因此，我正在Arcgis的Arcpy工具箱中工作，该工具箱将DEM栅格文件纳入特定处理。 但是我需要裁剪这些图像，因为原始图像太大且处理时间太长。 但是事实是，Arcgis裁剪工具更改了我无法使用的数据类型。
我开始寻找执行此操作的代码，并且GDAL librairy似乎可以帮助用shapefile剪切geotiff。这是我遵循一些小的更改以适应我的1通道DEM的代码：<https://pcjericks.github.io/py-gdalogr-cookbook/raster_layers.html>
from osgeo import gdal, gdalnumeric, ogr, osr
from PIL import Image, ImageDraw
gdal.UseExceptions()
# This function will convert the rasterized clipper shapefile
# to a mask for use within GDAL.
def imageToArray(i):
"""
Converts a Python Imaging Library array to a
gdalnumeric image.
"""
a=gdalnumeric.fromstring(i.tostring(),'b')
a.shape=i.im.size[1], i.im.size[0]
return a
def arrayToImage(a):
"""
Converts a gdalnumeric array to a
Python Imaging Library Image.
"""
i=Image.fromstring('L',(a.shape[1],a.shape[0]),
(a.astype('b')).tostring())
return i
def world2Pixel(geoMatrix, x, y):
"""
Uses a gdal geomatrix (gdal.GetGeoTransform()) to calculate
the pixel location of a geospatial coordinate
"""
ulX = geoMatrix[0]
ulY = geoMatrix[3]
xDist = geoMatrix[1]
yDist = geoMatrix[5]
rtnX = geoMatrix[2]
rtnY = geoMatrix[4]
pixel = int((x - ulX) / xDist)
line = int((ulY - y) / xDist)
return (pixel, line)
#
# EDIT: this is basically an overloaded
# version of the gdal_array.OpenArray passing in xoff, yoff explicitly
# so we can pass these params off to CopyDatasetInfo
#
def OpenArray( array, prototype_ds = None, xoff=0, yoff=0 ):
ds = gdal.Open( gdalnumeric.GetArrayFilename(array) )
if ds is not None and prototype_ds is not None:
if type(prototype_ds).__name__ == 'str':
prototype_ds = gdal.Open( prototype_ds )
if prototype_ds is not None:
gdalnumeric.CopyDatasetInfo( prototype_ds, ds, xoff=xoff, yoff=yoff )
return ds
def histogram(a, bins=range(0,256)):
"""
Histogram function for multi-dimensional array.
a = array
bins = range of numbers to match
"""
fa = a.flat
n = gdalnumeric.searchsorted(gdalnumeric.sort(fa), bins)
n = gdalnumeric.concatenate([n, [len(fa)]])
hist = n[1:]-n[:-1]
return hist
def stretch(a):
"""
Performs a histogram stretch on a gdalnumeric array image.
"""
hist = histogram(a)
im = arrayToImage(a)
lut = []
for b in range(0, len(hist), 256):
# step size
step = reduce(operator.add, hist[b:b+256]) / 255
# create equalization lookup table
n = 0
for i in range(256):
lut.append(n / step)
n = n + hist[i+b]
im = im.point(lut)
return imageToArray(im)
def main( shapefile_path, raster_path ):
# Load the source data as a gdalnumeric array
srcArray = gdalnumeric.LoadFile(raster_path)
# Also load as a gdal image to get geotransform
# (world file) info
srcImage = gdal.Open(raster_path)
geoTrans = srcImage.GetGeoTransform()
# Create an OGR layer from a boundary shapefile
shapef = ogr.Open("%s.shp" % shapefile_path)
lyr = shapef.GetLayer( os.path.split( os.path.splitext( shapefile_path )[0] )[1] )
poly = lyr.GetNextFeature()
# Convert the layer extent to image pixel coordinates
minX, maxX, minY, maxY = lyr.GetExtent()
ulX, ulY = world2Pixel(geoTrans, minX, maxY)
lrX, lrY = world2Pixel(geoTrans, maxX, minY)
# Calculate the pixel size of the new image
pxWidth = int(lrX - ulX)
pxHeight = int(lrY - ulY)
clip = srcArray[ulY:lrY, ulX:lrX]
#
# EDIT: create pixel offset to pass to new image Projection info
#
xoffset = ulX
yoffset = ulY
print "Xoffset, Yoffset = ( %f, %f )" % ( xoffset, yoffset )
# Create a new geomatrix for the image
geoTrans = list(geoTrans)
