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Open a mutliband raster, edit values in one of the bands, and overwrite the raster using Python/Rasterio?



Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern)
Announcing the arrival of Valued Associate #679: Cesar Manara
Unicorn Meta Zoo #1: Why another podcast?Using GDAL in python to stack Landsat bandsFirst time rasterio errorIn gdal how to save 3 dimensional array as stacked raster image?Creating NRG Multiband TIF from single bands using QGIS?How do I import multiple tif images and save it as one tiff file with skimage or gdal in python?Using Rasterio or GDAL to stack multiple bands without using subprocess commandsContinuously changing values in the same band of a multiband rasterCalling individual bands from multiband.tif in python perform action and save output in mutilband.tif?Is it possible to read in specific bands from a multi-band raster with gdal or rasterio?How to extract ALL bands from multiband raster in ArcGIS?



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1















I have numerous multiband rasters (36 band) in which preserving the band order is important for future processing. One of the bands often contains erroneous data and I'd like to be able to change all the values in within that band to 0, but keep the band in place. Then ideally overwrite the changes to the existing raster. Is there a way to do this without having to open the band in question, make the change to 0, and then re-stack all the other bands along with the edited band into a new file? Or at the very least save the changes to a new raster without having to call up the other 35 bands individually into the stacking function?



For instance



import rasterio as rio
import numpy as np

inraster = "path_to_a_mutliband_raster"
rast = rio.open(inraster)
badband = rast.read(7)
badbad[badband != 0] = 0


From there I'm not sure how to save those changes back into the mutliband raster.










share|improve this question
























  • I am not certain at all, but I would be surprised if it would be possible to edit only a single band without re-writing the full file. One somewhat messy workaround I can think of would be to write your 0-band to disk, then make a virtual raster that stacks the good bands before, the 0-band, and the good bands after into a single file.

    – Jon
    Apr 8 at 16:30

















1















I have numerous multiband rasters (36 band) in which preserving the band order is important for future processing. One of the bands often contains erroneous data and I'd like to be able to change all the values in within that band to 0, but keep the band in place. Then ideally overwrite the changes to the existing raster. Is there a way to do this without having to open the band in question, make the change to 0, and then re-stack all the other bands along with the edited band into a new file? Or at the very least save the changes to a new raster without having to call up the other 35 bands individually into the stacking function?



For instance



import rasterio as rio
import numpy as np

inraster = "path_to_a_mutliband_raster"
rast = rio.open(inraster)
badband = rast.read(7)
badbad[badband != 0] = 0


From there I'm not sure how to save those changes back into the mutliband raster.










share|improve this question
























  • I am not certain at all, but I would be surprised if it would be possible to edit only a single band without re-writing the full file. One somewhat messy workaround I can think of would be to write your 0-band to disk, then make a virtual raster that stacks the good bands before, the 0-band, and the good bands after into a single file.

    – Jon
    Apr 8 at 16:30













1












1








1








I have numerous multiband rasters (36 band) in which preserving the band order is important for future processing. One of the bands often contains erroneous data and I'd like to be able to change all the values in within that band to 0, but keep the band in place. Then ideally overwrite the changes to the existing raster. Is there a way to do this without having to open the band in question, make the change to 0, and then re-stack all the other bands along with the edited band into a new file? Or at the very least save the changes to a new raster without having to call up the other 35 bands individually into the stacking function?



For instance



import rasterio as rio
import numpy as np

inraster = "path_to_a_mutliband_raster"
rast = rio.open(inraster)
badband = rast.read(7)
badbad[badband != 0] = 0


From there I'm not sure how to save those changes back into the mutliband raster.










share|improve this question
















I have numerous multiband rasters (36 band) in which preserving the band order is important for future processing. One of the bands often contains erroneous data and I'd like to be able to change all the values in within that band to 0, but keep the band in place. Then ideally overwrite the changes to the existing raster. Is there a way to do this without having to open the band in question, make the change to 0, and then re-stack all the other bands along with the edited band into a new file? Or at the very least save the changes to a new raster without having to call up the other 35 bands individually into the stacking function?



For instance



import rasterio as rio
import numpy as np

inraster = "path_to_a_mutliband_raster"
rast = rio.open(inraster)
badband = rast.read(7)
badbad[badband != 0] = 0


From there I'm not sure how to save those changes back into the mutliband raster.







python editing rasterio multi-band






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Apr 9 at 14:57









nmtoken

8,12542866




8,12542866










asked Apr 8 at 15:21









jeremyg19jeremyg19

183




183












  • I am not certain at all, but I would be surprised if it would be possible to edit only a single band without re-writing the full file. One somewhat messy workaround I can think of would be to write your 0-band to disk, then make a virtual raster that stacks the good bands before, the 0-band, and the good bands after into a single file.

    – Jon
    Apr 8 at 16:30

















  • I am not certain at all, but I would be surprised if it would be possible to edit only a single band without re-writing the full file. One somewhat messy workaround I can think of would be to write your 0-band to disk, then make a virtual raster that stacks the good bands before, the 0-band, and the good bands after into a single file.

