[gdal-dev] gdalwarp problems with MODIS L1B

[Yuta Sato]

Hi,

I think the MOD021KM swath product is point data, which should be gridded
using the array of latitude and longitude given.
gdal griddata may be an option. However, it's very slow even for a single
band of MOD021KM product.

MODIS team provides MODIS Swath Reprojection Tool for gridding the data,
which performs fast.
 https://lpdaac.usgs.gov/tools/modis_reprojection_tool_swath

I do not know the science behind MODIS Swath Reprojection Tool why it's
faster than the gdal griddata.
Can we discuss and implement a faster gridding tool in gdal? Why I am
focusing gdal is because the MODIS swath tool works only for MODIS data,
but the expected gdal tool would work for any data.

Thanks.

On Thu, May 21, 2015 at 4:45 PM, Rutger <kassies at gmail.com> wrote:

> Hey,
>
> Maybe i'm missing something, but for as far as i know, the MODIS MOD021KM
> product is still a 'swath', and therefore still containing the bow-tie
> effect as the result of the scanning sensor. Wouldn't this mean that
> gdalwarp will never work? The lat/lon arrays aren't continuous, so any
> fitting (GCP/TPS) wont be accurate. And upsampling the arrays with cubic,
> like Even did, will result in interpolating pixels which are next each
> other
> in the array/file, but aren't next to each other 'on the ground', wont work
> well.
>
> I think you need to either use a dedicated algorithm (like gradient
> search),
> or something very generic (like the KDTree of Pyresample) to overcome the
> bow-tie effect.
>
> I have spend alot of time experimenting with this in GDAL, since i try to
> do
> as much with GDAL as possible. But projecting a swath file from a scanning
> sensor (like MODIS or VIIRS) is something i have never gotten to work. For
> some historic discussion about this see for example:
>
> http://osgeo-org.1560.x6.nabble.com/gdal-dev-reproject-python-numpy-binary-swath-lat-lon-td4978609.html
>
>
> Regards,
> Rutger
>
>
>
> --
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> Sent from the GDAL - Dev mailing list archive at Nabble.com.
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