Analisis Bibliometrik Pemanfaatan Data Satelit TRMM dalam Estimasi Curah Hujan
DOI:
https://doi.org/10.53863/kst.v7i01.1589Keywords:
bibliometric, rainfall, satellite, TRMM, VOSviewerAbstract
Climate change has posed significant challenges in water resources management, particularly in relation to the need for accurate and reliable rainfall predictions. Precise rainfall information is essential for various domains, ranging from disaster risk reduction such as floods and droughts, to strategic planning in the agricultural sector and irrigation management. The main focus of this research is on the automatic rainfall estimation method, which is implemented through the utilization of Tropical Rainfall Measuring Mission (TRMM) satellite data. The characteristics of TRMM data, especially its wide spatial and temporal coverage, are considered to have great potential to reduce the constraints arising from the limitations of ground-based observation data.To analyze the development and trends in this topic, we employed a comprehensive bibliometric analysis. This analysis was conducted using VOSviewer software, which facilitates the visualization of collaboration networks and the identification of dominant research themes. The study period covered publications from 2000 to 2020. The bibliometric analysis results revealed substantial fluctuations in the number of publications, with peaks recorded in 2006 and 2010, indicating a significant increase in research interest and activity during these periods. Furthermore, the most cited articles within the study period made fundamental contributions to the understanding and implementation of TRMM data, particularly in the development of models and algorithms for rainfall estimation. It is expected that this research will provide important information and guidance for academics and policymakers in optimizing water resource management strategies amidst the challenges of climate change, and assist in creating more precise and reliable methods for future rainfall prediction
References
Al Husaeni, D. N., & Nandiyanto, A. B. D. (2023). A Bibliometric Analysis of Vocational School Keywords Using VOSviewer. ASEAN Journal of Science and Engineering Education, 3(1), 1–10. https://ejournal.upi.edu/index.php/AJSEE/article/view/43030.
Allan, R. P., & Soden, B. J. (2008). Atmospheric warming and the amplification of precipitation extremes. Science, 321(5895), 1481–1484. https://doi.org/10.1126/science.1160787.
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133(May), 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070.
Elnashar, A., Zeng, H., Wu, B., Zhang, N., Tian, F., Zhang, M., Zhu, W., Yan, N., Chen, Z., Sun, Z., Wu, X., & Li, Y. (2020). Downscaling TRMM monthly precipitation using google earth engine and google cloud computing. Remote Sensing, 12(23), 1–22. https://doi.org/10.3390/rs12233860.
Fang, J. (2019). Evaluation of the TRMM 3B42 and GPM IMERG products for extreme precipitation analysis over China. Atmospheric Research, 223, 24–38. https://doi.org/10.1016/j.atmosres.2019.03.001.
Feloni, E., & Nastos, P. T. (2024). Evaluating Rainwater Harvesting Systems for Water Scarcity Mitigation in Small Greek Islands under Climate Change. Sustainability (Switzerland) , 16(6). https://doi.org/10.3390/su16062592.
Giarno, Hadi, M. P., Suprayogi, S., & Murti, S. H. (2018). Distribution of accuracy of TRMM daily rainfall in Makassar Strait. Forum Geografi. http://journals.ums.ac.id/index.php/fg/article/view/5774.
Giro, R. A., Luini, L., Riva, C. G., Pimienta-Del-Valle, D., & Riera Salis, J. M. (2022). Real-Time Rainfall Estimation Using Satellite Signals: Development and Assessment of a New Procedure. IEEE Transactions on Instrumentation and Measurement, 71. https://doi.org/10.1109/TIM.2022.3165840.
Goodarzi, M. R., Pooladi, R., & Niazkar, M. (2022). Evaluation of Satellite-Based and Reanalysis Precipitation Datasets with Gauge-Observed Data over Haraz-Gharehsoo Basin, Iran. Sustainability (Switzerland), 14(20). https://doi.org/10.3390/su142013051.
Hofifah, S. N., & Nandiyanto, A. B. D. (2024). ASEAN Journal of Science and Engineering Research Trends from The Scopus Database Using Keyword Water Hyacinth and Ecosystem : A Bibliometric Literature Review. 4(1), 33–48.
Huffman, G., Adler, R. ., Bolvin, D. ., Gu, G., Nelkin, E. ., Bowman, K. ., HOng, Y., Stocker, E. ., & Wolff, D. . (2007). The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. Journal of Hydrometeorology, 8(1), 38–55. https://doi.org/10.1175/JHM560.1.
Huffman, G. J., Adler, R. F., Bolvin, D. T., Gu, G., Nelkin, E. J., Bowman, K. P., Hong, Y., Stocker, E. F., & Wolff, D. B. (2007). The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. Journal of Hydrometeorology, 8(1), 38–55. https://doi.org/10.1175/JHM560.1.
Krisnayanti, D. S., Welkis, D. F. B., Fery, M. H., & Legono, D. (2020). Evaluasi Kesesuaian Data Tropical Rainfall Measuring Mission (TRMM) Dengan Data Pos Hujan Pada Das Temef Di Kabupaten Timor Tengah Selatan. Jurnal Sumber Daya Air. https://jurnalsda.pusair-pu.go.id/index.php/JSDA/article/view/646.
Kullahci, K., & Altunkaynak, A. (2024). Maximizing daily rainfall prediction accuracy with maximum overlap discrete wavelet transform-based machine learning models. International Journal of Climatology, 44(10), 3405–3426. https://doi.org/10.1002/joc.8530.
