It's​ recommended to use bilinear interpolation for continuous data sets without distinct boundaries. The surface must be continuous and the closest points must be related. When you run the process, it generates a smoother surface, but not as severe as cubic convolution which uses 16 neighboring cells.

What is bilinear interpolation used for?

In computer vision and image processing, bilinear interpolation is used to resample images and textures. An algorithm is used to map a screen pixel location to a corresponding point on the texture map. A weighted average of the attributes (color, transparency, etc.)

Why does bilinear interpolation gives better results than nearest neighbor approach?

The difference between the two resampling functions is especially apparent in a surface plot of the resampled image (Fig. 7-16). Bilinear resampling produces a smoother surface, at the expense of being considerably slower than nearest-neighbor resampling, because Eq. (7-14) must be calculated for every output pixel.