我已经能够使用matplotlib绘制和显示光栅图像。那部分是成功的。我所坚持的部分是能够以某种方式挽救那个情节。对于rasterio,我找到了两个有用的教程:
https://rasterio.readthedocs.io/en/latest/topics/windowed-rw.html
以及
我得到了一个名为NDVI的函数的calculate,通过matplotlib,我可以用下面的代码以我想要的方式显示它。但当我把文件另存为GeoTIFF时,桌面上的图像全黑了。我计划重新投影数据,我已经把代码注释掉了。在
这是我的代码:
import rasterio
import matplotlib.pyplot as plt
import numpy as np
nirband = r"LC08_L1TP_015033_20170822_20170912_01_T1_B5.TIF"
redband =r"LC08_L1TP_015033_20170822_20170912_01_T1_B4.TIF"
#rasterio.windows.Window(col_off, row_off, width, height)
window = rasterio.windows.Window(2000,2000,800,600)
with rasterio.open(nirband) as src:
subset = src.read(1, window=window)
fig, ax = plt.subplots(figsize=(12,6))
plt.imshow(subset)
plt.title(f'Band 5 Subset')
with rasterio.open(nirband) as src:
nir = src.read(1, window=window)
with rasterio.open(redband) as src:
red = src.read(1, window=window)
red = red.astype(float)
nir = nir.astype(float)
np.seterr(divide='ignore', invalid='ignore')
ndvi = np.empty(nir.shape, dtype=rasterio.float32)
check = np.logical_or ( red > 0, nir > 0 )
naip_ndvi = np.where ( check, (1.0*(nir - red )) / (1.0*( nir + red )),-2 )
fig, ax = plt.subplots(figsize=(12,6))
ndvi = ax.imshow(naip_ndvi)
ax.set(title="NDVI")
with rasterio.open("LC08_L1TP_015033_20170822_20170912_01_T1_B5.TIF") as src:
naip_data_ras = src.read()
naip_meta = src.profile
with rasterio.open('MyExample.tif', 'w',**naip_meta) as dst:
dst.write(naip_ndvi, window=window)
# =============================================================================
# with rasterio.open('example.tif') as dataset:
#
# # Read the dataset's valid data mask as a ndarray.
# mask = dataset.dataset_mask()
#
# # Extract feature shapes and values from the array.
# for geom, val in rasterio.features.shapes(
# mask, transform=dataset.transform):
#
# # Transform shapes from the dataset's own coordinate
# # reference system to CRS84 (EPSG:4326).
# geom = rasterio.warp.transform_geom(
# dataset.crs, 'EPSG:4326', geom, precision=6)
#
# # Print GeoJSON shapes to stdout.
# print(geom)
# =============================================================================
下面是我使用matplotlib时NDVI的样子(我想将其作为GeoTIFF文件保存到桌面上):
谢谢你的帮助!在
如何查看输出图像?在图像查看器中,或在GIS或遥感软件中,可以为文件添加对比度拉伸?NDVI值从-1到1-可能值的范围太小,您的软件无法自动显示。我最近在修改PlanetScope图像时也遇到了类似的问题——它使用matplotlib显示出来,但tiff显示为黑色。在
您可以尝试通过将单元格值乘以100来缩放输出-这可能有助于解决显示问题。您还可以使用可以对图像应用对比度拉伸的软件(QGIS、esri产品、ImageJ或图像处理软件)验证输出图像值
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