<![CDATA[Remote sensing has become a key technology for assessing environmental damage following disasters due to its ability to provide timely, spatially explicit information. Despite its growing application, existing studies remain fragmented across disciplines and lack a structured understanding of research development. This study aims to systematically map the scientific landscape of remote sensing applications in post disaster environmental damage assessment using a bibliometric approach. A total of 200 publications indexed in scopus from 2015 to 2024 were analysed, comprising 48.195 citations and h-index of 142. Bibliometric analysis was conducted using VOSviewer to examinekeyword co-occurrence and to generate network, overlay, and density visualizations. The result identify four major research cluster : damage detection and assessment, environmental impact analysis, remote sensing applications, and disaster management. Network analysis indicates that remote sensing and damage assessment function as central nodes linkinginterdisciplinary research themes. Overlay visualization reveals a clear transition from conventional monitoring approaches toward data driven methods, particularly machine learning, predictive modeling, and GIS based analysis. Density analysis shows that research remains concentrated on monitoring and environmental assessment, while emerging topics such as artificial intelligence and UAV based sending remain underexplored. This study provides a structured and quantitative synthesis of research development and highlights the increasing role of remote sensing as a data driven decision support system. The findings offer new insights into research trends and identify under explored areas for future investigation.]]>
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