In order to obtain macroscopic and quantitative porosity data in outcrop rapidly, a new Hyperspectrum based porosity estimation method was proposed in this paper. Sandstone samples were collected from field outcrop and measured for porosity data, whose influence factors were analyzed with rock thin section. After the preprocessing on the spectral data of rock samples, the spectral response mechanism of porosity was preliminarily explored. Considering the high dimensionality of spectral bands and the multiple correlation between bands, the porosity estimation models were constructed using the partial least squares method. The important bands in the model were indicated by the variable importance in the projection. The results show that: sandstone porosity can be indirectly retrieved based on the correlation between interstitial fillings and porosity and the spectral characteristics of interstitial fillings; sandstone porosity shows good spectral response; reflectance has the ability to estimate porosity quantitatively (porosity estimation model based on full wavelengths: R2=0.72, RMSE=2.28, RPD=194); the important bands help to reduce the independent variable dimension and find the porosity-sensitive spectral response. This study lays the foundation for porosity characterization in the outcrop based on hyperspectral images.