Title

Fuel Treatment Units - Murray Goldfields 

Alternate title

BLD_FTU_MGF 

Purpose

For burn planning. 

Credit

Gerard Buggy 

Credit

Jason Scheepers 

Supplemental Information

Update 20250415: Risk analysis data added (District Risk Reduction and Assets (houses) Saved scores). Separate Workcentre field added for ease of use. Duplicate Fuel Treatment names resolved temporarily by adding 'a' to the end of one of each of the duplicate values. Update 20250509: - Some FTUs amalgamated; new FTU names generated to resolved duplicates; new FIREFMZ for Castlemaine applied where 50% or more coverage; - FTU grades applied: A = 6, B = 5, C = 1; - FIREFMZ for remainder of district applied where 50% or more coverage ('Notes' column shows exceptions where there was no FIREFMZ value that covered => 50%). To score, APZ = 6, BMZ = 4, LMZ = 1; - Residual Risk scores split into quartiles and applied to each FTU, with 1st quartile being assigned, 1, 2nd quartile 2, and so on - where there was less than 80% coverage of any particular RR value for an FTU but the quartile score was consistent across the FTU, “0” was placed in the RR_Score field and the appropriate value in the RR_Quartile field. When no RR score reached 80% coverage of an FTU then a ‘0’ was placed in both fields; - Overall Fuel Hazard scores applied: where an OFH did not have a clear 80% coverage, field is null; - Overall risk score tallied in 'Total' field; - Fire History applied (LASTBURNT): if burn took place 5 years or less ago, notation is “N”; if > 5 years, notation is “Y”. Column is titled “Fire_MoreThan5” Update 20250619 & 20250620: minor geometry edits. Update 20250703: joined a multipart polygon (CASBU542862) and updated FIREFMZ information. 

Code

4283 

Maintenance and update frequency

As needed  

Title

File geodatabase. Vector. 1 

DELWP Categories

Use limitation

Departmental Use Only 

Classification

Limited Distribution  

Description

Collection Method: GPS 

Classification

Unclassified  

Attribute Quality

Positional Accuracy

Conceptual Consistency

Missing Data

Excess Data