Surface crevasses across the Greenland Ice Sheet remain a major source of uncertainty in understanding mass loss processes, including calving, ice flow, and meltwater routing. Most previous studies have primarily focused on the two-dimensional characteristics of surface crevasses on the Greenland Ice Sheet, measurement of crevasse depth, especially from catchment to ice-sheet scale, is limited, thereby limiting our ability to quantify their impact on ice-sheet stability and surface hydrology. The ICESat-2 ATL03 data (0.7 m resolution) provide an unprecedented opportunity to measure crevasse depths, yet large-scale applications are hindered by challenges such as massive data volume and noises. Here, we develop an automated and efficient ICESat-2 method for crevasse depth estimation that rapidly identifies crevassed regions using a novel roughness index, retrieves signal photons via a similarity-based weighted density approach, and extracts crevasses for depth estimation using a local extrema method. A total of 18,775 crevasse locations were detected from 2,286 beams on Sermeq Kujalleq in 2019. The average crevasse depth is 7.20 ± 0.03 m, with depth maxima occurring at approximately 20 km and 10 km inland in the south and north ice streams, respectively. Crevasses in the northern ice stream are mainly distributed below 600 m a.s.l, whereas those in the southern ice stream predominantly occur below 900 m a.s.l. Compared to IceBridge ATM data, the RMSE of crevasse depths estimated from the ATL03 product is 0.97 m, 5.30 m lower than that from ATL06. In addition, ATL03-derived depths are approximately 28% and 30% deeper than those from ATL06 and ArcticDEM. This study enables metre-scale crevasses to be incorporated into large-scale analyses of ice dynamics and calving, and highlights the potential of ICESat-2 for large-scale crevasse depth estimation, providing valuable insights for global crevasse mapping.