What methodology does the "bilinear" technique use to resample a raster?

The bilinear resampling technique utilizes the values of the four nearest cells surrounding a given pixel to interpolate a new value. This method is based on a weighted average of those four cells, where the weights are determined by the distance each neighboring cell is from the target pixel. The closer a neighboring cell is, the higher its influence on the interpolated value. This approach provides smoother transitions in the raster data and is particularly effective for continuous data, such as elevation, temperature, or other similar datasets.

In this context, focusing on surrounding cells allows bilinear interpolation to create a more accurate representation of the data than methods that rely on a single cell's value or employ more complex mathematical operations, such as quadratic interpolation. This makes bilinear resampling a widely utilized method in GIS for enhancing the quality and usability of raster datasets while preserving the original data's integrity as much as possible.