Geospatial Raster Data Analytics in Python [Repost]

Looking for a comprehensive overview of raster data analytics in Python? An ideal fit for data scientists and geospatial practitioners, this course is designed to help you get started using vector data and various tools in Python, such as GeoPandas and Shapely.

Instructor Milan Janosov covers the basics, from creating synthetic raster data to collecting, visualizing, and modifying existing real-world raster data. Along the way, get hands-on practical experience exploring raster data both statistically and visually. By the end of this course, you’ll be equipped with in-demand skills for resampling and reprojecting raster data, combining single-band raster data into multiband raster data, conducting advanced analytics on multiband raster data, and more.

Learning objectives

• Accurately describe the characteristics of raster data and differentiate it from other geospatial data types.
• Acquire, read, and visualize raster data from various sources, including population and elevation data, using appropriate software and tools.
• Perform basic data exploration techniques, including histogram analysis and log scaling, and interpret the results to enhance data visualization.
• Manipulate raster data by successfully performing operations on data sets such as clipping, resampling, and reprojecting.
• Combine multiple single-band raster files into a multiband raster file, conduct analytical exercises on the resulting data, and interpret the outcomes.