Contacts

Identifiers and Keywords

ANZLIC Id

ANZVI0803008638 

Jurisdiction

Victoria 

Topic category

• Environment
• Biota
• Farming
• Transportation

Resource Constraints

Use limitation

None. 

Classification

Unclassified  

Creative Commons Attribution 4.0 (CC-BY)

• 
• License Text

Other Dataset Details

Date ( Revision )

2022-02-18

Status

Completed  

Purpose

The primary purpose of this data to provide rapid and comprehensive landscape-scale spatial information about bushfire severity to inform initial risk assessments on the public land in the actual and potential impact zone. This assists with the transition from response to emergency stabilisation and initial recovery in accordance with the Code of Practice for Bushfire Management on Public Land (2012). Further reading on the approach used can be found in the article The Utility of Random Forests for wildfire severity mapping, link to resource: https://www.sciencedirect.com/science/article/abs/pii/S0034425718303328?via%3Dihub 

Format

GeoTiff 23 

Supplemental Information

Related Documents: None 

Maintenance and update frequency

Irregular  

Spatial

Spatial representation type

Grid  

Description

General - Victoria 

N

S

E

W

Temporal

Begin date

2020-01-01 

End date

2020-01-01 

Quality

Missing Data

A six-class fire severity classification across 1.8 million hectares of predominately forested public land in east and north east Victoria and southern New South Wales, Australia. The classification covers three main areas: East Gippsland (comprising the Snowy and Tambo complex fires, start date: 21/11/2019, end date: 13/03/2020; extent (WGS84): N: -36.929, S: -37.814, E: 150.033, W: 147.417) Ovens-Alpine (comprising the Ovens 41 - Abbeyard - Yarrarabula South Fires and the western part of the Alpine complex fires, start date: 30/12/2019, end date: 26/01/2020; extent (WGS84): N -36.627, S: -37.332, E: 147.565, W: 147.565) Upper Murray-Alpine (comprising the Upper Murray 26 - Upper Murray - Walwa and the north eastern part of the Alpine complex fires, start date: 19/12/2019, end date: 14/02/2020; extent (WGS84): -N: 35.782, S: -36.901, E: 148.2632, W: 147.4582) Completeness Verification: An independent ground-based validation of the data has not been undertaken. An accuracy assessment of the classification model has been performed (see Classification) using independent cross validation approach to estimate model accuracy. Twelve wildfires occuring inacross Central and Eastern Victoria were used for the cross validation. Cross validation involved holding out one fire for model validation and using the remaining fires to train the Random Forest. The Random Forest model was then used to predict fire severity for the validation fire. This process was repeated until validation had been undertaken for each fire. Metrics of model performance were then calculated using the independent predictions and observed fire severity 

Excess Data

Classification was undertaken using a Random Forest model that was trained using data from 12 wildfires occuring in the 2018/19 season across Central and Eastern Victoria. Classes are defined below together with [Estimated producer accuracy %]. Producer accuracy is estimated through cross-validation of the classification model described in https://www.sciencedirect.com/science/article/abs/pii/S0034425718303328?via%3Dihub Estimated global accuracy is 85% (0.81 Kappa) Class 0. No Data (e.g. due to obscuration of satellite imagery due to cloud, cloud-shadow and/or smoke and haze) 1. Non-woody vegetation (unclassified). 2. Unburnt - UB (Canopy and understorey foliage are largely (>90%) unburnt) [88%] 3. Low canopy scorch - LCS (Canopy foliage is largely unaffected (<20% scorched), but the understorey has been burnt) [75%] 4. Medium canopy scorch - MCS (Canopy is a mosaic of both unburnt and scorched foliage, 20 - 80%) [61%] 5. High canopy scorch - HCS (>80% of canopy foliage is scorched) [91%] 6. Canopy burnt - CB (> 20% canopy foliage consumed) [97%] 

Attribute Quality

Classes are defined below together with [Estimated producer accuracy %]. Producer accuracy is estimated through cross-validation of the classification model described in https://www.sciencedirect.com/science/article/abs/pii/S0034425718303328?via%3Dihub Estimated global accuracy is 85% (0.81 Kappa) Class 0. No Data (e.g. due to obscuration of satellite imagery due to cloud, cloud-shadow and/or smoke and haze) 1. Non-woody vegetation (unclassified). 2. Unburnt - UB (Canopy and understorey foliage are largely (>90%) unburnt) [88%] 3. Low canopy scorch - LCS (Canopy foliage is largely unaffected (<20% scorched), but the understorey has been burnt) [75%] 4. Medium canopy scorch - MCS (Canopy is a mosaic of both unburnt and scorched foliage, 20 - 80%) [61%] 5. High canopy scorch - HCS (>80% of canopy foliage is scorched) [91%] 6. Canopy burnt - CB (> 20% canopy foliage consumed) [97%] 

Positional Accuracy

https://earth.esa.int/web/sentinel/technical-guides/sentinel-2-msi/performance 

Lineage

Statement

Dataset Source: Sentinel 2, https://sentinel.esa.int/web/sentinel/missions/sentinel-2 Dataset Originality: Primary 

About the Metadata Record

Metadata identifier

urn:uuid / 7b4e8b68-7803-5844-8b12-4edda539cb4d