From the course: Geospatial Raster Data Analytics in Python
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Prepare real-world raster data - Python Tutorial
From the course: Geospatial Raster Data Analytics in Python
Prepare real-world raster data
- Welcome to the last chapter of this course where we are going to combine everything that we have learned so far. Here we are going to work with multiple real life data sets and learn how to combine them, how to re-project them, how to re-sample them, how to create multiband raster data, and of course how to visualize all of this. Additionally, we will also learn how to conduct various computations and analytical steps on raster data. The goal of this last chapter is to equip you with all the necessary skills to dive into any real life raster data that you may come across. In this chapter, we are going to conduct a series of advanced analytical steps using Germany as an example. To be able to proceed with these analytical steps, first, we need to prepare the country level population grid for Germany. Hence, in this notebook we used the previously introduced techniques to first obtain the vector boundaries of Germany, and then to use that to crop the Euro level population lead…
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Contents
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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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