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The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) employs a unique multi-beam photon counting approach to acquire a near-continuously sampled profile and provides more precise technology for mapping the leaf area index (LAI) at the global scale. The inversion accuracy of LAI is affected by the clumping effect, which has been an open question for spaceborne laser scanning. Here, we present a segmented method based on the path length distribution model to calculate the clumping-corrected LAI independently using ICESat-2 data. The results showed that the LAI derived by the proposed method with a 200 m segment was consistent with the airborne laser scanningderived LAI, with an RMSE of 0.37. A satisfactory agreement (RMSE = 1.03) was also shown between MODIS LAI and ICESat-2 LAI. Moreover, the LAI derived by the proposed method was on average 31.72 % higher than the LAIe derived by Beer's law, which indicated that the proposed method achieved the purpose of correcting the clumping effect. The gap probability calculated by the 200 m moving window and path length distribution obtained by the 1 m moving window as the model input had the highest accuracy. In addition, the limitation of the point cloud data and the time lag of ICESat-2 acquisitions and ALS observations may affect the inversion accuracy of LAI. This study proposed a feasible way to correct the clumping effect and invert LAI independently using ICESat-2 data, which has the potential to characterize vegetation structure precisely at regional and global scales.
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