Using python library Rasterio to create a subset of a TIFF image and then display it and save it?
I have two Raster images, one from band 4 with a B4 at the end and another from band 5 with B5 at the end. I want to subset the B5 raster to 800x600, then display it and save it as a GeoTiff. Then I want to compute the NDVI (I assume I'll need both the B4 and B5 to do this, but not sure). Then I want to display the NDVI subset of the B5 raster. Display it and save it as a GeoTiff.
How would I create something like a 800 x 600 pixel subset of a TIFF raster image? I want to also take that TIFF and generate an NDVI image for that subset.
NOTE: I am working with a Landsat image. The image has B5 at the end of the file title.
What I've done so far:
import rasterio
from rasterio.windows import Window
import matplotlib.pyplot plt # for later use
with rasterio.open('MyRasterImage.tif') as src:
w = src.read(1, window=Window(0, 0, 800, 600))
I want to display this using Spyder or Jupyter notebooks. So I thought to use matplotlib and did the flowing code:
# Plot
plt.imshow(w)
plt.show()
Doing this generates a 800x600 matplotlib window, but it's all purple, not sure why its producing this.
Now I want to be able to display this 800x600 image. Then after that I want preform an NDVI on that subset 800x600 image. Then display the subset 800x600 image with NDVI showing.
I know the formuala is: NDVI = (NIR - red) / (NIR + red)
But how do I extract out NIR and red here from this single Landsat image?
My attempt at that:
band1 = dataset.read(1)
band2 = dataset.read(2)
band3 = dataset.read(3)
print(band[2])
When I run that code for the bands I get the error:
rasterio indexerror: band index 2 out of range (not in (1,))
When I run this code:
print(w.count)
It returns '1'.
So this means that the Landsat image only has one band? But in order to do NDVI don't I need 3 bands?
I am thinking of writing some code like this to get the NDVI from that raster. But not sure how to go about extracting out the bands:
# We handle the connections with "with"
with rasterio.open(bands[0]) as src:
b3 = src.read(1)
with rasterio.open(bands[1]) as src:
b4 = src.read(1)
# Allow division by zero
numpy.seterr(divide='ignore', invalid='ignore')
# Calculate NDVI
ndvi = (b4.astype(float) - b3.astype(float)) / (b4 + b3)
This code doesn't work because bands isn't define as anything so I don't know how to define bands to get the NDVI.
After this I am not sure how to go about both displaying and saving the rendered image.
python rasterio
asked Nov 18 '18 at 16:16
yuen2yuen2
194
add a comment |
I have two Raster images, one from band 4 with a B4 at the end and another from band 5 with B5 at the end. I want to subset the B5 raster to 800x600, then display it and save it as a GeoTiff. Then I want to compute the NDVI (I assume I'll need both the B4 and B5 to do this, but not sure). Then I want to display the NDVI subset of the B5 raster. Display it and save it as a GeoTiff.
How would I create something like a 800 x 600 pixel subset of a TIFF raster image? I want to also take that TIFF and generate an NDVI image for that subset.
NOTE: I am working with a Landsat image. The image has B5 at the end of the file title.
What I've done so far:
import rasterio
from rasterio.windows import Window
import matplotlib.pyplot plt # for later use
with rasterio.open('MyRasterImage.tif') as src:
w = src.read(1, window=Window(0, 0, 800, 600))
I want to display this using Spyder or Jupyter notebooks. So I thought to use matplotlib and did the flowing code:
# Plot
plt.imshow(w)
plt.show()
Doing this generates a 800x600 matplotlib window, but it's all purple, not sure why its producing this.
Now I want to be able to display this 800x600 image. Then after that I want preform an NDVI on that subset 800x600 image. Then display the subset 800x600 image with NDVI showing.
I know the formuala is: NDVI = (NIR - red) / (NIR + red)
But how do I extract out NIR and red here from this single Landsat image?
My attempt at that:
band1 = dataset.read(1)
band2 = dataset.read(2)
band3 = dataset.read(3)
print(band[2])
When I run that code for the bands I get the error:
rasterio indexerror: band index 2 out of range (not in (1,))
When I run this code:
print(w.count)
It returns '1'.
So this means that the Landsat image only has one band? But in order to do NDVI don't I need 3 bands?
I am thinking of writing some code like this to get the NDVI from that raster. But not sure how to go about extracting out the bands:
# We handle the connections with "with"
with rasterio.open(bands[0]) as src:
b3 = src.read(1)
with rasterio.open(bands[1]) as src:
b4 = src.read(1)
# Allow division by zero
numpy.seterr(divide='ignore', invalid='ignore')
# Calculate NDVI
ndvi = (b4.astype(float) - b3.astype(float)) / (b4 + b3)
This code doesn't work because bands isn't define as anything so I don't know how to define bands to get the NDVI.
After this I am not sure how to go about both displaying and saving the rendered image.
python rasterio
asked Nov 18 '18 at 16:16
yuen2yuen2
194
add a comment |
I have two Raster images, one from band 4 with a B4 at the end and another from band 5 with B5 at the end. I want to subset the B5 raster to 800x600, then display it and save it as a GeoTiff. Then I want to compute the NDVI (I assume I'll need both the B4 and B5 to do this, but not sure). Then I want to display the NDVI subset of the B5 raster. Display it and save it as a GeoTiff.
