Mastering GDAL Tools

GDAL is an open-source library for raster and vector geospatial data formats. The library comes with a vast collection of utility programs that can perform many geoprocessing tasks and build scalable spatial ETL pipelines without the need for expensive software. This class introduces GDAL and OGR utilities with example workflows for processing satellite and aerial imagery.

Duration

8 Hours

Prerequisites

Learning Outcomes

  • Write commands to process large volumes of data
  • Effectively work with drone/aerial imagery
  • Automate satellite data processing
  • Build Extract-Transform-Load (ETL) pipelines

Course Outline

  • Introduction to GDAL/OGR Utilities
  • Raster Data Processing with GDAL Tools
    • Working with Elevation Data
    • Processing of Aerial Imagery
    • Processing Satellite Data
      • Merging individual bands into RGB composite
      • Apply Histogram Stretch and Color Correction
      • Pan Sharpening
      • Raster Algebra
    • Georeferencing
      • Georeferencing images with corner coordinates
      • Georeferencing with GCPs
    • Downloading WMS Layers
  • Vector Data Processing with OGR Tools
    • Working with CSV Files
    • Working with Virtual Files
    • Geoprocessing and Spatial Queries
  • Multi-Criteria Weighted Overlay Analysis
  • Running commands in batch

CERTIFICATION

Upon successful completion of all the live online sessions and the class assignments, participants will be issued an employer-verifiable certificate from Spatial Thoughts. Learn more.


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Meet Our Participants

Mastering GDAL Tools is one of the best courses I have received. Is incredible how powerful this command line tools are. After this course I was able to solve several problems in simple bash scripts and convert data easily. I was able to re-write several workflows like download and processing of GIS data that has taken me hundreds of lines in the python and setting several libraries, all with simple isolated bash scripts. The teaching methodology is great, with plenty of use cases and patience to explain. Highly recommended!

Norman Avila, Climaya, Guatemala.

Although I am working with GDAL already, this course is helping me reach the next level in my GDAL skills as I have learnt many other things in GDAL during this course. Ujaval is such an excellent teacher and the many examples he gives during the course makes the class interactions very lively and interesting.

Ellen Brock, Freelance data scientist, India.

Another great course delivered by Ujaval and Santhosh, I already have ideas of how to use this newfound knowledge in my work. Thank you for sharing your knowledge.

Steven Shepperson, MarineSpace, United Kingdom.

Till today, GDAL was more like a black-box for me. Thanks to this course from Spatial Thoughts, I now have a good insight on GDAL, especially the simplified methods of doing ETL on bulk datasets. Thanks Ujaval and Santhosh for all the support!

Gurudatta Kannambadi, Aaron GSD, India

This is world’s no. 1 course on GDAL. we learn things here that you wont find naywhere. i have been struggling with gdal for 5 years now. only after this course i am feeling more confident. if you have any wordly connections to GDAL then trust me you definitely should do this course.

Kaushik Roy, AI Engineer, Canada

I have some years of using GDAL in a basic way, now with this course, I feel that I have enhanced my skills, and I am sure that it will help me to have a better data workflow. The teachers are excellent, they have a great command of the subject and their examples are very clear.

Alexander Quevedo Chacón, Consultant, Mexico

The course offers a complete vision of GDAL / OGR that allows to know a wide range of possibilities in the raster and vector analysis, customizing and automating processes for multiple data formats.

Joan Bauzà, Geographer, Spain

Great course with very practical examples, Ujaval teaches it in an approachable way and is very thorough and kind in responding to even simple questions. It was extremely useful to be in the class, follow along step by step and hear about the reasoning behind each decision.

Pushkar Kopparla, Postdoctoral Fellow, University of Bern

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