我正在请求审核以下代码。我有一个空间参考图像和一个多边形。我编写了一个代码（见下文）来剪辑此图像以保存新图像（剪裁区域）。此功能基于要素类的几何图形剪切栅格。基于几何体的剪切意味着您将使用要素类中所有要素的边界来剪切栅格而不是这些要素的最小边界矩形
输入：多边形图层和一个或多个栅格图层 输出：新的栅格图层，剪裁为多边形边界
import osgeo.gdal
import shapefile
import struct, numpy, pylab
import numpy as np
import ogr
import osr,gdal
from shapely.geometry import Polygon
import osgeo.gdal as gdal
import sys
from osgeo import gdal, gdalnumeric, ogr, osr
import Image,ImageDraw
def world2Pixel(geoMatrix, x, y):
"""
Uses a gdal geomatrix (gdal.GetGeoTransform()) to calculate
the pixel location of a geospatial coordinate
(http://geospatialpython.com/2011/02/clip-raster-using-shapefile.html)
geoMatrix
[0] = top left x (x Origin)
[1] = w-e pixel resolution (pixel Width)
[2] = rotation, 0 if image is "north up"
[3] = top left y (y Origin)
[4] = rotation, 0 if image is "north up"
[5] = n-s pixel resolution (pixel Height)
"""
ulX = geoMatrix[0]
ulY = geoMatrix[3]
xDist = geoMatrix[1]
yDist = geoMatrix[5]
rtnX = geoMatrix[2]
rtnY = geoMatrix[4]
pixel = np.round((x - ulX) / xDist).astype(np.int)
line = np.round((ulY - y) / xDist).astype(np.int)
return (pixel, line)
def Pixel2world(geoMatrix, x, y):
ulX = geoMatrix[0]
ulY = geoMatrix[3]
xDist = geoMatrix[1]
yDist = geoMatrix[5]
coorX = (ulX + (x * xDist))
coorY = (ulY + (y * yDist))
return (coorX, coorY)
def RASTERClipByPolygon(inFile,poly,outFile):
# Open the image as a read only image
ds = osgeo.gdal.Open(inFile,gdal.GA_ReadOnly)
# Check the ds (=dataset) has been successfully open
# otherwise exit the script with an error message.
if ds is None:
raise SystemExit("The raster could not openned")
# Get image georeferencing information.
geoMatrix = ds.GetGeoTransform()
ulX = geoMatrix[0]
ulY = geoMatrix[3]
xDist = geoMatrix[1]
yDist = geoMatrix[5]
rtnX = geoMatrix[2]
rtnY = geoMatrix[4]
# get the WKT (= Well-known text)
dsWKT = ds.GetProjectionRef()
# get driver information
DriverName = ds.GetDriver().ShortName
# open shapefile (= border of are of interest)
shp = osgeo.ogr.Open(poly)
if len(shp.GetLayer()) != 1:
raise SystemExit('The shapefile must have exactly one layer')
# Create an OGR layer from a boundary shapefile
layer = shp.GetLayer(0)
feature = layer.GetNextFeature()
geometry = feature.GetGeometryRef()
# Make sure that it is a polygon
if geometry.GetGeometryType() != osgeo.ogr.wkbPolygon:
raise SystemExit('This module can only load polygon')
# get Extent of the clip area
X_min, X_max, Y_min, Y_max = layer.GetExtent()
# Convert the layer extent to image pixel coordinates
uldX, uldY = world2Pixel(geoMatrix, X_min, Y_max)
lrdX, lrdY = world2Pixel(geoMatrix, X_max, Y_min)
# Calculate the pixel size of the new image
pxWidth = int(lrdX - uldX)
pxHeight = int(lrdY - uldY)
# get the Coodinate of left-up vertex of the pixel
X_minPixel, Y_maxPixel = Pixel2world(geoMatrix, uldX, uldY)
# get polygon's vertices
pts = geometry.GetGeometryRef(0)
points = []
for p in range(pts.GetPointCount()):
points.append((pts.GetX(p), pts.GetY(p)))
pnts = np.array(points).transpose()
# work band by band
nBands = ds.RasterCount
# panchromatic
if nBands == 1:
band = ds.GetRasterBand(1)
# get nodata value
nodata = band.GetNoDataValue()
# convert band in Array
bandArray = band.ReadAsArray()
del band
# clip arrey
bandArray_Area = bandArray[uldY:lrdY, uldX:lrdX]
del bandArray
# Create 2D Polygon Mask. Mode 'L', not '1', because
# Numpy-1.5.0 / PIL-1.1.7 does not support the numpy.array(img)
# conversion nicely for bivalue images.
img = Image.new('L', (pxWidth, pxHeight), 0)
target_ds = gdal.GetDriverByName(DriverName).Create(outFile, pxWidth, pxHeight, nBands, ds.GetRasterBand(1).DataType)
target_ds.SetGeoTransform((X_minPixel, xDist, rtnX,Y_maxPixel, rtnY, yDist))
pixels, line = world2Pixel(target_ds.GetGeoTransform(),pnts[0],pnts[1])
listdata = [(pixels[i],line[i]) for i in xrange(len(pixels))]
ImageDraw.Draw(img).polygon(listdata, outline=1, fill=1)
mask = numpy.array(img)
bandArray_Masked = bandArray_Area*mask
del bandArray_Area, mask
target_ds.GetRasterBand(nBands).WriteArray(bandArray_Masked)
target_ds.GetRasterBand(nBands).SetNoDataValue(nodata)
else:
img = Image.new('L', (pxWidth, pxHeight), 0)
target_ds = gdal.GetDriverByName(DriverName).Create(outFile, pxWidth, pxHeight, nBands, ds.GetRasterBand(1).DataType)
target_ds.SetGeoTransform((X_min, xDist, rtnX,Y_max, rtnY, yDist))
pixels, line = world2Pixel(target_ds.GetGeoTransform(),pnts[0],pnts[1])
listdata = [(pixels[i],line[i]) for i in xrange(len(pixels))]
ImageDraw.Draw(img).polygon(listdata, outline=1, fill=1)
mask = numpy.array(img)
for bandno in range(1, nBands+1):
band = ds.GetRasterBand(bandno)
nodata = band.GetNoDataValue()
# convert band in Array
bandArray = band.ReadAsArray()
del band
# clip arrey
bandArray_Area = bandArray[ulY:lrY, ulX:lrX]
del bandArray
bandArray_Masked = bandArray_Area*mask
target_ds.GetRasterBand(bandno).WriteArray(bandArray_Masked)
del bandArray_Area
target_ds.GetRasterBand(bandno).SetNoDataValue(nodata)
# set the reference info
if len(dsWKT) is 0:
# Source has no projection (needs GDAL >= 1.7.0 to work)
target_ds.SetProjection('LOCAL_CS["arbitrary"]')
else:
# Make the target raster have the same projection as the source
target_ds.SetProjection(dsWKT)
target_ds = None
答案 0 :(得分：3)
这可以在R中轻松完成。我刚刚意识到问题是针对python的。因此我做了编辑。有包装可用于在R中的python或python中运行R，请检查包rpy2。
## Read the shapefile
myshp <- shapefile("shapefile.shp")
## Reading the raster you want to crop
myraster <- raster('image.tif')
## create a layer only for the shape, the parameter inverse = TRUE or FALSE is imp
new_raster = mask(myraster, myshp, filename = "newras.tif", inverse = FALSE)
希望这会有所帮助。