Geospatial Raster Data Analytics in Python
1h 59mAdvanced2025-01-08
Authors
Milan Janosov, Ph.D.
Course details
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.
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.
Skills covered
GISPythonData AnalysisAECProgramming LanguagesData ScienceBusiness Analysis and StrategyBusiness Software and ToolsOpen SourceSoftware DevelopmentOne-Off
Concepts
Introduction
- Why raster analytics
The Context of Geospatial Data
- Brief recap on geospatial data and analytics
- Overview of raster data
- Data acquisition
The Basics of Raster Data
- Creating dummy raster data
- Spatial referencing and saving raster data
- Reading and characterizing raster data
- Visualizing single- and multi-band raster data
Raster Data Exploration
- Read and characterize real-world raster data
- Clip real-world raster data with vector data
- Visualize real-world raster data
- Zonal statistics on raster data
Advanced Analysis
- Prepare real-world raster data
- Elevation raster data
- Reprojecting raster data
- Resampling raster data
- Create multiband raster data
- Applying simple functions on raster data - Part 1
- Applying simple functions on raster data - Part 2
- Applying simple functions on raster data - Part 3
- Applying complex functions on raster data
Continuing Your Raster Analytics Learning Journey
- Continuing on with raster data