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<p>Slightly less tricky using gdal.ApplyGeoTransform() (note the
explicit cast of line[0]/col[0]) as a int, to avoid a numpy type
to be used, which confuses gdal.ApplyGeoTransform) :</p>
<p>import numpy as np<br>
from osgeo import gdal<br>
ds = gdal.Open('byte.tif', gdal.GA_ReadOnly)<br>
rb = ds.GetRasterBand(1)<br>
img_array = rb.ReadAsArray()<br>
vmin = img_array.min()<br>
(line, col) = np.where(img_array==vmin)<br>
line = int(line[0])<br>
col = int(col[0])<br>
print(f"col={col}, line={line}")<br>
gt = ds.GetGeoTransform()<br>
X, Y = gdal.ApplyGeoTransform(gt, col, line)<br>
print(f"X={X}, Y={Y}")<br>
<br>
</p>
<div class="moz-cite-prefix">Le 30/10/2024 à 01:41, Even Rouault via
gdal-dev a écrit :<br>
</div>
<blockquote type="cite"
cite="mid:9fe9a6c5-83f6-4bcc-9dd9-e238dba2d59f@spatialys.com">
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<p>if you are just interested in any point where the minimum is
reached:<br>
</p>
<p>import numpy as np<br>
from osgeo import gdal<br>
ds = gdal.Open('<span lang="EN-US">P3412A</span>.tif',
gdal.GA_ReadOnly)<br>
rb = ds.GetRasterBand(1)<br>
img_array = rb.ReadAsArray()<br>
vmin = img_array.min()<br>
(line, col) = np.where(img_array==vmin)<br>
line = line[0]<br>
col = col[0]<br>
print(f"col={col}, line={line}")<br>
gt = ds.GetGeoTransform()<br>
X = gt[0] + gt[1] * col + gt[2] * line<br>
Y = gt[3] + gt[4] * col + gt[5] * line<br>
print(f"X={X}, Y={Y}")<br>
<br>
</p>
<div class="moz-cite-prefix">Le 30/10/2024 à 01:31, Rahkonen Jukka
via gdal-dev a écrit :<br>
</div>
<blockquote type="cite"
cite="mid:DB9PR09MB688709C9E2EF933987BE0FCDFD542@DB9PR09MB6887.eurprd09.prod.outlook.com">
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<p class="MsoNormal">Hi,<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><span lang="EN-US">I would like to know
the georeferenced coordinates of the min and max values of
a DEM file. Even better if I could forward them into a
vector file. If the minimum or maximum happens to be on a
flat area like seabed I would be happy with the first
pixel at the moment.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">By copy-pasting from </span><a
href="https://stackoverflow.com/questions/41996079/how-do-i-open-geotiff-images-with-gdal-in-python"
moz-do-not-send="true"><span lang="EN-US">How do I open
geotiff images with GDAL in Python? - Stack Overflow</span></a>
<span lang="EN-US">and </span><a
href="https://en.moonbooks.org/Articles/How-to-find-the-indexes-of-the-minimum-or-maximum-values-in-a-matrix-using-python-/"
moz-do-not-send="true"><span lang="EN-US">How to find the
indexes of the minimum or maximum value(s) in a matrix
using python ?</span></a> <span lang="EN-US">I think I
managed to get the correct points as numpy indexes<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">>>> import
numpy as np<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">>>> from
osgeo import gdal<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">>>> ds =
gdal.Open('P3412A.tif', gdal.GA_ReadOnly)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">>>> rb =
ds.GetRasterBand(1)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">>>> img_array
= rb.ReadAsArray()<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">>>> vmin =
img_array.min()<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">>>> vmax =
img_array.max()<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">>>> vmin<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">-0.929<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">>>> vmax<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">17.246<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">>>><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">>>>
np.where(img_array==vmin)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">(array([1504],
dtype=intg64), array([1189], dtype=int64))<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">>>>
np.where(img_array==vmax)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">(array([1545],
dtype=int64), array([2423], dtype=int64))<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">>>><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">But now I have no idea
about how to get the georeferenced coordinates.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">The task feels rather
simple and I was sure that someone has already made an
utility or a QGIS plugin, but all I have found yet is for
R. I was thinking that perhaps some of the gdaldem modes
could be misused for this purpose, but I believe they
cannot. For QGIS I found advice to use an obvious but
clumsy method of polygonising the raster and finding the
extremes from the vector data. And one OpenJUMP developer
took the challenge and wrote a prototype with Java but it
is not complete yet.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">-Jukka Rahkonen-<o:p></o:p></span></p>
</div>
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moz-do-not-send="true">http://www.spatialys.com</a>
My software is free, but my time generally not.
Butcher of all kinds of standards, open or closed formats. At the end, this is just about bytes.</pre>
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<pre class="moz-signature" cols="72">--
<a class="moz-txt-link-freetext" href="http://www.spatialys.com">http://www.spatialys.com</a>
My software is free, but my time generally not.
Butcher of all kinds of standards, open or closed formats. At the end, this is just about bytes.</pre>
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