Aiming at the problem that it is difficult for remote sensing data to achieve both high spatial and spectral resolution, a quadtree-based adaptive block area-to-point regression Kriging method (QAATPRK) is proposed to fuse the panchromatic (PAN) and multispectral (MS) data of GF-1.The proposed method is based on the area to point regression Kriging method, where the whole image is segmented into several independent fusion units and fused, splicing the results. For each individual fusion unit, spatial information of high-resolution PAN images were used for regression modeling and the residuals were treated by the regression Kriging method. The proposed method is compared with the Principal Component Analysis (PCA) method, wavelet transform method, Intensity-Hue-Saturation and Gram-Schmidt (IGS) method, and DenseNet. Root mean square error (RMSE), structure similarity (SSIM), universal image quality index (UIQI), relative global-dimensional synthesis error (ERGAS), and spectral angle mapper (SAM) demonstrate that the fusion image quality of the proposed method is the best and the spectral properties of the MS image are maintained.