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Background: The ecological vulnerability assessment (EVA) is employed as a tool for integrated evaluation of the ecosystem with the help of indicators belonging to natural, social, and economy systems. The unavailability of suitable datasets has repeatedly been reported as an obstacle to conducting EVA on large spatial and temporal scales. The progress in remote sensing (RS) technology has aided the development of ecological vulnerability indicators (EVIs) from RS datasets. Scope and approach: This manuscript presents a comprehensive review of 80 peer-reviewed publications which uses RS for EVA. In this regard, the paper is divided into five main sections: First, the background and rationale of conducting this review is presented in the introduction. Second, the methodology for selection and interpretation of selected literature is discussed. Then, the results section presents findings from various dimensions: general trend of literature, spatial or temporal scale of EVA, analysis of targets systems, RS and Non-RS derived EVIs, sensors used for acquisition of RS data, conceptual models, weights determining mechanisms, and software. Next, multiple gaps in the body of knowledge are identified and general recommendations are formulated for future researchers. Finally, the link of EVA with sustainable development is highlighted in the conclusion section. Key findings: The overall trend shows that both the quantity and quality of research regarding EVA has increased over the past decades. It is observed that large number of studies report EVA on both temporal and spatial scale. Further, the results reveal 52 EVIs are derived from RS data and 101 EVIs are derived from non-RS data. The Landsat datasets are found most repeatedly used in EVA research. The remote sensing ecological index (RSEI) and principal component analysis (PCA) are prominent conceptual models and weighting mechanisms. Finally, ArcGIS software is most widely reported software in the EVA literature.