Ocean-Land Interfaces (OLIs) are instantaneous boundaries between fluctuating ocean surfaces and land and provide fundamental information for scientific research on ocean hydrology, ocean-land resource management, and sea level rise. However, detecting OLIs with high accuracy and resolution in automated manners is a challenging task. Airborne oceanic LiDARs (AOLs) are high-resolution, efficient, and flexible measurement systems that can be used for integrated ocean and land measurements. In areas where the ocean meets land, both ocean and land may exist in the laser spot of AOL, resulting in mixed ocean-land waveforms. If these mixed waveforms can be accurately identified, they can be used to detect the precise location of the ocean-land interface.Considering the existence of mixed ocean-land waveforms, a mixed waveform method based on AOL mixed ocean-land waveforms is proposed for ocean-land interface determination in this paper. First, the waveform features of the AOL infrared lasers are extracted, and principal component analysis is performed to reduce redundant features. Second, the waveform features are used to classify the AOL waveforms to obtain a membership matrix, and the Otsu method is used to determine the mixed ocean-land waveforms. Third, the DBSCAN algorithm is used to identify and eliminate misclassified mixed waveforms. Fourth, the PAEK algorithm is applied to smooth the laser points corresponding to the mixed ocean-land waveforms and output the ocean-land interface. Finally, the expression of the infrared laser-radar equation for mixed ocean and land is provided, and a method combining theoretical analysis and measured data verification is used to analyze the differences between ocean, land, and mixed ocean and land waveforms.The correctness and effectiveness of the methods proposed in this paper were verified via raw AOL datasets collected by the Optech CZMIL system. Compared with the traditional AOL elevation threshold method, the proposed AOL mixed waveform method reduced the mean and standard deviation of the ocean-land interface bias by 24.07% and 9.76%, respectively, and improved the SSIM index by 0.031, providing a new approach for detecting the ocean-land interface on tidal flats via AOL.The coexistence of water and land within AOL laser spots generates mixed ocean-land waveforms, and identifying these mixed waveforms has important theoretical and practical value. This study proposes an identification method for infrared laser mixed waveforms based on waveform fuzzy classification and Otsu threshold determination and an ocean-land interface extraction method using those identified mixed waveforms. Furthermore, this study extends the laser-radar equation by proposing an infrared laser-radar equation for infrared laser interactions with mixed ocean and land, providing a theoretical basis for studying mixed infrared laser waveforms. On the basis of this equation, a differential analysis was conducted on the ocean, land, and mixed ocean-land waveforms. The correctness and practicality of the infrared laser-radar equation for mixed ocean and land were verified via visualization analysis results of raw waveform data.