Workshop Title: Introduction to GDAL for Spatial Data Science (No Programming Experience Required!)

Workshop Description:

This hands-on workshop is designed for new users and non-programmers who want to explore the power of GDAL (Geospatial Data Abstraction Library) for spatial data science. GDAL is a robust open-source library used to read, write, manipulate, and convert geospatial data in various formats. Whether you're dealing with raster or vector data, GDAL provides a wide array of tools to handle geospatial tasks efficiently and consistently.

In this session, we'll walk through the core features and capabilities of GDAL, focusing on the most common operations you’ll need when working with geospatial datasets. The workshop will be beginner-friendly, using the GDAL Python package in a notebook environment to streamline workflows. Participants will use Google Colab to ensure uniformity across different operating systems and avoid the complexities of local software installation. By the end of the session, you'll feel confident in using GDAL to handle spatial data without needing advanced coding knowledge.

Key Features and Capabilities of GDAL:

Data format conversion: Easily convert between dozens of geospatial formats (e.g., GeoTIFF, Shapefile, KML, JSON, etc.).
Raster data manipulation: Perform clipping, warping, re-projection, resampling, and pixel value analysis.
Vector data operations: Simplify, buffer, and re-project vector layers or convert between vector formats.
Spatial reference management: Handle projections and coordinate system transformations with ease.
Metadata handling: Read and write metadata to spatial files.
GDAL utilities: Learn to use common GDAL command-line utilities directly within Python.

GDAL 101: The Geospatial Data Abstraction Library (Oct. 30th, 2024)