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.Tif to .GeoTiff Scaling issue using GDAL

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I was trying to georeference a .tif file generated from a matplotlib output using GDAL's python bindings and it seems to be off-scale. My objective was to create a geotiff file from the output of a contourf function. Code samples are pasted below.

fig = plt.figure()

plt.axis('off')

plt.contour(land_reference,levels=[-9999],origin='upper', cmap='gray',extent=(77.53,81.05,28.65,31.49))

plt.contourf(Z, levels=levels,origin='upper', cmap='RdYlGn',extent=(77.53,81.05,28.65,31.49))



fig.canvas.draw()





plt.savefig(r'C:UsersMRG16-10417DesktopNewtestspecies.tif',transparent='true',bbox_inches='tight')

Then I use GDAL as follows,

from osgeo import gdal, osr

import numpy as np





src_filename ='C:/Users/MRG16-10417/Desktop/New/testspecies.tif'

dst_filename = 'C:/Users/MRG16-10417/Desktop/New/newspecies.tif'



#The row and column values of the tif file was used here

nrows=252

ncols=386



src_ds = gdal.Open(src_filename)

format = "GTiff"

driver = gdal.GetDriverByName(format)



xmin = 77.5000000002060005

xmax = 81.0833333335421997

ymin = 28.6666666666176049

ymax = 31.4999999999532037



# Open destination dataset

dst_ds = driver.CreateCopy(dst_filename, src_ds, 0)







xres = (xmax-xmin)/float(ncols)

yres = (ymax-ymin)/float(nrows)

geotransform=(xmin,xres,0,ymax,0, -yres)  



# Set location

dst_ds.SetGeoTransform(geotransform)



# Get raster projection

epsg = 4326

srs = osr.SpatialReference()

srs.ImportFromEPSG(epsg)

dest_wkt = srs.ExportToWkt()



# Set projection

dst_ds.SetProjection(dest_wkt)



# Close files

dst_ds = None

src_ds = None

The resultant image on QGIS,
As you can see the image is slightly off scale and isn't exactly overlapping on the reference .shp file of the same geographic extents and projection.

What could be the reason for this?

Is it because the source image that is incorrect, as matplotlib could be scaling down the image?

pyqgis gdal georeferencing

share|improve this question

edited May 28 '18 at 13:42

PolyGeo♦

54k1782246

asked May 28 '18 at 6:23

Amruth KiranAmruth Kiran

185

bumped to the homepage by Community♦ 4 mins ago

This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.

add a comment | 

0

I was trying to georeference a .tif file generated from a matplotlib output using GDAL's python bindings and it seems to be off-scale. My objective was to create a geotiff file from the output of a contourf function. Code samples are pasted below.

fig = plt.figure()

plt.axis('off')

plt.contour(land_reference,levels=[-9999],origin='upper', cmap='gray',extent=(77.53,81.05,28.65,31.49))

plt.contourf(Z, levels=levels,origin='upper', cmap='RdYlGn',extent=(77.53,81.05,28.65,31.49))



fig.canvas.draw()





plt.savefig(r'C:UsersMRG16-10417DesktopNewtestspecies.tif',transparent='true',bbox_inches='tight')

Then I use GDAL as follows,

from osgeo import gdal, osr

import numpy as np





src_filename ='C:/Users/MRG16-10417/Desktop/New/testspecies.tif'

dst_filename = 'C:/Users/MRG16-10417/Desktop/New/newspecies.tif'



#The row and column values of the tif file was used here

nrows=252

ncols=386



src_ds = gdal.Open(src_filename)

format = "GTiff"

driver = gdal.GetDriverByName(format)



xmin = 77.5000000002060005

xmax = 81.0833333335421997

ymin = 28.6666666666176049

ymax = 31.4999999999532037



# Open destination dataset

dst_ds = driver.CreateCopy(dst_filename, src_ds, 0)







xres = (xmax-xmin)/float(ncols)

yres = (ymax-ymin)/float(nrows)

geotransform=(xmin,xres,0,ymax,0, -yres)  



# Set location

dst_ds.SetGeoTransform(geotransform)



# Get raster projection

epsg = 4326

srs = osr.SpatialReference()

srs.ImportFromEPSG(epsg)

dest_wkt = srs.ExportToWkt()



# Set projection

dst_ds.SetProjection(dest_wkt)



# Close files

dst_ds = None

src_ds = None

The resultant image on QGIS,
As you can see the image is slightly off scale and isn't exactly overlapping on the reference .shp file of the same geographic extents and projection.

What could be the reason for this?

Is it because the source image that is incorrect, as matplotlib could be scaling down the image?

pyqgis gdal georeferencing

share|improve this question

edited May 28 '18 at 13:42

PolyGeo♦

54k1782246

asked May 28 '18 at 6:23

Amruth KiranAmruth Kiran

185

bumped to the homepage by Community♦ 4 mins ago

This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.

add a comment | 

I was trying to georeference a .tif file generated from a matplotlib output using GDAL's python bindings and it seems to be off-scale. My objective was to create a geotiff file from the output of a contourf function. Code samples are pasted below.

fig = plt.figure()

plt.axis('off')

plt.contour(land_reference,levels=[-9999],origin='upper', cmap='gray',extent=(77.53,81.05,28.65,31.49))

plt.contourf(Z, levels=levels,origin='upper', cmap='RdYlGn',extent=(77.53,81.05,28.65,31.49))



fig.canvas.draw()





plt.savefig(r'C:UsersMRG16-10417DesktopNewtestspecies.tif',transparent='true',bbox_inches='tight')

