On Mon, 7 Dec 2020, Felix wrote:
Our application requires us to fetch for many pairs of (latitude, longitude)
all existing values within some radius from an existing raster dataset. Is it
possible to read values from a GDALRasterBand given some general bounding
box, even if it is at the edge of a dataset?
One can easily convert between bounding boxes in geographical coordinates and
pixels using Dataset::GetGeoTransform() and InvGeoTransform(), but
GDALRasterBand/GDALMDArray/the Python bindings seems to not have a method for
being queried by it. Of course, simple boxes can be read e.g. using the
Python methods Band::ReadAsArray/Band::ReadRaster. But this does not work
once queries get to the boundaries, as all of these methods do not support
"wrapping around" to the other side of the dataset. As an example:
Dataset: 1000 x 1000 pixels
Bounding box in pixels, given as two corner points in (x, y) pixels:
(950, 950) and (50, 50)
This should query all 50 by 50 pixel corners of the dataset and
result in a 100 by 100 pixel result
It arises when a point at the edge of a dataset is queried with a
radius of 50 pixels
However, numpy and the above methods do not allow to express such
wrap-around indexing
Is there some method that I'm overlooking or is this intentionally something
that users should implement for themselfs? It feels like such indexing would
be required in a lot of other places too.
Unless your dataset covers the whole world, I don't understand why would
wld want such a wrap-around for a geographical application.
Even then you would wrap at the left/right border but not the poles
(top/bottom).
If you are processing whole world data, could you generate a second raster
with the left and right halves swapped and split the points into two sets ?
Then provided you use the correct image for each set your radius wont
cross the edge of the raster.
--
Andrew C. Aitchison Kendal, UK
[email protected]
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