FMQF Features on Crown Land

dataset: FORMER_MINING_FEATURES_CROWN
The Former Mines and Quarries Project (2022 to 2025) created a process to extract data from many WOVG datasets in order to collate all these features into an inventory. of Mining and Quarrying Features such as Mine Shafts or Quarries. It includes a considerable number of new features collected from LIDAR analysis. Feeder Datasets include: ABANDONED_MINES ACTIVE_CONTAM FMQF FMQF_LIDAR FOI_POINT FOI_POLYGON HERITAGE_INVENTORY HERITAGE_REGISTER HIST100_POINT MINERALS.MINSITE MULLOCK100_POLYGON RECWEB_HISTORIC_RELIC MINERALS.SHAFT The following link provides all documentation behind the database that was used to create this dataset: https://earthresources.efirst.com.au/product.asp?pID=1353&cID=71 For further information email fmqf@deeca.vic.gov.au
 
Citation proposal Citation proposal
(2025)

FMQF Features on Crown Land

Department of Energy, Environment and Climate Action
 

Description

Title
FMQF Features on Crown Land 
Alternate title
FORMER_MINING_FEATURES_CROWN 
Resource Type
Dataset  
Purpose
To meet the obligations of the 2019 VAGO report to consolidate information into a single database. 
Credit
ResourcesVic 
Credit
Parks Victoria 
Credit
Department of Energy, Environment and Climate Action 
Status
Completed  
 
 

Temporal

Time period
1851-01-012025-02-03 
 
 

Spatial

Spatial representation type
Vector  
Horizontal Accuracy
25m  
Code
Geographicals on GDA94 
 

 

Maintenance

Maintenance and update frequency
Irregular  
 
 

Format

Title
ESRI Fgdb 
 
 

Contacts

  Point of contact

Cited responsible party  

No information provided.

Cited responsible party  

No information provided.
 
 

Keywords

Topic category
  • Environment
DELWP Categories
  • Minerals & Petroleum
 
 

Resource Constraints

Use limitation
<a href=&#09; https://creativecommons.org/licenses/by/4.0/&#09;>Creative Commons Attribution 4.0 International</a> 
Classification
Unclassified  
 
 

Lineage

Statement
As per the abstract 
 
 

Metadata Constraints

Use limitation
Unknown 
Classification
Unclassified  
 
 

Quality

Attribute Quality
Comments
Good 
Positional Accuracy
Comments
Varies from 5m to 250m 
Conceptual Consistency
Missing Data
Comments
Missing data outside of major mining areas and outside of recent LIDAR project areas. 
Excess Data
 
 

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