    – Jon
    Apr 8 at 16:30
















I am not certain at all, but I would be surprised if it would be possible to edit only a single band without re-writing the full file. One somewhat messy workaround I can think of would be to write your 0-band to disk, then make a virtual raster that stacks the good bands before, the 0-band, and the good bands after into a single file.

– Jon
Apr 8 at 16:30





I am not certain at all, but I would be surprised if it would be possible to edit only a single band without re-writing the full file. One somewhat messy workaround I can think of would be to write your 0-band to disk, then make a virtual raster that stacks the good bands before, the 0-band, and the good bands after into a single file.

– Jon
Apr 8 at 16:30










1 Answer
1






active

oldest

votes


















0














I did not find a solution to overwrite the existing raster, but the time of making a new one was much faster than I expected. In this case it still required calling up the other bands and writing them back to new file. Here is what I used -



import rasterio as rio
import numpy as np

rasterin = "path_to_a_mutliband_raster"
rasterout = 'path_to_output_raster'

rast = rio.open(rasterin)
meta = rast.meta
bands = [x + 1 for x in list(range(rast.count))]
rast.close()
badbands = [7, 16, 25]

with rio.open(rasterout, 'w', **meta) as dst:
with rio.open(rasterin) as src:
for ID, b in enumerate(bands,1):
if b in ndvibands:
ndvi = src.read(b)
ndvi[ndvi != 0] = 0
dst.write(ndvi, ID)
else:
data = src.read(b)
dst.write(data, ID)
dst.close





share|improve this answer























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    1 Answer
    1






    active

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    active

    oldest

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    active

    oldest

    votes









    0














    I did not find a solution to overwrite the existing raster, but the time of making a new one was much faster than I expected. In this case it still required calling up the other bands and writing them back to new file. Here is what I used -



    import rasterio as rio
    import numpy as np

    rasterin = "path_to_a_mutliband_raster"
    rasterout = 'path_to_output_raster'

    rast = rio.open(rasterin)
    meta = rast.meta
    bands = [x + 1 for x in list(range(rast.count))]
    rast.close()
    badbands = [7, 16, 25]

    with rio.open(rasterout, 'w', **meta) as dst:
    with rio.open(rasterin) as src:
    for ID, b in enumerate(bands,1):
    if b in ndvibands:
    ndvi = src.read(b)
    ndvi[ndvi != 0] = 0
    dst.write(ndvi, ID)
    else:
    data = src.read(b)
    dst.write(data, ID)
    dst.close





    share|improve this answer



























      0














      I did not find a solution to overwrite the existing raster, but the time of making a new one was much faster than I expected. In this case it still required calling up the other bands and writing them back to new file. Here is what I used -



      import rasterio as rio
      import numpy as np

      rasterin = "path_to_a_mutliband_raster"
      rasterout = 'path_to_output_raster'

      rast = rio.open(rasterin)
      meta = rast.meta
      bands = [x + 1 for x in list(range(rast.count))]
      rast.close()
      badbands = [7, 16, 25]

      with rio.open(rasterout, 'w', **meta) as dst:
      with rio.open(rasterin) as src:
      for ID, b in enumerate(bands,1):
      if b in ndvibands:
      ndvi = src.read(b)
      ndvi[ndvi != 0] = 0
      dst.write(ndvi, ID)
      else:
      data = src.read(b)
      dst.write(data, ID)
      dst.close





      share|improve this answer

























        0












        0








        0







        I did not find a solution to overwrite the existing raster, but the time of making a new one was much faster than I expected. In this case it still required calling up the other bands and writing them back to new file. Here is what I used -



        import rasterio as rio
        import numpy as np

        rasterin = "path_to_a_mutliband_raster"
        rasterout = 'path_to_output_raster'

        rast = rio.open(rasterin)
        meta = rast.meta
        bands = [x + 1 for x in list(range(rast.count))]
        rast.close()
        badbands = [7, 16, 25]

        with rio.open(rasterout, 'w', **meta) as dst:
        with rio.open(rasterin) as src:
        for ID, b in enumerate(bands,1):
        if b in ndvibands:
        ndvi = src.read(b)
        ndvi[ndvi != 0] = 0
        dst.write(ndvi, ID)
        else:
        data = src.read(b)
        dst.write(data, ID)
        dst.close





        share|improve this answer













        I did not find a solution to overwrite the existing raster, but the time of making a new one was much faster than I expected. In this case it still required calling up the other bands and writing them back to new file. Here is what I used -



        import rasterio as rio
        import numpy as np

        rasterin = "path_to_a_mutliband_raster"
        rasterout = 'path_to_output_raster'

        rast = rio.open(rasterin)
        meta = rast.meta
        bands = [x + 1 for x in list(range(rast.count))]
        rast.close()
        badbands = [7, 16, 25]

        with rio.open(rasterout, 'w', **meta) as dst:
        with rio.open(rasterin) as src:
        for ID, b in enumerate(bands,1):
        if b in ndvibands:
        ndvi = src.read(b)
        ndvi[ndvi != 0] = 0
        dst.write(ndvi, ID)
        else:
        data = src.read(b)
        dst.write(data, ID)
        dst.close






        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Apr 9 at 12:53









        jeremyg19jeremyg19

        183




        183



























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