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GDAL:重新投影 netCDF 文件

GDAL:重新投影 netCDF 文件

Helenr 2021-11-23 20:14:20
我正在尝试使用 GDAL 将 netCDF 文件转换为 EPSG:3857 以与 Mapbox 一起使用。这将是 .nc 到 .nc 的转换。不光栅。我愿意使用 GDAL 或其他方法来做到这一点。这些数据在进入控制台应用程序之前必须重新投影 - 这个过程需要数周时间才能找到解决方案 - 我认为这很简单。我正在为卫星数据着色。有 3 个 .nc 文件(蓝色、红色和红外线),它们在组合和处理后会创建一个彩色图像。下载 3 个文件(从 Amazon AWS)后,python 控制台应用程序进行处理并将 .jpg 转储到同一文件夹。该应用程序的源代码位于此处,因此您可以验证数据。(由于文件是超高分辨率的,所以速度很慢)。我试过的代码是:gdalwarp -t_srs EPSG:3857 test.nc test-projected.nc但是,已经尝试了其他几种变体,但没有任何效果。我不是这方面的专业人士,但我什至应该使用 gdalwarp 来做到这一点吗?我只想改变投影 - 没有别的,所以 python 应用程序仍然可以处理数据。它必须能够使用重新投影的文件创建 .jpg。
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慕婉清6462132

TA贡献1804条经验 获得超2个赞

这是我的解决方案:


# -*- coding: utf-8 -*-

"""

Created on Mon Mar  4 17:39:45 2019


@author: Guy Serbin

"""


import os, sys, glob, argparse

from osgeo import gdal, osr

from scipy.misc import imresize


parser = argparse.ArgumentParser(description = 'Script to create CONUS true color image from GOES 16 L1b data.')

parser.add_argument('-i', '--indir', type = str, default = r'C:\Data\Freelancer\DavidHolcomb', help = 'Input directory name.')

parser.add_argument('-o', '--outdir', type = str, default = None, help = 'Output directory name.')

parser.add_argument('-p', '--proj', type = int, default = 3857, help = 'Output projection, must be EPSG number.')

args = parser.parse_args()


if not args.indir:

    print('ERROR: --indir not set. exiting.')

    sys.exit()

elif not os.path.isdir(args.indir):

    print('ERROR: --indir not set to a valid directory path. exiting.')

    sys.exit()


if not args.outdir:

    print('WARNING: --outdir not set. Output will be written to --indir.')

    args.outdir = args.indir


o_srs = osr.SpatialReference()

o_srs.ImportFromEPSG(args.proj)



# based upon code ripped from https://riptutorial.com/gdal/example/25859/read-a-netcdf-file---nc--with-python-gdal


# Path of netCDF file

netcdf_red = glob.glob(os.path.join(args.indir, 'OR_ABI-L1b-RadC-M3C02_G16_s*.nc'))[0]

netcdf_green = glob.glob(os.path.join(args.indir, 'OR_ABI-L1b-RadC-M3C03_G16_s*.nc'))[0]

netcdf_blue = glob.glob(os.path.join(args.indir, 'OR_ABI-L1b-RadC-M3C01_G16_s*.nc'))[0]

baselist = os.path.basename(netcdf_blue).split('_')


outputfilename = os.path.join(args.outdir, 'OR_ABI-L1b-RadC-M3TrueColor_1_G16_{}.tif'.format(baselist[3]))

print('Output file will be: {}'.format(outputfilename))

tempfile = os.path.join(args.outdir, 'temp.tif')


# Specify the layer name to read

layer_name = "Rad"


# Open netcdf file.nc with gdal

print('Opening red band file: {}'.format(netcdf_red))

dsR = gdal.Open("NETCDF:{0}:{1}".format(netcdf_red, layer_name))

print('Opening green band file: {}'.format(netcdf_green))

dsG = gdal.Open("NETCDF:{0}:{1}".format(netcdf_green, layer_name))

print('Opening blue band file: {}'.format(netcdf_blue))

dsB = gdal.Open("NETCDF:{0}:{1}".format(netcdf_blue, layer_name))

red_srs = osr.SpatialReference()

red_srs.ImportFromWkt(dsR.GetProjectionRef())

i_srs = osr.SpatialReference()

i_srs.ImportFromWkt(dsG.GetProjectionRef())