Mamenun, M., Pawitan, H., & Sopaheluwakan, A. (2014). Validasi Dan Koreksi Data Satelit Trmm Pada Tiga Pola Hujan Di Indonesia. Jurnal Meteorologi Dan Geofisika, 15(1), 13–23. https://doi.org/10.31172/jmg.v15i1.169.
Maryanti, R., Nandiyanto, A. B. D., Hufad, A., Sunardi, S., Al Husaeni, D. N., & Al Husaeni, D. F. (2023). a Computational Bibliometric Analysis of Science Education Research Using Vosviewer. Journal of Engineering Science and Technology, 18(1), 301–309.
Mashudi, I., Anwar, M., & Fengky F, A. (2021). Pemanfaatan data satelit tropical rainfall measuring mission (TRMM) untuk pemetaan zona agroklimat neraca air lahan di Kalimantan Tengah. Journal of Environment and Management, 2(1), 11–25. https://doi.org/10.37304/jem.v2i1.2655.
Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., & Dolman, A. J. (2011). Global land-surface evaporation estimated from satellite-based observations. Hydrology and Earth System Sciences, 15(2), 453–469. https://doi.org/10.5194/hess-15-453-2011.
Mukhlisa, N., & Hasan, K. (2024). Analisis Bibliometrik : Konsep , Metodologi , Dan Aplikasinya Dalam Penelitian Ilmiah. 950–961.
Nandiyanto, A. B. D., Fiandini, M., & Al Husaeni, D. N. (2022). Research Trends from The Scopus Database Using Keyword Water Hyacinth and Ecosystem: A Bibliometric Literature Review. ASEAN Journal of Science and Engineering, 4(1), 33–48. https://doi.org/10.17509/ajse.v4i1.60149.
Prospero, J. M., Ginoux, P., Torres, O., Nicholson, S. E., & Gill, T. E. (2002). Environmental characterization of global sources of atmospheric soil dust identified with the Nimbus 7 Total Ozone Mapping Spectrometer (TOMS) absorbing aerosol product. Reviews of Geophysics, 40(1), 2-1-2–31. https://doi.org/10.1029/2000RG000095.
Ramanathan, V., Crutzen, P. J., Lelieveld, J., Mitra, A. P., Althausen, D., Anderson, J., Andreae, M. O., Cantrell, W., Cass, G. R., Chung, C. E., Clarke, A. D., Coakley, J. A., Collins, W. D., Conant, W. C., Dulac, F., Heintzenberg, J., Heymsfield, A. J., Holben, B., Howell, S., … Valero, F. P. J. (2001). Indian Ocean Experiment: An integrated analysis of the climate forcing and effects of the great Indo-Asian haze. Journal of Geophysical Research Atmospheres, 106(D22), 28371–28398. https://doi.org/10.1029/2001JD900133.
Rodell, M., Velicogna, I., & Famiglietti, J. S. (2009). Satellite-based estimates of groundwater depletion in India. Nature, 460(7258), 999–1002. https://doi.org/10.1038/nature08238.
Satria WD, H., & Qothrunada, D. T. (2022). Evaluasi Data Estimasi Curah Hujan Satelit Trmm 3B42 Dengan Data Observasi Di Kolaka Tahun 2019. EduFisika: Jurnal Pendidikan Fisika, 7(2), 214–220. https://doi.org/10.59052/edufisika.v7i2.20374.
Sheffield, J., Goteti, G., & Wood, E. . (2006). Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. Journal of Climate, 19(13), 3088–3111. https://doi.org/10.1175/JCLI3790.1.
Shi, H., Chen, J., Li, T., & Wang, G. (2020). A new method for estimation of spatially distributed rainfall through merging satellite observations, raingauge records, and terrain digital elevation model data. Journal of Hydro-Environment Research, 28(xxxx), 1–14. https://doi.org/10.1016/j.jher.2017.10.006.
Werf, G. R. Van Der, Randerson, J. ., Giglio, L., Collatz, G. ., Mu, M., Kasibhatla, P. S., Morton, D. C., DeFries, R. S., Jin, Y., & van Leeuwen, T. T. (2010). Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997-2009). Atmospheric Chemistry and Physics, 10(23), 11707–11735. https://doi.org/10.5194/acp-10-11707-2010.
Wheeler, M. C., & Hendon, H. H. (2004). An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Monthly Weather Review, 132(8), 1917–1932. https://doi.org/10.1175/1520-0493(2004)132<1917:AARMMI>2.0.CO;2.
Yu, Y., Li, Y., Zhang, Z., Gu, Z., Zhong, H., Zha, Q., Yang, L., Zhu, C., & Chen, E. (2020). A bibliometric analysis using VOSviewer of publications on COVID-19. Annals of Translational Medicine, 8(13), 816–816. https://doi.org/10.21037/atm-20-4235.
Zhang, P., Liu, X., & Pu, K. (2023). Precipitation Monitoring Using Commercial Microwave Links: Current Status, Challenges and Prospectives. Remote Sensing, 15(19). https://doi.org/10.3390/rs15194821.
Zhou, L., Tucker, C. J., Kaufmann, R. K., Slayback, D., Shabanov, N. V., & Myneni, R. B. (2001). Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. Journal of Geophysical Research Atmospheres, 106(D17), 20069–20083. https://doi.org/10.1029/2000JD000115.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Rafika Andari, Nurhamidah Nurhamidah

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License that allows others to share the work with an acknowledgment of the work’s authorship and initial publication in this journal