Visualization of Prediction Methods for Wildfire Modeling Using CiteSpace: A Bibliometric Analysis
Wildfire is a growing concern worldwide with significant impacts on human lives and the environment. This study aimed to provide an overview of the current trends and research gaps in wildfire prediction by conducting a bibliometric analysis of papers in the Web of Science and Scopus databases. Cite...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Atmosphere |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4433/14/6/1009 |
| _version_ | 1797596187978629120 |
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| author | Mengya Pan Shuo Zhang |
| author_facet | Mengya Pan Shuo Zhang |
| author_sort | Mengya Pan |
| collection | DOAJ |
| description | Wildfire is a growing concern worldwide with significant impacts on human lives and the environment. This study aimed to provide an overview of the current trends and research gaps in wildfire prediction by conducting a bibliometric analysis of papers in the Web of Science and Scopus databases. CiteSpace was employed to analyze the co-occurrence of keywords, identify clusters, and detect emerging trends. The results showed that the most frequently occurring keywords were “wildfire”, “prediction”, and “model” and the top three clusters were related to “air quality”, “history”, and “validation”. The analysis of emerging trends revealed a focus on vegetation, precipitation, land use, trends, and the random forest algorithm. The study contributes to a better understanding of the research trends and gaps in wildfire prediction and provides recommendations for future research, such as incorporating new data sources and using advanced techniques. |
| first_indexed | 2024-03-11T02:47:04Z |
| format | Article |
| id | doaj.art-bb41ab8f922c44d1b38e8807fdda0725 |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-11T02:47:04Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-bb41ab8f922c44d1b38e8807fdda07252023-11-18T09:14:57ZengMDPI AGAtmosphere2073-44332023-06-01146100910.3390/atmos14061009Visualization of Prediction Methods for Wildfire Modeling Using CiteSpace: A Bibliometric AnalysisMengya Pan0Shuo Zhang1School of Information Management, Nanjing University, Nanjing 210023, ChinaSchool of Information Management, Nanjing University, Nanjing 210023, ChinaWildfire is a growing concern worldwide with significant impacts on human lives and the environment. This study aimed to provide an overview of the current trends and research gaps in wildfire prediction by conducting a bibliometric analysis of papers in the Web of Science and Scopus databases. CiteSpace was employed to analyze the co-occurrence of keywords, identify clusters, and detect emerging trends. The results showed that the most frequently occurring keywords were “wildfire”, “prediction”, and “model” and the top three clusters were related to “air quality”, “history”, and “validation”. The analysis of emerging trends revealed a focus on vegetation, precipitation, land use, trends, and the random forest algorithm. The study contributes to a better understanding of the research trends and gaps in wildfire prediction and provides recommendations for future research, such as incorporating new data sources and using advanced techniques.https://www.mdpi.com/2073-4433/14/6/1009wildfire predictionWeb of ScienceScopusCiteSpaceresearch trends |
| spellingShingle | Mengya Pan Shuo Zhang Visualization of Prediction Methods for Wildfire Modeling Using CiteSpace: A Bibliometric Analysis Atmosphere wildfire prediction Web of Science Scopus CiteSpace research trends |
| title | Visualization of Prediction Methods for Wildfire Modeling Using CiteSpace: A Bibliometric Analysis |
| title_full | Visualization of Prediction Methods for Wildfire Modeling Using CiteSpace: A Bibliometric Analysis |
| title_fullStr | Visualization of Prediction Methods for Wildfire Modeling Using CiteSpace: A Bibliometric Analysis |
| title_full_unstemmed | Visualization of Prediction Methods for Wildfire Modeling Using CiteSpace: A Bibliometric Analysis |
| title_short | Visualization of Prediction Methods for Wildfire Modeling Using CiteSpace: A Bibliometric Analysis |
| title_sort | visualization of prediction methods for wildfire modeling using citespace a bibliometric analysis |
| topic | wildfire prediction Web of Science Scopus CiteSpace research trends |
| url | https://www.mdpi.com/2073-4433/14/6/1009 |
| work_keys_str_mv | AT mengyapan visualizationofpredictionmethodsforwildfiremodelingusingcitespaceabibliometricanalysis AT shuozhang visualizationofpredictionmethodsforwildfiremodelingusingcitespaceabibliometricanalysis |