How would I create something like a 800 x 600 pixel subset of a TIFF raster image? I want to also take that TIFF and generate an NDVI image for that subset.
NOTE: I am working with a Landsat image. The image has B5 at the end of the file title.
What I've done so far:
import rasterio
from rasterio.windows import Window
import matplotlib.pyplot plt # for later use
with rasterio.open('MyRasterImage.tif') as src:
w = src.read(1, window=Window(0, 0, 800, 600))
I want to display this using Spyder or Jupyter notebooks. So I thought to use matplotlib and did the flowing code:
# Plot
plt.imshow(w)
plt.show()
Doing this generates a 800x600 matplotlib window, but it's all purple, not sure why its producing this.
Now I want to be able to display this 800x600 image. Then after that I want preform an NDVI on that subset 800x600 image. Then display the subset 800x600 image with NDVI showing.
I know the formuala is: NDVI = (NIR - red) / (NIR + red)
But how do I extract out NIR and red here from this single Landsat image?
My attempt at that:
band1 = dataset.read(1)
band2 = dataset.read(2)
band3 = dataset.read(3)
print(band[2])
When I run that code for the bands I get the error:
rasterio indexerror: band index 2 out of range (not in (1,))
When I run this code:
print(w.count)
It returns '1'.
So this means that the Landsat image only has one band? But in order to do NDVI don't I need 3 bands?
I am thinking of writing some code like this to get the NDVI from that raster. But not sure how to go about extracting out the bands:
# We handle the connections with "with"
with rasterio.open(bands[0]) as src:
b3 = src.read(1)
with rasterio.open(bands[1]) as src:
b4 = src.read(1)
# Allow division by zero
numpy.seterr(divide='ignore', invalid='ignore')
# Calculate NDVI
ndvi = (b4.astype(float) - b3.astype(float)) / (b4 + b3)
This code doesn't work because bands isn't define as anything so I don't know how to define bands to get the NDVI.
After this I am not sure how to go about both displaying and saving the rendered image.
python rasterio
asked Nov 18 '18 at 16:16
yuen2yuen2
194
I have two Raster images, one from band 4 with a B4 at the end and another from band 5 with B5 at the end. I want to subset the B5 raster to 800x600, then display it and save it as a GeoTiff. Then I want to compute the NDVI (I assume I'll need both the B4 and B5 to do this, but not sure). Then I want to display the NDVI subset of the B5 raster. Display it and save it as a GeoTiff.
How would I create something like a 800 x 600 pixel subset of a TIFF raster image? I want to also take that TIFF and generate an NDVI image for that subset.
NOTE: I am working with a Landsat image. The image has B5 at the end of the file title.
What I've done so far:
import rasterio
from rasterio.windows import Window
import matplotlib.pyplot plt # for later use
with rasterio.open('MyRasterImage.tif') as src:
w = src.read(1, window=Window(0, 0, 800, 600))
I want to display this using Spyder or Jupyter notebooks. So I thought to use matplotlib and did the flowing code:
# Plot
plt.imshow(w)
plt.show()
Doing this generates a 800x600 matplotlib window, but it's all purple, not sure why its producing this.
Now I want to be able to display this 800x600 image. Then after that I want preform an NDVI on that subset 800x600 image. Then display the subset 800x600 image with NDVI showing.
I know the formuala is: NDVI = (NIR - red) / (NIR + red)
But how do I extract out NIR and red here from this single Landsat image?
My attempt at that:
band1 = dataset.read(1)
band2 = dataset.read(2)
band3 = dataset.read(3)
print(band[2])
When I run that code for the bands I get the error:
rasterio indexerror: band index 2 out of range (not in (1,))
When I run this code:
print(w.count)
It returns '1'.
So this means that the Landsat image only has one band? But in order to do NDVI don't I need 3 bands?
I am thinking of writing some code like this to get the NDVI from that raster. But not sure how to go about extracting out the bands:
# We handle the connections with "with"
with rasterio.open(bands[0]) as src:
b3 = src.read(1)
with rasterio.open(bands[1]) as src:
b4 = src.read(1)
# Allow division by zero
numpy.seterr(divide='ignore', invalid='ignore')
# Calculate NDVI
ndvi = (b4.astype(float) - b3.astype(float)) / (b4 + b3)
This code doesn't work because bands isn't define as anything so I don't know how to define bands to get the NDVI.
After this I am not sure how to go about both displaying and saving the rendered image.
python rasterio
python rasterio
asked Nov 18 '18 at 16:16
yuen2yuen2
194
asked Nov 18 '18 at 16:16
yuen2yuen2
194
edited Nov 18 '18 at 16:26
yuen2
asked Nov 18 '18 at 16:16
yuen2yuen2
194
asked Nov 18 '18 at 16:16
yuen2yuen2
194
asked Nov 18 '18 at 16:16
yuen2yuen2
194
194
add a comment |
add a comment |
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