 147–159
https://doi.org/10.1007/BF00130027
28 M C Matthiessen, S A Winkel (1999). Scientific centres in Europe: an analysis of research strength and patterns of specialisation based on bibliometric indicators. Urban Stud, 36(3): 453–477
https://doi.org/10.1080/0042098993475
29 R V O’neill, K H Riitters, J D Wickham, K B Jones (1999). Landscape pattern metrics and regional assessment. Ecosyst Health, 5(4): 225–233
https://doi.org/10.1046/j.1526-0992.1999.09942.x
30 D G Pina, L Barać, I Buljan, F Grimaldo, A Marušić (2019). Effects of seniority, gender and geography on the bibliometric output and collaboration networks of European Research Council (ERC) grant recipients. PLoS One, 14(2): e0212286
https://doi.org/10.1371/journal.pone.0212286 pmid: 30763395
31 H E Peng, H R Zhang (2009). Study on factor analysis and selection of common landscape metrics. For Res, 22(4): 470–474
32 J Peng, Y L Wang, Y Zhang, M T Ye, J S Wu (2006). Research on the influence of land use classification on landscape metrics. Acta Geogr Sin, 61(2): 157–168
33 N Schumaker (1996). Using landscape indices to predict habitat connectivity. Ecology, 77(4): 1210–1225
https://doi.org/10.2307/2265590
34 S Shen, P Yue, C Fan (2019). Quantitative assessment of land use dynamic variation using remote sensing data and landscape pattern in the Yangtze River Delta. Sustain Comput Infor, 23: 111–119
https://doi.org/10.1016/j.suscom.2019.07.006
35 I Vorovencii (2015). Quantifying landscape pattern and assessing the land cover changes in Piatra Craiului National Park and Bucegi Natural Park, Romania, using satellite imagery and landscape metrics. Environ Monit Assess, 187(11): 692
https://doi.org/10.1007/s10661-015-4909-4 pmid: 26476552
36 H W Wang, T Tiyip (2009). Remote sensing dynamic monitor and driving force of soil salinization in arid area: a case of delta oasis of Weigan and Kuqa River. Arid Land Geogr, 32(3): 445–453
37 X Wang, X Li, Z Zhang, M Ma (2014). Spatial display of bibliometric indicators using information system. Libr Inform Service, 58(3): 72–77
38 X Wang, Z Zhang, X Li (2015). Tendency analysis of the international studies of qinghai-tibet plateau using MKD and GIS. J China Soc Sci and Tech Inform, 34(9): 930–937
39 Y Wang, S Hong, Y Wang, X Gong, C He, Z Lu, F B Zhan (2019). What is the difference in global research on central Asia before and after the collapse of the USSR: a bibliometric analysis. Scientometrics, 119(2): 909–930
https://doi.org/10.1007/s11192-019-03069-0
40 A Wu (2015). Trends of the geographical distribution of the core journals in china. Journal of Academic Libraries, 33(03): 96–100
41 J Wu (2004). Effects of changing scale on landscape pattern analysis: scaling relations. Landsc Ecol, 19(2): 125–138
https://doi.org/10.1023/B:LAND.0000021711.40074.ae
42 J Wu (2013). Geographical knowledge diffusion and spatial diversity citation rank. Scientometrics, 94(1): 181–201
https://doi.org/10.1007/s11192-012-0715-8
43 J Wu, W Shen, W Sun, P T Tueller (2002). Empirical patterns of the effects of changing scale on landscape metrics. Landsc Ecol, 17(8): 761–782
https://doi.org/10.1023/A:1022995922992
44 M Yang, X Wang (2015). A biliometrics analysis of world libraries’ papers based on GIS. Remote Sensing Technology and Application, 30(4): 819–824
45 W R Yang (2015a). Spatiotemporal change and driving force of urban landscape pattern in Beijing. Acta Ecol Sin, 35(13): 4357–4366
46 D Zhang, H Z Fu, Y S Ho (2017). Characteristics and trends on global environmental monitoring research: a bibliometric analysis based on Science Citation Index Expanded. Environ Sci Pollut Res Int, 24(33): 26079–26091
https://doi.org/10.1007/s11356-017-0147-3 pmid: 28942484
47 Q J Zhang, B J Fu, L D Chen (2003). Several problems about landscape pattern change research. Sci Geogr Sin, 23(3): 264–270
48 X Zhang, R C Estoque, H Xie, Y Murayama, M Ranagalage (2019). Bibliometric analysis of highly cited articles on ecosystem services. PLoS One, 14(2): e0210707
https://doi.org/10.1371/journal.pone.0210707 pmid: 30742632
49 X Zhang, F Zhang, D Wang (2018). Analysis of bibliometrics and visualization on landscape in china and abroad during 2010–2016. J SW China Normal U (Natrual Science Edition), 43(7): 149–156
50 L Zhou P, L Leydesdorff (2006). The Emergence of China as a Leading Nation in Science. Res Policy, 35(1): 84–103
51 Y Zhuang, X Liu, T Nguyen, Q He, S Hong (2013). Global remote sensing research trends during 1991–2010 a bibliometric analysis. Scientometrics, 96(1): 203–219
https://doi.org/10.1007/s11192-012-0918-z
[1] FES-21875-OF-AX_suppl_1 Download
[1] Suvendu ROY,Abhay Sankar SAHU. Effectiveness of basin morphometry, remote sensing, and applied geosciences on groundwater recharge potential mapping: a comparative study within a small watershed[J]. Front. Earth Sci., 2016, 10(2): 274-291.
[2] Liangfeng ZHU,Jianzhong SUN,Changling LI,Bing ZHANG. SolidEarth: a new Digital Earth system for the modeling and visualization of the whole Earth space[J]. Front. Earth Sci., 2014, 8(4): 524-539.
[3] Jing SUN, Xiang LI. A pyramid-based approach to visual exploration of a large volume of vehicle trajectory data[J]. Front Earth Sci, 2012, 6(4): 345-353.
[4] Ali Bagherzadeh, Mohammad Reza Mansouri Daneshvar. Sediment yield assessment by EPM and PSIAC models using GIS data in semi-arid region[J]. Front Earth Sci, 2011, 5(2): 207-216.
[5] Mohammad Reza MANSOURI DANESHVAR, Ali BAGHERZADEH. Landslide hazard zonation assessment using GIS analysis at Golmakan Watershed, northeast of Iran[J]. Front Earth Sci, 2011, 5(1): 70-81.
[6] Ni-Bin CHANG, Der-Quei CHANG, . Long-term risk assessment of possible accidental release of nuclear power plants in complex terrains with respect to synoptic weather patterns[J]. Front. Earth Sci., 2010, 4(2): 205-228.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed