The polarized reflectance estimation of land surfaces is one of the most important uncertainties in the polarized remote sensing detection of atmospheric aerosol by satellites and thus becomes an important link in the land-atmosphere decoupling during aerosol inversion. The directional polarized measurements of atmospheric aerosol in the near-infrared band (865 nm) by a directional polarimetric camera (DPC) aboard the GaoFen (GF-5) satellite are spatiotemporally matched with the aerosol product AOD L2.0 of the sites of the worldwide ground-based aerosol monitoring website AERONET. Data corresponding to small aerosol optical depth (AOD) values are thereby screened out to reduce the influence of aerosol and further to obtain directional polarized reflectance data of the land surface. The performance of five semiempirical bidirectionally polarized reflectance distribution function (BPDF) models of land surfaces for eight typical land surface types is quantitatively compared using the DPC measurements. The models compared included the Nadal-Bréon model, the Waquet model, the Maignan model, the Litvinov model, and the Xie-Cheng model. The comparison shows that the results of the Litvinov and Nadal-Bréon models agree well with the DPC measurements. Specifically, the average correlation coefficients of the results of the two models with the DPC measurements reach 0.958 and 0.952, respectively, and the corresponding average root-mean-square errors (RMSEs) are 0.202% and 0.223%, respectively. The research results serve as a reference concerning BPDF models for polarized reflectance estimation of land surfaces with DPC data and provide prior data support for applications such as the inversion of aerosol parameters with DPC data.