GDAL：重新投影netCDF文件

Question

我试图通过使用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。不要光栅。我愿意使用GDAL或其他方法来执行此操作。这些数据在进入控制台应用程序之前必须重新投影 - 这个过程需要数周才能找到解决方案 - 我认为这很简单。

我正致力于卫星数据的着色。有3个.nc文件（蓝色，红色和红外），当组合和处理时，会创建一个彩色图像。下载3个文件后（从Amazon AWS），python控制台应用程序执行处理并将.jpg转储到同一文件夹。该应用程序的源代码是Located here so you may validate the data。 （由于文件是超高分辨率，因此速度很慢）。

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。

我不是这个专业人士，但我是否应该使用gdalwarp这样做？我只想改变投影 - 没有别的，所以python应用程序仍然可以使用数据。它必须能够使用重新投影的文件创建.jpg。

以下链接是需要转换的数据样本：

.nc file on AWS > Color Channel 1 (Blue 1km resolution)

.nc file on AWS > Color Channel 2 (Red, Higher 0.5km resolution & larger file size)

.nc file on AWS > Color Channel 3 (Infrared - serves as green)

另外，网上其他人通过https://github.com/blaylockbk/pyBKB_v2/tree/master/BB_GOES16的pyproj模块使用类似投影完成了这项工作。 （我的必须是EPSG：3857用于Mapbox）。如果python代码被修改为一次性执行此操作，那也会很棒。作为最后的希望，我开了一笔赏金。

我不知道python，所以我一直在尝试GDAL - 但是为了实现预期的结果（或一个正在运行的GDAL脚本）添加到我的源代码中的工作python代码将获得赏金。

Answer 1

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.')