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Hi!<br>
<br>
Some time ago, I asked for an inversion of gdal.Warp based on
GEOLOCATION arrays (longitude/latitude). Back then, my question was:
How can I transform an image with projected coordinates back to
cartesian/image coordinates, given that a geolocation array tells
GDAL where to put which pixel in the output?<br>
<br>
In 11/2021, this was unfortunately not implemented yet. However, is
seems like in the meantime someting like this has been added:<br>
- <a class="moz-txt-link-freetext" href="https://github.com/OSGeo/gdal/pull/5520">https://github.com/OSGeo/gdal/pull/5520</a><br>
- <a class="moz-txt-link-freetext" href="https://github.com/OSGeo/gdal/pull/6069">https://github.com/OSGeo/gdal/pull/6069</a><br>
-
<a class="moz-txt-link-freetext" href="https://github.com/OSGeo/gdal/blob/c92b22d02c99eae0152f49595947fb3747ddc280/autotest/gcore/geoloc.py#L396">https://github.com/OSGeo/gdal/blob/c92b22d02c99eae0152f49595947fb3747ddc280/autotest/gcore/geoloc.py#L396</a><br>
<br>
But I am not quite sure if that is what I want. If so, how would a
Python implementation based on gdal.Warp look like? Is that
documented somewhere?<br>
<br>
Best,<br>
Daniel<br>
<br>
<br>
<br>
<div class="moz-cite-prefix">Am 30.11.2021 um 14:20 schrieb Daniel
Scheffler:<br>
</div>
<blockquote type="cite"
cite="mid:b1cf6b86-4922-ca9a-bdd4-ec4fff2883d7@gfz-potsdam.de">
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
Ok thanks, too bad that this is not implemented. I think the
inversion of this transformation would be a nice feature to be
added in GDAL. It would be very useful to me (especially if it is
accessible via the Python bindings) and would ease the
implementation in a processing pipeline for the upcoming EnMAP
hyperspectral satellite. Should I open a feature request in the
GDAL issue tracker on GitHub?<br>
<br>
<br>
<div class="moz-cite-prefix">Am 30.11.2021 um 14:02 schrieb Even
Rouault:<br>
</div>
<blockquote type="cite"
cite="mid:1791a553-3e0e-f5e6-659d-11ac6f708ab3@spatialys.com">
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charset=UTF-8">
<p><br>
</p>
<div class="moz-cite-prefix">Le 30/11/2021 à 12:52, Daniel
Scheffler a écrit :<br>
</div>
<blockquote type="cite"
cite="mid:c2cf3a49-200b-91a6-dd81-1b3059859558@gfz-potsdam.de">
<meta http-equiv="content-type" content="text/html;
charset=UTF-8">
Thanks a lot for taking the time, Even, I got the
transformation from cartesian to projected coordinates to work
in memory with the GTiff driver. With MEM, NUMPY or VRT it
does not work because these formats are either not readable
from /vsimem/ or don´t have a regular file path which is
needed to set the <font size="2">X_DATASET and </font><font
size="2">Y_DATASET keys in the GEOLOCATION metadata</font>.<br>
</blockquote>
Ah indeed for X_DATASET/Y_DATASET, you can't use a MEM or NUMPY
dataset. But a /vsimem/xxx dataset in another format should
work.<br>
<blockquote type="cite"
cite="mid:c2cf3a49-200b-91a6-dd81-1b3059859558@gfz-potsdam.de">
<div class="moz-forward-container"> <br>
<font size="2">Regarding the inversion of this
transformation, i.e., </font><font size="2">from
projected coordinates to pixel/line:</font><br>
<blockquote type="cite">The logic of <span class="pl-en">GDALCreateGenImgProjTransformer2()
around <a class="moz-txt-link-freetext"
href="https://github.com/OSGeo/gdal/blob/master/alg/gdaltransformer.cpp#L1825"
moz-do-not-send="true">https://github.com/OSGeo/gdal/blob/master/alg/gdaltransformer.cpp#L1825</a>
which is for the source dataset should be ported a few
lines after for the target dataset. Probably with a new
transformer option to be able to point to an auxiliary
dataset, such as a VRT one of your example, to extract
the geolocation metadata items from it, that would be
different from the target dataset itself, because,
except perhaps for the netCDF case, most GDAL datasets
that expose a GEOLOCATION metadata domain must be
read-only.</span></blockquote>
<br>
I don´t completely get what you mean here. To me, this
sounds like there might be a way to do the inverted
transformation using the C-API of GDAL. </div>
</blockquote>
No, I meant there's some missing code to do that.<br>
<blockquote type="cite"
