From the course: Geospatial Raster Data Analytics in Python
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Resampling raster data - Python Tutorial
From the course: Geospatial Raster Data Analytics in Python
Resampling raster data
- [Instructor] Resampling raster data is a widely used method to reduce file size, volume, and complexity. This simplification approach is also useful when we are merging multiple raster files with different spatial resolutions. In this example, we will match the spatial resolutions of the previously reprojected Germany level population and elevation rasters. First, we import the usual rasterio and NumPy libraries, along with the resampling method of rasterio. Additionally, to ensure CRS level compatibility, we will use the previously introduced reproject method as well. Here, I will only import the new libraries. Now let's specify the previously created input files, which are going to be the reprojected elevation and population maps of Germany. Here, now I just copy and paste it from the previous notebook. Then to figure out what we are dealing with, let's compare the resolution of these two raster files. For that, we will have to open both files and print the resolution attributes…
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Prepare real-world raster data3m 35s
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Elevation raster data4m 48s
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Reprojecting raster data8m 57s
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Resampling raster data6m 20s
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Create multiband raster data4m 16s
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Applying simple functions on raster data: Part 13m 48s
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Applying simple functions on raster data: Part 23m 57s
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Applying simple functions on raster data: Part 34m 33s
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Applying complex functions on raster data4m 55s
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