Raster handling with Python and GDAL

Web Reference: In computer graphics and digital photography, a raster graphic, raster image, or simply raster is a digital image made up of a rectangular grid of tiny colored (usually square) so-called pixels. A raster graphic is made up of a collection of tiny, uniformly sized pixels, which are arranged in a two-dimensional grid made up of columns and rows. Each pixel contains one or more bits of information, depending on the degree of detail in the image. In its simplest form, a raster consists of a matrix of cells (or pixels) organized into rows and columns (or a grid) where each cell contains a value representing information, such as temperature.

YouTube Excerpt: Read, create, and modify geospatial raster (grid) data sets with GDAL in Python and materials provided at https://hydro-informatics.com/jupyter/geo-raster.html The jupyter notebooks can be git-cloned (or zip-downloaded) from the course repository: https://github.com/hydro-informatics/jupyter-python-course.git This tutorial uses the jupyter notebook named geo02-raster.ipynb in the course repository. The flusstools documentatin is available at https://flusstools.readthedocs.io with installation guidance from https://hydro-informatics.com/python-basics/pyinstall.html The RiverArchitect sample data is available at https://github.com/RiverArchitect/SampleData/tree/master/01_Conditions/2100_sample Lecturer: Sebastian Schwindt -- Contents of this video -- 00:02:29 - Load a raster dataset (open_raster) 00:05:03 - Working with flusstool 00:08:00 - Raster band statistics and color tables (standalone scripts) 00:14:08 - GDAL drivers and data types 00:15:10 - Create and save a raster (create_raster) 00:24:06 - Raster calculous (map algebra) 00:30:03 - Reproject (geotransform) a raster 00:43:03 - Zonal statistics (rasterstats) 00:46:13 - Clip a raster 00:48:01 - Slope and aspect rasters with subprocess gdal shell commands 00:49:41 - Least cost path (wrap-up) 00:51:13 - skimage (scikit-image) and route_through_array

Read, create, and modify geospatial raster (grid) data sets with GDAL in Python and materials provided at...

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