This tool will create an image mosaic from one or more input image files using one of three resampling methods including, nearest neighbour, bilinear interpolation, and cubic convolution. The order of the input source image files is important. Grid cells in the output image will be assigned the corresponding value determined from the last image found in the list to possess an overlapping coordinate.
Note that when the inputs
parameter is left unspecified, the tool will use all of the .tif, .tiff, .rdc, .flt, .sdat, and .dep files located in the working directory. This can be a useful way of mosaicing large number of tiles, particularly when the text string that would be required to specify all of the input tiles is longer than the allowable limit.
This is the preferred mosaicing tool to use when appending multiple images with little to no overlapping areas, e.g. tiled data. When images have significant overlap areas, users are advised to use the mosaic_with_feathering tool instead.
Resample is very similar in operation to the Mosaic tool. The Resample tool should be used when there is an existing image into which you would like to dump information from one or more source images. If the source images are more extensive than the destination image, i.e. there are areas that extend beyond the destination image boundaries, these areas will not be represented in the updated image. Grid cells in the destination image that are not overlapping with any of the input source images will not be updated, i.e. they will possess the same value as before the resampling operation. The Mosaic tool is used when there is no existing destination image. In this case, a new image is created that represents the bounding rectangle of each of the two or more input images. Grid cells in the output image that do not overlap with any of the input images will be assigned the NoData value.
def mosaic(self, images: List[Raster], resampling_method: str = "cc") -> Raster: ...