The mineral resources such as lithium and boron in the saline lakes of Qinghai Tibet Plateau are of great economic value. The content and spatial distribution of lithium, boron and other mineral resources are the focus of salt lake observation, which has important significance for the development and utilization of saline lake resources. Using remote sensing technology to carry out saline lake observation can overcome the shortcomings of traditional observation station, such as discontinuous data, time and labor intensive, whilemachine learning algorithms can quickly and efficiently mine remote sensing data information. Therefore, based on landsat- 8 remote sensing image data, this paper uses LightGBM algorithm to carry out remote sensing inversion of lithium concentration in north lake of Zabuye salt lake in Tibet. After a series of experimental steps, such as the acquisition of spectral data of sampling points, the construction of LightGBM regression model of lithium concentration, and the inversion of lithium concentration in salt lake, the final model evaluation results show that the average relative error is 0. 053530925, the root mean square error is 10. 2869, and the chi square is 0. 867. The model has a high degree of fitting with the measured data. The inversion results show that: in the whole of north lake the highest lithium concentration is in the southeast waters, and the lowest is in the midwest waters; the confluence of rivers and the Qiulinanmu spring group lowers the lithium concentration in the nearby waters; for travertine island, which is located in the low lithium concentration area in the middle, the confluence of springs in the island makes the lithium concentration in the nearby waters higher, which is consistent with the actual situation. Through the inversion research in this paper, the feasibility and accuracy of LightGBM machine learning algorithm for fast inversion of saline lake lithium concentration are proved. At the same time, it provides technical explanation for remote sensing inversion of other salt lake mineral resources, and lays the foundation for subsequent salt lake resource assessment.