（初学笔记1）python读多波段遥感影像并存到三维数组中

新手的python学习笔记1

自己合成的23波段的影像，研究半天怎么弄到三维数组里面去，也是在网上找了很多篇大佬的代码，拼拼补补。啊啊啊啊啊我好笨:(

代码部分：

import numpy as np
#import matplotlib as mpl
#import matplotlib.pyplot as plt
import gdal
#import cv2
import os


#读文件
def image_read(imagepath, bandnum):
    image = gdal.Open(imagepath)             # 打开该图像
    if image == None:
        print(imagepath + "该影像不能打开!")
        return
    lie = image.RasterXSize                # 栅格矩阵的列数
    hang = image.RasterYSize               # 栅格矩阵的行数
    im_bands = image.RasterCount           # 波段数
    im_proj = image.GetProjection()        # 获取投影信息
    im_geotrans = image.GetGeoTransform()  # 仿射矩阵
    print('该tif:{}个行，{}个列，{}层波段, 取出第{}层波段.'.format(hang, lie, im_bands, bandnum))
    band = image.GetRasterBand(bandnum)          # Get the information of band num.
    band_array = band.ReadAsArray(0,0,lie,hang)  # Getting data from zeroth rows and 0 columns
    # band_df = pd.DataFrame(band_array)
    del image  # 减少冗余
    return band_array #, im_proj, im_geotrans


#读到三维数组中
def read_in_array(image_path, nband):
    aa = image_read(image_path, 1)
    bb = image_read(image_path, 2)
    aa = np.array([aa,bb])
    for n in range(3,nband+1):
        bb = image_read(image_path, n)
        cc = np.append(aa,bb)                    #先拼接成一个行向量
        dim = aa.shape                           #获取原矩阵的维数
        print('原矩阵维数：',dim)
        aa = cc.reshape(dim[0]+1,dim[1],dim[2])  #再通过原矩阵的维数重新组合
        print('维数：',aa.shape)
    return aa

 
#文件目录
dir_path = r"E:\filter\little\NDVI"                #路径名
image_name = "NDVI_test_2011"                      #文件名
image_path = os.path.join(dir_path, image_name)
out_array = read_in_array(image_path, 23)          #波段是1-23

显示结果：