geoTrans[0] = minX
geoTrans[3] = maxY
# Map points to pixels for drawing the
# boundary on a blank 8-bit,
# black and white, mask image.
points = []
pixels = []
geom = poly.GetGeometryRef()
pts = geom.GetGeometryRef(0)
for p in range(pts.GetPointCount()):
points.append((pts.GetX(p), pts.GetY(p)))
for p in points:
pixels.append(world2Pixel(geoTrans, p[0], p[1]))
rasterPoly = Image.new("L", (pxWidth, pxHeight), 1)
rasterize = ImageDraw.Draw(rasterPoly)
rasterize.polygon(pixels, 0)
mask = imageToArray(rasterPoly)
# Clip the image using the mask
clip = gdalnumeric.choose(mask, \
(clip, 0)).astype(gdalnumeric.uint8)
clip[:,:] = stretch(clip[:,:])
# Save new tiff
#
# EDIT: instead of SaveArray, let's break all the
# SaveArray steps out more explicity so
# we can overwrite the offset of the destination
# raster
#
### the old way using SaveArray
#
# gdalnumeric.SaveArray(clip, "OUTPUT.tif", format="GTiff", prototype=raster_path)
#
###
#
gtiffDriver = gdal.GetDriverByName( 'GTiff' )
if gtiffDriver is None:
raise ValueError("Can't find GeoTiff Driver")
gtiffDriver.CreateCopy( "OUTPUT.tif",
OpenArray( clip, prototype_ds=raster_path, xoff=xoffset, yoff=yoffset )
)
# Save as an 8-bit jpeg for an easy, quick preview
clip = clip.astype(gdalnumeric.uint8)
gdalnumeric.SaveArray(clip, "OUTPUT.jpg", format="JPEG")
gdal.ErrorReset()
if __name__ == '__main__':
main( "shapefile", "DEM.tiff" )
但是我遇到了“形状不匹配ValueError”：
<ipython-input-22-32e4e8197a02> in main(shapefile_path, raster_path, region_shapefile_path)
166
167 # Clip the image using the mask
--> 168 clip = gdalnumeric.choose(mask, (clip, 0)).astype(gdalnumeric.uint8)
169
/home/edgar/anaconda3/envs/gis2/lib/python2.7/site-packages/numpy/core/fromnumeric.pyc in choose(a, choices, out, mode)
399
400 """
--> 401 return _wrapfunc(a, 'choose', choices, out=out, mode=mode)
402
403
/home/edgar/anaconda3/envs/gis2/lib/python2.7/site-packages/numpy/core/fromnumeric.pyc in _wrapfunc(obj, method, *args, **kwds)
49 def _wrapfunc(obj, method, *args, **kwds):
50 try:
---> 51 return getattr(obj, method)(*args, **kwds)
52
53 # An AttributeError occurs if the object does not have
ValueError: shape mismatch: objects cannot be broadcast to a single shape
我试图查看代码的来源，我意识到这部分可能无法正常工作：
minX, maxX, minY, maxY = lyr.GetExtent()
ulX, ulY = world2Pixel(geoTrans, minX, maxY)
lrX, lrY = world2Pixel(geoTrans, maxX, minY)
print("ulX, lrX, ulY, lrY : " , ulX, lrX, ulY, lrY) #image pixel coordinates of the shapefile
print(srcArray.shape) #shape of the raster image
clip = srcArray[ ulY:lrY, ulX:lrX] #extracting the shapefile zone from the raster image?
