A proof of concept Python toolkit for effective landscape fuel hazard management
summary
A proof‑of‑concept Python toolkit automates a 16+ step manual risk workflow to rank hazard‑reduction burn units by acceptable/conditional/unacceptable risk, encodes ISO 31000 decisions, and logs metadata at every step. It links ArcGIS + Python 2.7 + pandas to read Excel, join fuel and strategic tables, and output maps. Tested on ~14,500 burn units across ~89,000 km² with an existing 5% annual burn target, runs scenarios in 10 seconds vs hours and is rolling out as a NSW pilot.
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chapters (20)
- 0:00Introduction
- 1:10Personal connection to bushfires
- 7:10Legal responsibility
- 8:35Best practices
- 12:00Risk classification
- 13:25Risk ranking
- 14:45Classification
- 16:10Python
- 18:05Human error
- 20:00Spatial data
- 22:10Data processing
- 23:30Output
- 23:45Proof of concept
- 24:10Current risks
- 25:25Baseline risks
- 25:50Key outputs
- 26:35Key takeaways
- 27:15Extending the toolkit
- 27:45NSW pilot project
- 28:10Questions
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