Master GDAL CLI

Overview

This course introduces practical, command-line workflows for preparing raster data for analysis and cloud deployment using GDAL. You will build foundational skills in inspecting raster metadata, making informed reprojection decisions, and optimizing elevation datasets for cloud-based access using Cloud-Optimized GeoTIFFs (COGs). Through guided explanations, hands-on labs, and scenario-based reflection activities, you will explore how projection choice, resolution, resampling methods, internal tiling, compression, and overviews affect raster accuracy and performance. The course emphasizes intentional decision-making rather than default command usage, helping learners understand not just how to run GDAL tools, but why specific options matter in real-world geospatial workflows. You are required to have basic familiarity with raster data concepts and comfort using a command-line interface. However, no prior GDAL experience is required. By the end of the course, you will be able to confidently inspect, reproject, optimize, and validate digital elevation models (DEMs) for reliable analytical use and efficient cloud deployment.

Syllabus

Understanding Raster Data with GDAL

Before modifying raster data, you need to understand what’s inside it. In this module, you will review why inspecting raster metadata is a critical first step in any geospatial workflow.

Reprojecting Raster Data with gdalwarp

Most raster datasets are delivered in projections that do not match your analysis or cloud requirements. Reprojection is a core GDAL skill you will use frequently. In this module, you will review how gdalwarp performs reprojection, resampling, and extent control for raster data.

Creating Cloud-Optimized GeoTIFFs

You will understand what truly makes a GeoTIFF cloud-optimized by focusing on how internal structure, tiling, and overviews affect performance and usability in cloud and web-based workflows.