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) :
import numpy as np
from osgeo import gdal
ds = gdal.Open('byte.tif', gdal.GA_ReadOnly)
rb = ds.GetRasterBand(1)
img_array = rb.ReadAsArray()
vmin = img_array.min()
(line, col) = np.where(img_array==vmin)
line = int(line[0])
col = int(col[0])
print(f"col={col}, line={line}")
gt = ds.GetGeoTransform()
X, Y = gdal.ApplyGeoTransform(gt, col, line)
print(f"X={X}, Y={Y}")
Le 30/10/2024 à 01:41, Even Rouault via gdal-dev a écrit :
if you are just interested in any point where the minimum is reached:
import numpy as np
from osgeo import gdal
ds = gdal.Open('P3412A.tif', gdal.GA_ReadOnly)
rb = ds.GetRasterBand(1)
img_array = rb.ReadAsArray()
vmin = img_array.min()
(line, col) = np.where(img_array==vmin)
line = line[0]
col = col[0]
print(f"col={col}, line={line}")
gt = ds.GetGeoTransform()
X = gt[0] + gt[1] * col + gt[2] * line
Y = gt[3] + gt[4] * col + gt[5] * line
print(f"X={X}, Y={Y}")
Le 30/10/2024 à 01:31, Rahkonen Jukka via gdal-dev a écrit :
Hi,
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.
By copy-pasting from How do I open geotiff images with GDAL in
Python? - Stack Overflow
<https://stackoverflow.com/questions/41996079/how-do-i-open-geotiff-images-with-gdal-in-python>
and How to find the indexes of the minimum or maximum value(s) in a
matrix using python ?
<https://en.moonbooks.org/Articles/How-to-find-the-indexes-of-the-minimum-or-maximum-values-in-a-matrix-using-python-/>
I think I managed to get the correct points as numpy indexes
>>> import numpy as np
>>> from osgeo import gdal
>>> ds = gdal.Open('P3412A.tif', gdal.GA_ReadOnly)
>>> rb = ds.GetRasterBand(1)
>>> img_array = rb.ReadAsArray()
>>> vmin = img_array.min()
>>> vmax = img_array.max()
>>> vmin
-0.929
>>> vmax
17.246
>>>
>>> np.where(img_array==vmin)
(array([1504], dtype=intg64), array([1189], dtype=int64))
>>> np.where(img_array==vmax)
(array([1545], dtype=int64), array([2423], dtype=int64))
>>>
But now I have no idea about how to get the georeferenced coordinates.
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.
-Jukka Rahkonen-
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--
http://www.spatialys.com
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.
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