print(clip)
并返回：
('ulX, lrX, ulY, lrY : ', 35487, 37121, 3844, 5399)
(5041, 5041)
[]
似乎这些索引已达到极限（但是奇怪的是python并没有那么麻烦），并且没有任何内容被复制。 因此，我尝试使用与总栅格图像相对应的shapefile来更改代码，以获取与要提取的区域相对应的“真实”像素值：
#shapefile corresponding to the whole raster image
region_shapef = ogr.Open("%s.shp" % region_shapefile_path)
region_lyr = region_shapef.GetLayer( os.path.split( os.path.splitext( region_shapefile_path )[0] )[1] )
RminX, RmaxX, RminY, RmaxY = region_lyr.GetExtent()
RulX, RulY = world2Pixel(geoTrans, RminX, RmaxY)
RlrX, RlrY = world2Pixel(geoTrans, RmaxX, RminY)
#linear regression to find the equivalent pixel values of the clipping zone
pX = float(srcArray.shape[1])/(RlrX - RulX)
X0 = -(RulX*pX)
pY = float(srcArray.shape[0])/(RlrY - RulY)
Y0 = -(RulY*pY)
idXi = int(ulX*pX+X0)
idXf = int(lrX*pX+X0)
idYi = int(ulY*pY+Y0)
idYf = int(lrY*pY+Y0)
clip = srcArray[idYi:idYf, idXi:idXf]
print(clip)
返回一个真正提取值的数组：
[[169.4 171.3 173.7 ... 735.6 732.8 729.7]
[173.3 176.4 179.9 ... 734.3 731.5 728.7]
[177.8 182. 186.5 ... 733.1 730.3 727.5]
...
[ 73.3 77.5 83. ... 577.4 584.9 598.1]
[ 72.8 76.5 81.5 ... 583.1 593. 606.2]
[ 71.3 74.7 79. ... 588.9 599.1 612.3]]
尽管我还有那个该死的东西：
<ipython-input-1-d7714555354e> in main(shapefile_path, raster_path, region_shapefile_path)
170
171 # Clip the image using the mask
--> 172 clip = gdalnumeric.choose(mask, (clip, 0)).astype(gdalnumeric.uint8)
173
174 # This image has 3 bands so we stretch each one to make them
/home/edgar/anaconda3/envs/gis2/lib/python2.7/site-packages/numpy/core/fromnumeric.pyc in choose(a, choices, out, mode)
399
400 """
--> 401 return _wrapfunc(a, 'choose', choices, out=out, mode=mode)
402
403
/home/edgar/anaconda3/envs/gis2/lib/python2.7/site-packages/numpy/core/fromnumeric.pyc in _wrapfunc(obj, method, *args, **kwds)
49 def _wrapfunc(obj, method, *args, **kwds):
50 try:
---> 51 return getattr(obj, method)(*args, **kwds)
52
53 # An AttributeError occurs if the object does not have
ValueError: shape mismatch: objects cannot be broadcast to a single shape
我是否缺少或误解了一些东西？我真的开始缺乏想法，因此，如果有人有想法请，将不胜感激。
否则，如果您知道另一种无需更改即可裁剪我的DEM的方法，我也很好。
答案 0 :(得分：1)
您可以使用gdal.Warp（）和shapefile作为剪切线以更简单的方式实现
from osgeo import gdal
input_raster = "path/to/yourDEM.tif"
# or as an alternative if the input is already a gdal raster object you can use that gdal object
input_raster=gdal.Open("path/to/yourDEM.tif")
input_shape = "path/to/yourShapefile.shp" # or any other format
output_raster="path/to/outputDEM.tif" #your output raster file
ds = gdal.Warp(output_raster,
input_raster,
format = 'GTiff',
cutlineDSName = input_shape, # or any other file format
cutlineWhere="FIELD = 'whatever'" # optionally you can filter your cutline (shapefile) based on attribute values
dstNodata = -9999) # select the no data value you like
ds=None #do other stuff with ds object, it is your cropped dataset. in this case we only close the dataset.