Analisis Bibliometrik Pemanfaatan Data Satelit TRMM dalam Estimasi Curah Hujan

Rafika Andari; Nurhamidah Nurhamidah

doi:10.53863/kst.v7i01.1589

Penulis

Rafika Andari Institut Teknologi Padang, Padang, Indonesia
Nurhamidah Nurhamidah Universitas Andalas, Padang, Indonesia

DOI:

https://doi.org/10.53863/kst.v7i01.1589

Kata Kunci:

bibliometric, curah hujan, satelit, TRMM, VOSviewer

Abstrak

Perubahan iklim telah menimbulkan tantangan signifikan dalam pengelolaan sumber daya air, khususnya terkait dengan kebutuhan akan prediksi curah hujan yang akurat dan andal. Informasi curah hujan yang presisi sangat penting untuk berbagai domain, mulai dari pengurangan risiko bencana seperti banjir dan kekeringan, hingga perencanaan strategis dalam sektor pertanian dan manajemen irigasi. Fokus utama penelitian ini adalah pada metode estimasi curah hujan secara otomatis, yang diimplementasikan melalui pemanfaatan data satelit Tropical Rainfall Measuring Mission (TRMM). Karakteristik data TRMM, khususnya cakupan spasial dan temporalnya yang luas, dinilai memiliki potensi besar untuk mereduksi kendala yang timbul dari keterbatasan data observasi berbasis darat. Untuk menganalisis perkembangan dan tren penelitian dalam topik ini, kami menerapkan analisis bibliometrik komprehensif. Analisis ini dilakukan menggunakan perangkat lunak VOSviewer, yang memungkinkan visualisasi jaringan kolaborasi dan identifikasi topik-topik dominan. Periode studi mencakup publikasi dari tahun 2000 hingga 2020. Hasil analisis bibliometrik mengungkapkan fluktuasi substansial dalam jumlah publikasi, dengan puncaknya yang tercatat pada tahun 2006 dan 2010, menunjukkan peningkatan minat dan aktivitas penelitian yang signifikan pada periode tersebut. Lebih lanjut, artikel-artikel dengan sitasi terbanyak dalam periode studi memberikan kontribusi fundamental terhadap pemahaman dan implementasi data TRMM, khususnya dalam pengembangan model dan algoritma untuk estimasi curah hujan. Diharapkan penelitian ini dapat memberikan informasi penting dan arah bagi para akademisi dan pembuat keputusan dalam mengoptimalkan strategi pengelolaan sumber daya air di tengah tantangan perubahan iklim, serta membantu dalam menciptakan metode yang lebih tepat dan andal untuk memperkirakan curah hujan di masa depan

Referensi

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.