# Downsampling Geotiff using summation - Gdal/Numpy

Depending on the version of GDAL, there are a few different resample options available; see gdalwarp.

## GDAL 1.10 or later using `-r average`

average resampling, computes the weighted average of all non-NODATA contributing pixels

This isn't tested, but should look something like:

```
gdalwarp -t_srs EPSG:4326 -tr 0.5 0.66 -r average fine_one_sq_km.tif coarse_average.tif
```

Then to get the *sum*, multiply the average by the number of pixels of the fine resolution raster in one pixel of the coarse resolution raster, which hopefully is constant (you could assume it is).

## GDAL 3.1 or later using `-r sum`

compute the weighted sum of all non-NODATA contributing pixels

This should look like this:

```
gdalwarp -t_srs EPSG:4326 -tr 0.5 0.66 -r sum fine_one_sq_km.tif coarse_sum.tif
```

Otherwise, `scipy.ndimage.measurements.sum_labels`

(or `sum`

for older versions) can be used to aggregate multidimensional sums. But this may rely on perfect matchings between grids.

Apparently, `gdalwarp`

got a new `sum`

method in GDAL release 3.1.0, see release notes. Adapting from the above solution:

```
gdalwarp -t_srs EPSG:4326 -tr 0.5 0.66 -r sum fine_one_sq_km.tif coarse_sum.tif
```