Developing Feasible Scenarios for bioenergy production in South Africa with Python
Speaker: Hayden Wilson
Track: Data Science
Room: Video Stream 1
Time: Oct 07 (Thu): 14:30
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)