如何投影和重新采样网格以与GDAL python匹配另一个网格？

Question

Clarification: I somehow left out the key aspect: not using os.system or subprocess - just the python API.

I'm trying to convert a section of a NOAA GTX offset grid for vertical datum transformations and not totally following how to do this in GDAL with python. I'd like to take a grid (in this case a Bathymetry Attributed Grid, but it could be a geotif) and use it as the template that I'd like to do to. If I can do this right, I have a feeling that it will greatly help people make use of this type of data.

Here is what I have that is definitely not working. When I run gdalinfo on the resulting destination dataset (dst_ds), it does not match the source grid BAG.

from osgeo import gdal, osr

bag = gdal.Open(bag_filename)
gtx = gdal.Open(gtx_filename)

bag_srs = osr.SpatialReference()
bag_srs.ImportFromWkt(bag.GetProjection())

vrt = gdal.AutoCreateWarpedVRT(gtx, None, bag_srs.ExportToWkt(), gdal.GRA_Bilinear,  0.125)

dst_ds = gdal.GetDriverByName('GTiff').Create(out_filename, bag.RasterXSize, bag.RasterYSize,
                                            1, gdalconst.GDT_Float32)
dst_ds.SetProjection(bag_srs.ExportToWkt())
dst_ds.SetGeoTransform(vrt.GetGeoTransform())

def warp_progress(pct, message, user_data):
  return 1

gdal.ReprojectImage(gtx, dst_ds, None, None, gdal.GRA_NearestNeighbour, 0, 0.125, warp_progress, None)

Example files (but any two grids where they overlap, but are in different projections would do):

• http://surveys.ngdc.noaa.gov/mgg/NOS/coast/F00001-F02000/F00574/BAG/ F00574_MB_2m_MLLW_2of3.bag
• http://vdatum.noaa.gov/download/data/VDatum_National.zip MENHMAgome01_8301/mllw.gtx

The command line equivalent to what I'm trying to do:

gdalwarp -tr 2 -2 -te 369179 4773093 372861 4775259 -of VRT -t_srs EPSG:2960 \
     MENHMAgome01_8301/mllw.gtx  mllw-2960-crop-resample.vrt
gdal_translate mllw-2960-crop-resample.{vrt,tif}

Answer 1

Thanks to Jamie for the answer.

#!/usr/bin/env python

from osgeo import gdal, gdalconst

# Source
src_filename = 'MENHMAgome01_8301/mllw.gtx'
src = gdal.Open(src_filename, gdalconst.GA_ReadOnly)
src_proj = src.GetProjection()
src_geotrans = src.GetGeoTransform()

# We want a section of source that matches this:
match_filename = 'F00574_MB_2m_MLLW_2of3.bag'
match_ds = gdal.Open(match_filename, gdalconst.GA_ReadOnly)
match_proj = match_ds.GetProjection()
match_geotrans = match_ds.GetGeoTransform()
wide = match_ds.RasterXSize
high = match_ds.RasterYSize

# Output / destination
dst_filename = 'F00574_MB_2m_MLLW_2of3_mllw_offset.tif'
dst = gdal.GetDriverByName('GTiff').Create(dst_filename, wide, high, 1, gdalconst.GDT_Float32)
dst.SetGeoTransform( match_geotrans )
dst.SetProjection( match_proj)

# Do the work
gdal.ReprojectImage(src, dst, src_proj, match_proj, gdalconst.GRA_Bilinear)

del dst # Flush

Answer 2

If I understand the question correctly, you could accomplish your goal by running gdalwarp and gdal_translate as subprocesses. Just assemble your options then do the following for example:

import subprocess

param = ['gdalwarp',option1,option2...]
cmd = ' '.join(param)
process = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
stdout = ''.join(process.stdout.readlines())
stderr = ''.join(process.stderr.readlines())

if len(stderr) > 0:
    raise IOError(stderr)

It may not be the most elegant solution, but it will get the job done. Once it is run, just load your data into numpy using gdal and carry on your way.