How to use Open Source Image cutting in GIS Development

This article mainly introduces how to use open source image cutting in GIS development, the article is very detailed, has a certain reference value, interested friends must read it!

In the process of using image data, it is sometimes necessary to cut the image data according to a coordinate range. Commonly used tools such as arcmap can be used for image cutting. The following introduces a use of open source class library for image cutting, the development language is python.

The name of the open source library is: https://github.com/mapbox/rasterio rasterio,github is a specialized image processing library with a variety of image processing functions, as described on the website.

Let's briefly say that you can use rasterio to do a simple image data cutting.

Before development, prepare a basic image, a cutting image area vector data, here prepare a shp file, to ensure that the vector cutting data and image data coordinate system is consistent.

The specific python code is as follows:

Import fiona

Import rasterio

Import rasterio.mask

# fiona Open the shp file and install it using conda or pip

# Open a shp file as read-only

With fiona.open ("Vector File clipdata.shp", "r") as shapfile:

# cycle through the area coordinate information of the shp file

Features = [feature ["geometry"] for feature in shapfile]

# Open the path of the cut tif file

With rasterio.open ("tif file path L15.tif") as src:

# cut layers according to the coordinate range of the vector

Out_image,out_transform = rasterio.mask.mask (src,features

Crop=True)

# copy the data of the source tif

Out_meta = src.meta.copy ()

# update the replicated source tif data according to the cutting information

Out_meta.update ({"driver": "GTiff"

"height": out_image.shape [1]

"width": out_image.shape [2]

"transform": out_transform})

# Save tif to a new file and write it to disk

With rasterio.open ("Save path clip.tif", "w", * * out_meta) as dest:

Dest.write (out_image)

Cut image effect:

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