Python实现3D地图可视化：GDAL与Matplotlib实战

from osgeo import gdal
import cv2
gdal.UseExceptions()

ds = gdal.Open('E:/Pythoncode/读取地理信息/无标题.tif')
bandg = ds.GetRasterBand(1)
elevationg = bandg.ReadAsArray()

bandr = ds.GetRasterBand(2)
elevationr = bandr.ReadAsArray()

bandb = ds.GetRasterBand(3)
elevationb = bandb.ReadAsArray()

import matplotlib.pyplot as plt
nrows, ncols = elevationr.shape

elevation= cv2.merge([elevationg,elevationr,elevationb])#
# I'm making the assumption that the image isn't rotated/skewed/etc. 
# This is not the correct method in general, but let's ignore that for now
# If dxdy or dydx aren't 0, then this will be incorrect
x0, dx, dxdy, y0, dydx, dy = ds.GetGeoTransform()

x1 = x0 + dx * ncols
y1 = y0 + dy * nrows

plt.imshow(elevation, cmap='gist_earth', extent=[x0, x1, y1, y0])
plt.show()

from PIL import Image
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
fig = plt.figure()
ax = Axes3D(fig)

img = Image.open('E:/Pythoncode/读取地理信息/无标题.tif')
xx=[]
yy=[]
colall=[]
x = img.size[0]
y = img.size[1]
for i in range(x):
 for j in range(y):
 
 r = hex(img.getpixel((i, j))[0])[2:]
 b = hex(img.getpixel((i, j))[1])[2:]
 g = hex(img.getpixel((i, j))[2])[2:]
 
 if len(r) == 1:
 r = '0' + r
 if len(b) == 1:
 b = '0' + b
 if len(g) == 1:
 g = '0' + g
 col = '#' + r + b + g
 colall.append(col)
 xx.append(x0 + dx * i)
 yy.append(y0 + dy * j)
 # col = '#FF00FF'
ax.scatter(xx, yy, 5, c=colall, alpha=0.5)
plt.show()