cite="mid:c2cf3a49-200b-91a6-dd81-1b3059859558@gfz-potsdam.de">
<div class="moz-forward-container">However, I am a Python
developer and my C skills are a bit poor. Is there any way
to use the Python bindings here?<br>
<br>
Kind regards,<br>
Daniel<br>
<br>
<br>
<br>
<br>
<div class="moz-cite-prefix">Am 26.11.2021 um 12:38 schrieb
Even Rouault:<br>
</div>
<blockquote type="cite"
cite="mid:2c9d72a2-3950-f846-b3e4-ee80500179a1@spatialys.com">
<meta http-equiv="Content-Type" content="text/html;
charset=UTF-8">
Daniel,<br>
<blockquote type="cite"
cite="mid:8e78eb30-6a89-104b-d2c4-f9ea8231aced@gfz-potsdam.de">
<br>
I am trying to convert image data from cartesian/image
coordinates to projected coordinates AND vice versa
using geolocation arrays in GDAL. I have two questions:<br>
<ol>
<li>Since this transformation is part of a processing
chain implemented in Python, I try to transform the
data directly in-memory, i.e, without any disk
access. This saves IO time and avoids permission
errors when trying to write temporary data on
Windows. How can this be done? I got correct results
with the code below, however, only when I
temporarily write the data to disk. I tried to write
the data to /vsimem/ using the MEM, GTiff and NUMPY
drivers. However, gdal.Warp can´t find the data
there (FileNotFoundError). I think, also the
gdal.Transformer class might be useful and I found
an interesting thread on that <a
href="https://lists.osgeo.org/pipermail/gdal-dev/2012-January/031502.html"
moz-do-not-send="true">here</a> and a related test
in the GDAL autotest suite (<a
href="https://github.com/OSGeo/gdal/blob/master/autotest/alg/transformgeoloc.py"
moz-do-not-send="true">here</a>). However, I can´t
get it to work for my specific case.</li>
</ol>
</blockquote>
<p>There's no reason it won't work with a in-memory
dataset.</p>
<p>If you use a MEM dataset, then you need to provide the
dataset object itself as the input dataset of
gdal.Warp() (the name of a MEM dataset is completely
ignored. a MEM dataset can't be opened, just created).</p>
<p>Similarly with a NUMPY dataset. With GTiff and
/vsimem/, they behave as a regular file. If you pass it
by name as input of gdal.Warp(), you need to make sure
to close (ds = None typically) the dataset before, so it
is properly flushed and can be opened. But you can also
pass it as an object without that constraint.</p>
<p>You can also create purely in-memory VRT files by
assigning them an empty name. Then of course you need to
provide them as objects to gdal.Warp()<br>
</p>
<p><br>
</p>
<blockquote type="cite"
cite="mid:8e78eb30-6a89-104b-d2c4-f9ea8231aced@gfz-potsdam.de">
<ol>
<li>My second question is how I can invert the
transformation, i.e., how can I transform an image
with projected coordinates back to cartesian/image
coordinates, given that a geolocation array tells
GDAL where to put which pixel in the output?
Background is a processing pipeline for satellite
data where some processing steps are running in
sensor geometry (image data as acquired by the
sensor, without any geocoding and projection) and I
need to provide corresponding AUX data which
originally come with projected coordinates.<br>
</li>
</ol>
</blockquote>
The logic of <span class="pl-en">GDALCreateGenImgProjTransformer2()
around <a class="moz-txt-link-freetext"
href="https://github.com/OSGeo/gdal/blob/master/alg/gdaltransformer.cpp#L1825"
moz-do-not-send="true">https://github.com/OSGeo/gdal/blob/master/alg/gdaltransformer.cpp#L1825</a>
which is for the source dataset should be ported a few
lines after for the target dataset. Probably with a new
transformer option to be able to point to an auxiliary
dataset, such as a VRT one of your example, to extract
the geolocation metadata items from it, that would be
different from the target dataset itself, because,
except perhaps for the netCDF case, most GDAL datasets
that expose a GEOLOCATION metadata domain must be
read-only.<br>
</span>
<blockquote type="cite"
cite="mid:8e78eb30-6a89-104b-d2c4-f9ea8231aced@gfz-potsdam.de">
<ol>
<li> <br>
</li>
</ol>
<p>Here is the code I already have to convert a sample
image from cartesian to projected coordinates:</p>
<blockquote>
<p><font size="2">import os<br>
