在Python中用GDAL实现矢量对栅格的切割实例-创新互联
概述:
成都创新互联是一家集网站建设,克拉玛依区企业网站建设,克拉玛依区品牌网站建设,网站定制,克拉玛依区网站建设报价,网络营销,网络优化,克拉玛依区网站推广为一体的创新建站企业,帮助传统企业提升企业形象加强企业竞争力。可充分满足这一群体相比中小企业更为丰富、高端、多元的互联网需求。同时我们时刻保持专业、时尚、前沿,时刻以成就客户成长自我,坚持不断学习、思考、沉淀、净化自己,让我们为更多的企业打造出实用型网站。本文讲述如何在Python中用GDAL实现根据输入矢量边界对栅格数据的裁剪。
效果:
裁剪前
矢量边界
裁剪后
实现代码:
# -*- coding: utf-8 -*- """ @author lzugis @date 2017-06-02 @brief 利用shp裁剪影像 """ from osgeo import gdal, gdalnumeric, ogr from PIL import Image, ImageDraw import os import operator 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.tobytes(),'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.frombytes('L',(a.shape[1],a.shape[0]), (a.astype('b')).tobytes()) 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] 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(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) # This image has 3 bands so we stretch each one to make them # visually brighter for i in range(3): clip[i,:,:] = stretch(clip[i,:,:]) # 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( "beijing.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, "beijing.jpg", format="JPEG") gdal.ErrorReset() if __name__ == '__main__': #shapefile_path, raster_path shapefile_path = 'beijing.shp' raster_path = 'world.tif' main( shapefile_path, raster_path )
新闻标题:在Python中用GDAL实现矢量对栅格的切割实例-创新互联
当前网址:http://cdiso.cn/article/dcgsei.html