Question

我有几个栅格，其中像素信息是高程数据。但是，图像中存在许多无数据值（零），超出了我想要的数据范围，因此文件大小不必要地大。我尝试使用gdal和numpy的混合裁剪图像，但是我注意到图像中有一个小的亚像素大小的偏移。这是舍入错误，可以采取任何措施解决此问题吗？

它在某些地方不是很好的Python语言，但是似乎可以正常工作，除了很小的移位

我也愿意使用python / numpy / gdal ...的任何其他方法...

我的代码是：

from osgeo import gdal
import numpy as np
import os
import subprocess

np.set_printoptions(threshold=np.nan)

inDir = '/path/to/files'
outDir = '/path/for/outfiles'

files = [file for file in os.listdir(inDir) if file.endswith('.tif')]

for file in files:
    outfile= os.path.join(outDir, file)
    if os.path.isfile(outfile):
        print('File exists')
        pass
    else:
        try:
            print(file)

            # open raster and read in the data
            dataset = gdal.Open(file)
            band = dataset.GetRasterBand(1)
            Cols = dataset.RasterXSize
            Rows = dataset.RasterYSize
            print('Reading Radar data...')
            data = band.ReadAsArray(0, 0, Cols, Rows).astype(np.float)
            # Read in the projection onfo
            ulx, xres, xskew, uly, yskew, yres  = dataset.GetGeoTransform()

            # define the corner co-ords
            ulx = ulx
            uly = uly
            lrx = ulx + (dataset.RasterXSize * xres)
            lry = uly + (dataset.RasterYSize * yres)


            # Make two arrays with the co-ords for each pixel
            XP = np.arange(ulx, lrx, xres, dtype=np.float64)
            YP = np.arange(uly, lry, yres, dtype=np.float64)            

            # Make an array the same shape as data populated with the X dimensions
            print('Building X dimensions...')
            Xarr = np.zeros_like(data)
            Xarr[...] = XP

            # Make an array the same shape as data populated with the Y dimensions
            print('Building Y dimensions...')
            Yarr = np.zeros_like(data)
            Yarr = Yarr.transpose()
            Yarr[...] = YP
            Yarr = Yarr.transpose()

            # Mask out the X and Y co-ords arrays based on presence of valid data
            print('Subsetting data...')
            SubXarr = Xarr[data > 0]
            SubYarr = Yarr[data > 0]
            SubData = data[data > 0]

            #Get the bounding co-ords based on presence of valid data
            # note yres is -ve
            print('Finding corner coords...')
            Xmin = np.amin(SubXarr)
            Xmax = np.amax(SubXarr) + abs(xres)
            Ymin = np.amin(SubYarr) - abs(yres)
            Ymax = np.amax(SubYarr)

            print(Xmin, Ymin)
            print(Xmax, Ymax)

            # Subset the input image based on the bounding co-ords
            outfile = os.path.join(outDir, file)
            print('Cropping Data to ' + str(outfile.split('/')[-1]))

            subprocess.call('gdalwarp -of GTiff -r cubic -tr ' + str(xres) + ' ' + str(yres) + ' -te ' + str(Xmin) + ' ' + str(Ymin) + ' ' + str(Xmax) + ' ' + str(Ymax) + ' -tr ' + str(xres) + ' ' + str(yres) + ' ' + str(file) + ' ' + str(outfile),shell=True)

        except Exception as e:
            print(e)
            print('Could not process: ', str(outfile.split('/')[-1]))

从空间图像中裁剪无数据

0 个答案: