Adam Symington
Dr. Adam Symington is a geospatial data scientist, currently working for Synmax. Adam has published a book on geospatial data visualisation, “PythonMaps, Geospatial Visualization with Python” and runs the PythonMaps project, a project designed to spread the love of geospatial data through eye-catching visualisation. Prior to his career in data science Adam was a computational materials scientist at the University of Bath in England where he used machine learning and other statistical techniques to predict the properties of materials. During Adams time in academia, he taught Python programming, developed a Python programming course and published open source software.
Sessions
The rapid expansion of the geospatial industry and accompanying increase in availability of geospatial data, presents unique opportunities and challenges in data science. As the need for skilled data scientists increases, the ability to manipulate and interpret this data becomes crucial. This workshop introduces the essentials of geospatial data manipulation and data visualisation, emphasizing hands-on techniques to transform, analyze and visualise diverse datasets effectively.
Throughout the workshop, attendees will explore the extensive ecosystem of geospatial Python libraries. Key tools include GeoPandas, Shapely and Cartopy for vector data, GDAL, Rasterio and rioxarray for raster data and participants will also learn to integrate these with popular plotting libraries such as Matplotlib, Bokeh, and Plotly for visualizations.
This tutorial will cover three primary topics: visualizing geospatial shapes, managing raster datasets, and synthesizing multiple data types into unified visual representations. Each section will incorporate data manipulation exercises to ensure attendees not only visualize but also deeply understand geospatial data.
Targeting both beginners and advanced practitioners, the workshop will employ real-world examples to guide participants through the necessary steps to produce striking and informative geospatial visualizations. By the end, attendees will be equipped with the knowledge to leverage advanced data science techniques in their geospatial projects, making them proficient in both the analysis and communication of spatial information.