Resampling a raster using rasterio – simple modification of grid spacing

Question

I am resampling raster data using Python’s rasterio. Looking at the rasterio.enums.Resampling class, it appears the only way to do this is to interpolate between adjacent raster grids, essentially smoothing the data.

Is there some way to do a simple upsampling that effectively divides one raster grid into many and preserves the original value for all of the sub-grids?

My resampling script is as follows – currently using the bi-linear method:

with rasterio.open(str(rasterpath+filename), crs="EPSG:4326") as src:
    data = src.read(
        out_shape=(
            src.count,
            int(src.height * upscale_factor),
            int(src.width * upscale_factor)
        ),
        resampling=Resampling.bilinear)

# scale image transform
    transform = src.transform * src.transform.scale(
        (src.width / data.shape[-1]),
        (src.height / data.shape[-2])
    )

Any suggestions? I would think some sort of treatment for discrete data would be built in but have not found it yet…

Asked By: Kingle

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Answer 1

I found a solution.

Deleting resampling=Resampling.bilinear avoids interpolation and performs a "simple" resampling.

Answered By: Kingle

Answer 2

What you’re trying to do is nearest neighbor interpolation, so you could specify resampling = Resampling.nearest. This is the default resampling algorithm, so not specifying any resampling algorithm equates to this. You can find all available resampling algorithms here.

Answered By: Pau Wiersma

Resampling a raster using rasterio – simple modification of grid spacing

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