Existing methods for detecting aircraft contrails primarily relied on the radiance or temperature differences between specific channels in multispectral images. However, they did not fully exploit the potential of spectral features. The advancement of satellite-borne hyperspectral imaging technology has provided a new data foundation for aircraft contrail detection. This study explored a detection algorithm for potential aircraft contrails using shortwave infrared hyperspectral images from the GF-5 AHSI. A spatial-spectral feature extraction method was proposed, which leveraged the complementary nature of spatial and spectral information in hyperspectral images. The method achieved an accuracy of over 97% and a false alarm rate of less than 2% on GF-5 hyperspectral image data. This work offers valuable insights for future research.