The high precision monitoring of the organic matter content of space-based black soil is of great significance to the utilization and conservation of black soil resources. Soil organic matter content prediction based on space-based hyperspectral data is an effective means to achieve high spatial and temporal soil coverage monitoring in large regions. The core parameters such as spectral resolution and signal-to-noise ratio of satellite-based hyperspectral instruments have a significant impact on the accuracy of soil organic matter content prediction. This paper aims to improve the level of soil organic matter monitoring in the black soil region of China. In this paper， to improve the level of soil organic matter monitoring in the black soil region of China， we conducted a study on the influence of spectral resolution and signal-to-noise ratio of satellite optical payload on soil organic matter content inversion， and constructed a hyperspectral satellite "instrument-observation-inversion" model for black soil monitoring based on MODTRAN atmospheric transmission model， instrument signal-to-noise ratio analysis model and partial least squares regression soil organic matter inversion model. And using the actual soil measurement data of Sanjiang Plain， a typical black soil area in northeast China， as model input， the soil spectral data measured in the laboratory in the black soil area is simulated into simulated data incorporating atmospheric effects and the characteristics of real space-based remote sensing instruments， and the inversion results are compared and analyzed for changing the spectral resolution and signal-to-noise ratio parameters， and the results show that： （1） The inversion performance of space-based remote sensing load spectral resolution parameter for black soil organic matter content prediction is better in the interval less than 40 nm， with RMSE<0.60% and R²>0.75； （2） When the spectral resolution is 15nm and the weighted signal-to-noise ratio is greater than or equal to 477.31， the inversion performance of black soil organic matter is optimal， with RMSE<0.535%；（3） The smaller the spectral resolution， the more significant the effect of noise， and the smaller the spectral interval， the higher the signal-to-noise ratio requirement. the best weighted signal-to-noise ratios at 10 nm and 20 nm resolution correspond to 494.07 and 462.16， and the minimum weighted signal-to-noise ratio requirements at 60 nm and 100 nm are 358.84 and 275.63， respectively.