GeoT = dsG.GetGeoTransform()

print(i_srs.ExportToWkt())

red_transform = osr.CoordinateTransformation(red_srs, o_srs)

transform = osr.CoordinateTransformation(i_srs, o_srs)


# Read full data from netcdf


print('Reading red band into memory.')

red = dsR.ReadAsArray(0, 0, dsR.RasterXSize, dsR.RasterYSize)

print('Resizing red band to match green and blue bands.')

red = imresize(red, 50, interp = 'bicubic')

print('Reading green band into memory.')

green = dsG.ReadAsArray(0, 0, dsG.RasterXSize, dsG.RasterYSize)

print('Reading blue band into memory.')

blue = dsB.ReadAsArray(0, 0, dsB.RasterXSize, dsB.RasterYSize)

red[red < 0] = 0

green[green < 0] = 0

blue[blue < 0] = 0


# Stack data and output

print('Stacking data.')

driver = gdal.GetDriverByName('GTiff')

stack = driver.Create('/vsimem/stack.tif', dsB.RasterXSize, dsB.RasterYSize, 3, gdal.GDT_Int16)

stack.SetProjection(i_srs.ExportToWkt())

stack.SetGeoTransform(GeoT)

stack.GetRasterBand(1).WriteArray(red)

stack.GetRasterBand(2).WriteArray(green)

stack.GetRasterBand(3).WriteArray(blue)

print('Warping data to new projection.')

warped = gdal.Warp('/vsimem/warped.tif', stack, dstSRS = o_srs, outputType = gdal.GDT_Int16)


print('Writing output to disk.')


outRaster = gdal.Translate(outputfilename, '/vsimem/warped.tif')


outRaster = None

red = None

green = None

blue = None

tmp_ds = None

dsR = None

dsG = None

dsB = None


print('Processing complete.')



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反对 回复 2021-11-23
?
斯蒂芬大帝

TA贡献1827条经验 获得超8个赞

您可以使用 rioxarray 来执行此操作。这样做的一个例子是:https : //corteva.github.io/rioxarray/html/examples/reproject.html


以下是针对您的用例的示例:


import rioxarray


xds = rioxarray.open_rasterio("OR_ABI-L1b-RadC-M3C01_G16_s20190621802131_e20190621804504_c20190621804546.nc")

<xarray.Dataset>

Dimensions:      (band: 1, x: 5000, y: 3000)

Coordinates:

  * y            (y) float64 1.584e+06 1.585e+06 ... 4.588e+06 4.589e+06

  * x            (x) float64 -3.627e+06 -3.626e+06 ... 1.381e+06 1.382e+06

  * band         (band) int64 1

    spatial_ref  int64 0

Data variables:

    Rad          (band, y, x) int16 ...

    DQF          (band, y, x) int8 ...

xds.rio.crs

CRS.from_wkt('PROJCS["unnamed",GEOGCS["unknown",DATUM["unnamed",SPHEROID["Spheroid",6378137,298.2572221]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]]],PROJECTION["Geostationary_Satellite"],PARAMETER["central_meridian",-75],PARAMETER["satellite_height",35786023],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],EXTENSION["PROJ4","+proj=geos +lon_0=-75 +h=35786023 +x_0=0 +y_0=0 +ellps=GRS80 +units=m +no_defs +sweep=x"]]')

然后,重新投影:


xds_3857 = xds.rio.reproject("epsg:3857")

<xarray.Dataset>

Dimensions:      (band: 1, x: 7693, y: 4242)

Coordinates:

  * x            (x) float64 -1.691e+07 -1.691e+07 ... -5.892e+06 -5.891e+06

  * y            (y) float64 7.714e+06 7.712e+06 ... 1.641e+06 1.64e+06

  * band         (band) int64 1

    spatial_ref  int64 0

Data variables:

    Rad          (band, y, x) int16 1023 1023 1023 1023 ... 1023 1023 1023 1023

    DQF          (band, y, x) int8 0 0 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0 0 0

Attributes:

    creation_date:  2019-09-25 01:02:54.590053

xds_3857.rio.crs

CRS.from_epsg(3857)

写入 netcdf:


xds_3857.to_netcdf("epsg3857.nc")


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反对 回复 2021-11-23
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