Then I use GDAL as follows,

from osgeo import gdal, osr

import numpy as np





src_filename ='C:/Users/MRG16-10417/Desktop/New/testspecies.tif'

dst_filename = 'C:/Users/MRG16-10417/Desktop/New/newspecies.tif'



#The row and column values of the tif file was used here

nrows=252

ncols=386



src_ds = gdal.Open(src_filename)

format = "GTiff"

driver = gdal.GetDriverByName(format)



xmin = 77.5000000002060005

xmax = 81.0833333335421997

ymin = 28.6666666666176049

ymax = 31.4999999999532037



# Open destination dataset

dst_ds = driver.CreateCopy(dst_filename, src_ds, 0)







xres = (xmax-xmin)/float(ncols)

yres = (ymax-ymin)/float(nrows)

geotransform=(xmin,xres,0,ymax,0, -yres)  



# Set location

dst_ds.SetGeoTransform(geotransform)



# Get raster projection

epsg = 4326

srs = osr.SpatialReference()

srs.ImportFromEPSG(epsg)

dest_wkt = srs.ExportToWkt()



# Set projection

dst_ds.SetProjection(dest_wkt)



# Close files

dst_ds = None

src_ds = None

The resultant image on QGIS,
As you can see the image is slightly off scale and isn't exactly overlapping on the reference .shp file of the same geographic extents and projection.

What could be the reason for this?

Is it because the source image that is incorrect, as matplotlib could be scaling down the image?

pyqgis gdal georeferencing

share|improve this question

edited May 28 '18 at 13:42

PolyGeo♦

54k1782246

asked May 28 '18 at 6:23

Amruth KiranAmruth Kiran

185

fig = plt.figure()

plt.axis('off')

plt.contour(land_reference,levels=[-9999],origin='upper', cmap='gray',extent=(77.53,81.05,28.65,31.49))

plt.contourf(Z, levels=levels,origin='upper', cmap='RdYlGn',extent=(77.53,81.05,28.65,31.49))



fig.canvas.draw()





plt.savefig(r'C:UsersMRG16-10417DesktopNewtestspecies.tif',transparent='true',bbox_inches='tight')

from osgeo import gdal, osr

import numpy as np





src_filename ='C:/Users/MRG16-10417/Desktop/New/testspecies.tif'

dst_filename = 'C:/Users/MRG16-10417/Desktop/New/newspecies.tif'



#The row and column values of the tif file was used here

nrows=252

ncols=386



src_ds = gdal.Open(src_filename)

format = "GTiff"

driver = gdal.GetDriverByName(format)



xmin = 77.5000000002060005

xmax = 81.0833333335421997

ymin = 28.6666666666176049

ymax = 31.4999999999532037



# Open destination dataset

dst_ds = driver.CreateCopy(dst_filename, src_ds, 0)







xres = (xmax-xmin)/float(ncols)

yres = (ymax-ymin)/float(nrows)

geotransform=(xmin,xres,0,ymax,0, -yres)  



# Set location

dst_ds.SetGeoTransform(geotransform)



# Get raster projection

epsg = 4326

srs = osr.SpatialReference()

srs.ImportFromEPSG(epsg)

dest_wkt = srs.ExportToWkt()



# Set projection

dst_ds.SetProjection(dest_wkt)



# Close files

dst_ds = None

src_ds = None

share|improve this question

edited May 28 '18 at 13:42

PolyGeo♦

54k1782246

asked May 28 '18 at 6:23

Amruth KiranAmruth Kiran

185

share|improve this question

edited May 28 '18 at 13:42

PolyGeo♦

54k1782246

asked May 28 '18 at 6:23

Amruth KiranAmruth Kiran

185

edited May 28 '18 at 13:42

PolyGeo♦

54k1782246

edited May 28 '18 at 13:42

PolyGeo♦

54k1782246

asked May 28 '18 at 6:23

Amruth KiranAmruth Kiran

185

asked May 28 '18 at 6:23

Amruth KiranAmruth Kiran

185

1 Answer
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0

I eventually figured out that matplotlib by default interpolates and I was losing a bunch rows/columns, saving that as an image further reduced the overall quality. Setting interpolation to none and dpi at 300, with a little fix to the lat-longs (extend the bbox) helped me overlay the imagery perfectly.

share|improve this answer

answered Jun 7 '18 at 7:14

Amruth KiranAmruth Kiran

185

add a comment | 

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0

I eventually figured out that matplotlib by default interpolates and I was losing a bunch rows/columns, saving that as an image further reduced the overall quality. Setting interpolation to none and dpi at 300, with a little fix to the lat-longs (extend the bbox) helped me overlay the imagery perfectly.

share|improve this answer

answered Jun 7 '18 at 7:14

Amruth KiranAmruth Kiran

185

add a comment | 

0

I eventually figured out that matplotlib by default interpolates and I was losing a bunch rows/columns, saving that as an image further reduced the overall quality. Setting interpolation to none and dpi at 300, with a little fix to the lat-longs (extend the bbox) helped me overlay the imagery perfectly.

share|improve this answer

answered Jun 7 '18 at 7:14

Amruth KiranAmruth Kiran

185

add a comment | 

I eventually figured out that matplotlib by default interpolates and I was losing a bunch rows/columns, saving that as an image further reduced the overall quality. Setting interpolation to none and dpi at 300, with a little fix to the lat-longs (extend the bbox) helped me overlay the imagery perfectly.

share|improve this answer

answered Jun 7 '18 at 7:14

Amruth KiranAmruth Kiran

185

share|improve this answer

answered Jun 7 '18 at 7:14

Amruth KiranAmruth Kiran

185

answered Jun 7 '18 at 7:14

Amruth KiranAmruth Kiran

185

answered Jun 7 '18 at 7:14

Amruth KiranAmruth Kiran

185