<![CDATA[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]]>
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