Abstract: Timely and accurate identification of ecological damage caused by abrupt events is important for ecological security and emergency response. Existing remote sensing detection methods are mostly designed for individual abrupt event types and often involve lengthy processing chains that compromise detection timeliness, making it difficult to meet the demand for unified and timely detection of ecological damage caused by multiple types of abrupt events. Therefore, this study proposed a unified immediate remote sensing detection method for ecological damage caused by abrupt events based on an ecological baseline, characterizing ecological damage as an anomalous disruption of the current ecosystem state relative to a stable ecological baseline. First, the conceptual scope of ecological damage was clarified from the perspective of remote sensing detection, and an immediate remote sensing detection framework for ecological damage caused by multiple types of abrupt events was constructed. Then, a candidate feature set was constructed around anomalies in ecosystem structure and surface state, and sensitive feature combinations were selected. Finally, immediate detection of areas affected by ecological damage was achieved by measuring the anomalous deviation of target-image features from ecological baseline features in a multidimensional feature space. The method was validated using Sentinel-2 imagery for five typical abrupt-event cases, including grassland fire, flood, landslide, debris flow, and freeze-thaw slump. The results showed that the method achieved good detection performance across different abrupt-event cases, and the three-dimensional feature combination yielded an F1-score of 0.935. The algorithm has potential for onboard deployment and can provide methodological support for rapid identification, emergency response, and unified detection of ecological damage caused by multiple types of abrupt events.