I am a Geospatial Data Scientist with a passion for devleoping elegant solutions to complex problems. I work within the Data Science team at SAEON uLwazi Node where we build tools and decision support systems for Societal Benefit. This allows me to facilitate the integration of science into policy and planning, allowing decisions to be driven by best available data. I am currently the project manager and lead analyst on the BioEnergy Atlas Project, a department of Science and Innovation funded project to assess the techno-economic feasibility for Bioenergy production in South Africa.

Accepted Talks:

Developing Feasible Scenarios for bioenergy production in South Africa with Python

BioEnergy has been a hot topic for some time, however there are a lot of unknowns regarding costs of Sourcing and Processing Biomass, that prevent its wider adoption. The team behind the BioEnergy Atlas for South Africa have developed a methodology and toolset that address a number of these unknowns, allowing for modeled scenarios for bioenergy production to be developed and compared.

This talk show cases how complex and computationally intensive spatial problems can be broken down into relatively simple components that are solvable using scientific compute methodologies and libraries in python.

The components of the modelling process discussed in this talk include: 1. Creation of a transport network where no roads exist using scikit-image 2. Geolocation of optimal potential facility locations based on the road transport costs and BioEnergy feedstock spatial location using GDAL and NetworkX 3. Calculation of BioEnergy Production costs per potential facility location (Pandas) 4. Presentation of Model Outputs using dashboards that facilitate Nexus type comparisons (Dash and Plotly)