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Mapping the research history, collaborations and trends of remote sensing in fire ecology

Author

Listed:
  • Mariana M. M. Santana

    (Universidade do Estado do Amapá (UEAP))

  • Eduardo Mariano-Neto

    (Universidade Federal da Bahia (UFBA))

  • Rodrigo N. Vasconcelos

    (Universidade Estadual de Feira de Santana (UEFS))

  • Pavel Dodonov

    (Universidade Federal da Bahia (UFBA))

  • José M. M. Medeiros

    (Universidade Federal do Tocantins (UFT))

Abstract

A combination of bibliometric and science mapping methods was carried out to explore characteristics of scientific production on the application of orbital remote sensing in fire ecology. The performance analyzes made it possible to identify the main actors responsible for the knowledge (authors, institutions and countries) and the journals selected for dissemination. Through co-occurrence and co-authorship networks we analyze the temporal evolution of knowledge, analyzing the emergence of themes and research methods, in addition to the pattern of interaction between the main actors involved. The research universe consisted of articles published in indexed journals at Scopus. Of the 2602 initial articles identified, 1977 articles were selected and a subsample of 1832 was selected for the period 2000–2019. As a result, we found that the production of articles started in 1973 and increased over time, with great expansion from 2000s, when different themes, tools and techniques were identified. Corroborating these results, we observed keywords networks more complex and richer in themes, tools and techniques in the period 2000–2019. On the topics surveyed, in the most recent period, there was a greater frequency of subjects such as risk, regime, history and severity. These topics are generally investigated based on data on active fire and global burnt area, which is why the articles most cited in the literature mostly dealt with techniques for obtaining these estimates. Regarding those responsible for research, we demonstrate that although scientific knowledge is concentrated in a few geographical centers and institutions, there are high scientific partnerships and cooperation.

Suggested Citation

  • Mariana M. M. Santana & Eduardo Mariano-Neto & Rodrigo N. Vasconcelos & Pavel Dodonov & José M. M. Medeiros, 2021. "Mapping the research history, collaborations and trends of remote sensing in fire ecology," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1359-1388, February.
    • Handle: RePEc:spr:scient:v:126:y:2021:i:2:d:10.1007_s11192-020-03805-x
    DOI: 10.1007/s11192-020-03805-x
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    References listed on IDEAS

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    1. Jesus San-Miguel-Ayanz & Nicolas Ravail, 2005. "Active Fire Detection for Fire Emergency Management: Potential and Limitations for the Operational Use of Remote Sensing," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 35(3), pages 361-376, July.
    2. Fenglian Liu & Aiwen Lin & Huanhuan Wang & Yuling Peng & Song Hong, 2016. "Global research trends of geographical information system from 1961 to 2010: a bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 751-768, February.
    3. Brigitte Leblon & Laura Bourgeau-Chavez & Jesus San-Miguel-Ayanz, 2012. "Use of Remote Sensing in Wildfire Management," Chapters, in: Sime Curkovic (ed.), Sustainable Development - Authoritative and Leading Edge Content for Environmental Management, IntechOpen.
    4. Perianes-Rodriguez, Antonio & Waltman, Ludo & van Eck, Nees Jan, 2016. "Constructing bibliometric networks: A comparison between full and fractional counting," Journal of Informetrics, Elsevier, vol. 10(4), pages 1178-1195.
    5. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
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    Cited by:

    1. Rodrigo N. Vasconcelos & Washington J. S. Franca Rocha & Diego P. Costa & Soltan G. Duverger & Mariana M. M. de Santana & Elaine C. B. Cambui & Jefferson Ferreira-Ferreira & Mariana Oliveira & Leonard, 2024. "Fire Detection with Deep Learning: A Comprehensive Review," Land, MDPI, vol. 13(10), pages 1-20, October.
    2. Javier Martínez-Vega & David Rodríguez-Rodríguez, 2022. "Protected Area Effectiveness in the Scientific Literature: A Decade-Long Bibliometric Analysis," Land, MDPI, vol. 11(6), pages 1-14, June.

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