Skip to content

Latest commit

 

History

History
62 lines (43 loc) · 28.5 KB

README.md

File metadata and controls

62 lines (43 loc) · 28.5 KB

Awesome Scientific Figure

PRs Welcome star fork

A curated list of scientific figures in research papers.

Contributing

Pull requests are welcome, please feel free to raise pull requests to add new recommendation.

Geographic map

Figure Citation (APA) Link Tag Color
Fig. 11 Xu, Y., Li, J., Belyi, A., & Park, S. (2021). Characterizing destination networks through mobility traces of international tourists—A case study using a nationwide mobile positioning dataset. Tourism Management, 82, 104195. [paper] flow #2A4291#2A4291
#F8CA13#F8CA13
#C00005#C00005
#64C9EA#64C9EA
#58AF63#58AF63
#E98A02#E98A02
#DE24CE#DE24CE
Fig. 10 Xu, Y., Li, J., Xue, J., Park, S., & Li, Q. (2021). Tourism geography through the lens of time use: A computational framework using fine-grained mobile phone data. Annals of the American Association of Geographers, 111(5), 1420-1444. [paper] notation #FDEDBD#FDEDBD
#FCDA9B#FCDA9B
#FDBD39#FDBD39
#E83D39#E83D39
#F7F7EF#F7F7EF
Fig. 1 Jiang, S., Yang, Y., Gupta, S., Veneziano, D., Athavale, S., & González, M. C. (2016). The TimeGeo modeling framework for urban mobility without travel surveys. Proceedings of the National Academy of Sciences, 113(37), E5370-E5378. [paper] prob #EFE541#EFE541
#296AB2#296AB2
#E40519#E40519
#75B728#75B728
Fig. 2 Xu, Y., Chen, D., Zhang, X., Tu, W., Chen, Y., Shen, Y., & Ratti, C. (2019). Unravel the landscape and pulses of cycling activities from a dockless bike-sharing system. Computers, Environment and Urban Systems, 75, 184-203. [paper] 3D #0098BD#0098BD
#4BE3CE#4BE3CE
#FEEDB0#EFE541
#FEAC54#FEAC54
#D1374F#EFE541

Combination Fig

Figure Citation (APA) Link Tag Color
Fig. 1 Gibbs, H., Liu, Y., Pearson, C. A., Jarvis, C. I., Grundy, C., Quilty, B. J., ... & Eggo, R. M. (2020). Changing travel patterns in China during the early stages of the COVID-19 pandemic. Nature Communications, 11(1), 1-9. [paper] cluster #1E78B5#1E78B5
#A6CEE3#A6CEE3
#B4DF8A#B4DF8A
#32A02D#32A02D
Fig. 3 Yabe, T., Jones, N. K., Rao, P. S. C., Gonzalez, M. C., & Ukkusuri, S. V. (2022). Mobile phone location data for disasters: A review from natural hazards and epidemics. Computers, Environment and Urban Systems, 94, 101777. [paper] cross #FE0505#FE0505
#0B0CFE#0B0CFE
#FF9D03#FF9D03
#007701#007701
#03FFFE#03FFFE
Fig. 1
Fig. 4
Tegally, H., San, J. E., Cotten, M., Tegomoh, B., Mboowa, G., Martin, D. P., ... & Omunakwe, H. E. (2022). The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance. Science, 378(6615), eabq5358. [paper] period #FDAE61#FDAE61
#FFFFBF#FFFFBF
#ACDDA5#ACDDA5
#2E84BC#2E84BC
#EE6AA6#EE6AA6
#BEBEBE#BEBEBE

#189E78#189E78
#DA5F00#DA5F00
#7570B3#7570B3
#E7288A#E7288A
#66A51E#66A51E
#E5AA05#E5AA05
#A6751D#A6751D
#666666#666666
Fig. 1 Yin, Y., Wang, Y., Evans, J. A., & Wang, D. (2019). Quantifying the dynamics of failure across science, startups and security. Nature, 575(7781), 190-194. [paper] font #EA9493#EA9493
#95CF95#95CF95

#3081AF#3081AF
#F18125#F18125
Fig. 1 Alessandretti, L., Aslak, U., & Lehmann, S. (2020). The scales of human mobility. Nature, 587(7834), 402-407. [paper] echo #2177B5#2177B5
#FF800E#FF800E
#2BA02B#2BA02B
#D72927#D72927
Fig. 1 Ren, M., Park, S., Xu, Y., Huang, X., Zou, L., Wong, M. S., & Koh, S. Y. (2022). Impact of the COVID-19 pandemic on travel behavior: A case study of domestic inbound travelers in Jeju, Korea. Tourism Management, 92, 104533. [paper] event

Scatter

Figure Citation (APA) Link Tag Color
Fig. 1 Song, C., Koren, T., Wang, P., & Barabási, A. L. (2010). Modelling the scaling properties of human mobility. Nature Physics, 6(10), 818-823. [paper] fit
Fig. 4 Wang, P., González, M. C., Hidalgo, C. A., & Barabási, A. L. (2009). Understanding the spreading patterns of mobile phone viruses. Science, 324(5930), 1071-1076. [paper] fit #375294#375294
#D93431#D93431
#1F7E46#1F7E46

Boxplot

Figure Citation (APA) Link Tag Color
Fig. 5 Xu, Y., Zou, D., Park, S., Li, Q., Zhou, S., & Li, X. (2022). Understanding the movement predictability of international travelers using a nationwide mobile phone dataset collected in South Korea. Computers, Environment and Urban Systems, 92, 101753. [paper] comparison #E95C49#E95C49
#5AC0D7#5AC0D7
Fig. 2 Jin, L., Tang, R., Wu, S., Guo, X., Huang, H., Hou, L., ... & Zhu, F. (2022). Antibody persistence and safety after heterologous boosting with orally aerosolised Ad5-nCoV in individuals primed with two-dose CoronaVac previously: twelve-month analyses of a randomized controlled trial. Emerging Microbes & Infections, (just-accepted), 1-20. [paper] comparison confidence #FEE0BE#FEE0BE
#A8DCA5#A8DCA5
#FFE1E0#FFE1E0

Other publications

Figure Citation Link Tag
Map showing carbon dioxide emissions by ships in 2015 > Raval, A., Spero, J., & Campbell, C. (2019). Pollution: the race to clean up the shipping industry. Financial Times, 9-10. [article in newspaper] flow

Classical

|Figure Citation Link Tag Color
Fig. 11 Fang, Z., Shaw, S. L., Tu, W., Li, Q., & Li, Y. (2012). Spatiotemporal analysis of critical transportation links based on time geographic concepts: a case study of critical bridges in Wuhan, China. Journal of Transport Geography, 23, 44-59. [paper] flow
Fig. 9 Alexander, L., Jiang, S., Murga, M., & González, M. C. (2015). Origin–destination trips by purpose and time of day inferred from mobile phone data. Transportation Research Part C: Emerging Technologies, 58, 240-250. [paper] flow
Fig. 5 Xu, Y., & González, M. C. (2017). Collective benefits in traffic during mega events via the use of information technologies. Journal of The Royal Society Interface, 14(129), 20161041. [paper] flow #359C7D#359C7D
#D15F2E#D15F2E
#6E72A6#6E72A6