from tempfile import TemporaryDirectory<br>
from osgeo import gdal, osr<br>
import numpy as np<br>
from matplotlib import pyplot as plt<br>
<br>
<br>
# get some test data<br>
swath_data = np.random.randint(1, 100, (500, 400))<br>
lons, lats = np.meshgrid(np.linspace(3, 5, 500),<br>
np.linspace(40, 42, 400))<br>
<br>
with TemporaryDirectory() as td:<br>
p_lons_tmp = os.path.join(td, 'lons.tif')<br>
p_lats_tmp = os.path.join(td, 'lats.tif')<br>
p_data_tmp = os.path.join(td, 'data.tif')<br>
p_data_vrt = os.path.join(td, 'data.vrt')<br>
p_data_mapgeo_vrt = os.path.join(td,
'data_mapgeo.vrt')<br>
<br>
# save numpy arrays to temporary tif files<br>
for arr, path in zip((swath_data, lons, lats),
(p_data_tmp, p_lons_tmp, p_lats_tmp)):<br>
rows, cols = arr.shape<br>
drv = gdal.GetDriverByName('GTiff')<br>
ds = drv.Create(path, cols, rows, 1,
gdal.GDT_Float64)<br>
ds.GetRasterBand(1).WriteArray(arr)<br>
del ds<br>
<br>
# add geolocation information to input data<br>
wgs84_wkt = osr.GetUserInputAsWKT('WGS84')<br>
utm_wkt = osr.GetUserInputAsWKT('EPSG:32632')<br>
ds = gdal.Translate(p_data_vrt, p_data_tmp,
format='VRT')<br>
ds.SetMetadata(<br>
<br>
dict(<br>
SRS=wgs84_wkt,<br>
X_DATASET=p_lons_tmp,<br>
Y_DATASET=p_lats_tmp,<br>
X_BAND='1',<br>
Y_BAND='1',<br>
PIXEL_OFFSET='0',<br>
LINE_OFFSET='0',<br>
PIXEL_STEP='1',<br>
LINE_STEP='1'<br>
),<br>
'GEOLOCATION'<br>
)del ds<br>
<br>
# warp from geolocation arrays and read the
result<br>
gdal.Warp(p_data_mapgeo_vrt, p_data_vrt,
format='VRT', geoloc=True,<br>
srcSRS=wgs84_wkt, dstSRS=utm_wkt)<br>
data_mapgeo =
gdal.Open(p_data_mapgeo_vrt).ReadAsArray()<br>
<br>
# visualize input and output data<br>
fig, axes = plt.subplots(1, 4)<br>
for i, (arr, title) in enumerate(zip((swath_data,
lons, lats, data_mapgeo),<br>
('swath data',
'lons', 'lats', 'projected data'))):<br>
axes[i].imshow(arr, cmap='gray')<br>
axes[i].set_title(title)<br>
plt.tight_layout()<br>
plt.show()</font></p>
<p><font size="2"><br>
</font></p>
</blockquote>
<p>Any help would be highly appreciated!</p>
<p>Best,</p>
<p>Daniel Scheffler<br>
</p>
<br>
<pre class="moz-signature" cols="72">--
M.Sc. Geogr. Daniel Scheffler
Helmholtz Centre Potsdam
GFZ German Research Centre For Geosciences
Department 1 - Geodesy and Remote Sensing
Section 1.4 - Remote Sensing
Telegrafenberg, 14473 Potsdam, Germany
Phone: +49 (0)331/288-1198
e-mail: <a class="moz-txt-link-abbreviated moz-txt-link-freetext" href="mailto:daniel.scheffler@gfz-potsdam.de" moz-do-not-send="true">daniel.scheffler@gfz-potsdam.de</a></pre>
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<pre class="moz-signature" cols="72">--
M.Sc. Geogr. Daniel Scheffler
Helmholtz Centre Potsdam
GFZ German Research Centre For Geosciences
Department 1 - Geodesy and Remote Sensing
Section 1.4 - Remote Sensing
Telegrafenberg, 14473 Potsdam, Germany
Phone: +49 (0)331/288-1198
e-mail: <a class="moz-txt-link-abbreviated moz-txt-link-freetext" href="mailto:daniel.scheffler@gfz-potsdam.de" moz-do-not-send="true">daniel.scheffler@gfz-potsdam.de</a></pre>
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<a class="moz-txt-link-freetext" href="http://www.spatialys.com" moz-do-not-send="true">http://www.spatialys.com</a>
My software is free, but my time generally not.</pre>
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<pre class="moz-signature" cols="72">--
M.Sc. Geogr. Daniel Scheffler
Helmholtz Centre Potsdam
GFZ German Research Centre For Geosciences
Department 1 - Geodesy and Remote Sensing
Section 1.4 - Remote Sensing
Telegrafenberg, 14473 Potsdam, Germany
Phone: +49 (0)331/288-1198
e-mail: <a class="moz-txt-link-abbreviated moz-txt-link-freetext" href="mailto:daniel.scheffler@gfz-potsdam.de" moz-do-not-send="true">daniel.scheffler@gfz-potsdam.de</a></pre>
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Dr. Daniel Scheffler
Helmholtz Centre Potsdam
GFZ German Research Centre For Geosciences
Department 1 - Geodesy and Remote Sensing
Section 1.4 - Remote Sensing and Geoinformatics
Telegrafenberg, 14473 Potsdam, Germany
Phone: +49 (0)331/288-1198
e-mail: <a class="moz-txt-link-abbreviated" href="mailto:daniel.scheffler@gfz-potsdam.de">daniel.scheffler@gfz-potsdam.de</a></pre>
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