Phase-sensitive optical time-domain reflection (Φ-OTDR) technique has played a critical role in the field of pipeline intrusion monitoring. Identifying and locating intrusion events is a key topic in this field. While neural network-based solutions have been proposed frequently in recent years, a majority of them neglect the location of the events, resulting in ongoing manual labor in practical engineering applications. Based on the investigation of pipeline intrusion event identification, an automatic event recognition and location method is proposed. The proposed method is based on the concept of target detection , and the spatio-temporal diagram of 1 s time and 4 km spatial distance is used as the input of the target detection network. As such, max-min normalization, bandpass filtering, and data augmentation are employed as preprocessing methods to realize the location and identification of intrusion events at the same time. The experiment demonstrates that the proposed method can achieve an average recall of 82.9% and a precision of 70.4% in three types of events, including surface beating, surface digging, and human jumping, which can basically meet most industrial requirements.