TERN Geospatial Catalogue
Woody Extent and Foliage Projective Cover - Spot, OEH algorithm, NSW
This dataset contains maps of woody vegetation extent and woody foliage projective cover (FPC) for New South Wales at 5 metre resolution. <br /><br />
Woody vegetation is a key feature of our landscape and an integral part of our society. We value it because it contributes to the economy, protects the land, provides us with recreation, and gives refuge to the unique and diverse range of fauna that we regard so highly. Yet it poses a significant threat to us in times of fire and storm. So information about trees is vital for a range of business, property planning, monitoring, risk assessment, and conservation activities. <br /><br />
The datasets are: <br />
Woody vegetation extent. A presence/absence map showing areas of trees and shrubs, taller than two metres, that are visible at the resolution of the imagery used in the analysis. This shows the location, extent, and density of foliage cover for stands of woody vegetation, enabling identification of small features such as trees in paddocks and scattered woodlands through to the largest expanses of forest in the State. Woody extent products contain 'bcu' in the file name.<br /><br />
Woody foliage projective cover (FPC). FPC is a measure of the proportion of the ground area covered by foliage (or photosynthetic tissue) held in a vertical plane and is a measure of canopy density. Woody FPC products contain 'bcv' in the file name. <br /><br />
Both mosaics and tiles are available, along with a shape file that identifies the location of the tiles.
Simple
Identification info
- Date (Creation)
- 2011-01-01
- Date (Publication)
- 2021-09-23
- Date (Revision)
- 2021-03-29
- Edition
- 1.0.0
Identifier
Publisher
Author
Office of Environment and Heritage (2011-2019), New South Wales - Broker, Data ()
320 Pitt St
Sydney
NSW
2000
Australia
- Website
- https://www.tern.org.au/
- Purpose
- What can the maps be used for? The maps are intended for use in rural landscapes and are suited to many applications including:<br /> - property planning<br /> - vegetation mask for topographic maps<br /> - local government planning<br /> - risk assessment, such as in fire-prone areas<br /> - native vegetation mapping<br /> - habitat identification and mapping
- Credit
- We owe a debt of gratitude to the numerous Science Division staff and volunteers who edited the maps. Thanks too, to the following organisations: Airbus Defence and Space for SPOT imagery data NSW Land and Property Information for ADS40 data NSW Land and Property Information and a number of commercial vendors for Lidar data Joint Remote Sensing Research Program
- Status
- Completed
Point of contact
Office of Environment and Heritage (2011-2019), New South Wales - Broker, Data ()
320 Pitt St
Sydney
NSW
2000
Australia
Spatial resolution
- Level of detail
- 1 meter - < 30 meters
- Topic category
-
- Environment
- Geoscientific information
- Farming
- Imagery base maps earth cover
Extent
N
S
E
W
))
Temporal extent
- Time period
- 2011-01-01 2011-12-31
- Keywords
- GCMD Earth Science and Earth Science Services Keywords
- Temporal Resolution
- ANZSRC Fields of Research
- Keywords
-
- trees
- Keywords (dataResolution)
Resource constraints
- Use limitation
- The Creative Commons Attribution 4.0 International (CC BY 4.0) license allows others to copy, distribute, display, and create derivative works provided that they credit the original source and any other nominated parties. Details are provided at https://creativecommons.org/licenses/by/4.0/
- File name
- 88x31.png
- File description
- CCBy Logo from creativecommons.org
- File type
- png
- Title
- Creative Commons Attribution 4.0 International Licence
- Alternate title
- CC-BY
- Edition
- 4.0
- Access constraints
- License
- Use constraints
- Other restrictions
- Other constraints
- TERN services are provided on an "as-is" and "as available" basis. Users use any TERN services at their discretion and risk. They will be solely responsible for any damage or loss whatsoever that results from such use including use of any data obtained through TERN and any analysis performed using the TERN infrastructure. <br/>Web links to and from external, third party websites should not be construed as implying any relationships with and/or endorsement of the external site or its content by TERN. <br /><br />Please advise any work or publications that use this data via the online form at https://www.tern.org.au/research-publications/#reporting
- Other constraints
- Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}.
Resource constraints
- Classification
- Unclassified
- Supplemental Information
- The coordinate reference systems for the files are NSW Lamberts Conformal Conic (mosaic). GDA94 MGA zones 54, 55, and 56 (tiles)
Distribution Information
Distributor
Distributor
- OnLine resource
-
Woody extent and foliage projective cover NSW
Woody extent and foliage projective cover NSW
Distribution Information
Distributor
Distributor
- OnLine resource
-
nswwoodyvegetationextentfpc2011factsheet1.pdf
Data file
Distribution Information
Distributor
Distributor
- OnLine resource
-
nswwoodyvegetationextentfpc2011factsheet2.pdf
Data file
Data quality info
- Hierarchy level
- Dataset
- Other
- OEH staff conducted two comparisons with independent observations of woody vegetation extent. The first comparison used fine-detailed maps of woody-vegetation extent derived from airborne Lidar surveys. The state-wide map of extent had an overall accuracy of 90.1%.<br /><br /> The second comparison used 6670 image-interpreted points of woody vegetation presence or absence. The points were gathered from images with 2.5 m pixels. The overall accuracy was 88%. The spatial variation in accuracy across the state, reported by Local Land Service region, is listed in the table below.<br /><br /> Care should be taken when interpreting the maps. Incorrect classification is most likely to occur where it is difficult to distinguish trees greater than two metres in height from other types of vegetation. Such vegetation includes sparse woodlands, low shrubs, chenopods, heath, wetlands, and irrigated pastures and crops. Also, woody vegetation is only detected about half of the time when the fol
Report
Result
- Statement
- <p>Accuracy assessment results are provided in the table below.</p> <table cellpadding="4"> <tbody> <tr> <th scope="col">Local Land<br />Service</th> <th scope="col">Points</th> <th scope="col">Lidar</th> <th scope="col">Local Land<br />Service</th> <th scope="col">Points</th> <th scope="col">Lidar</th> </tr> <tr> <td>North Coast</td> <td>95.8%</td> <td>93.6%</td> <td>Riverina</td> <td>89.0%</td> <td>93.0%</td> </tr> <tr> <td>Northern Tablelands</td> <td>91.8%</td> <td>89.0%</td> <td>Hunter</td> <td>88.7%</td> <td>85.3%</td> </tr> <tr> <td>South East</td> <td>91.6%</td> <td>94.5%</td> <td>North West</td> <td>88.3%</td> <td>89.0%</td> </tr> <tr> <td>Central Tablelands</td> <td>91.0%</td> <td>86.8%</td> <td>Murray</td> <td>84.8%</td> <td>90.3%</td> </tr> <tr> <td>Greater Sydney</td> <td>90.6%</td> <td>89.1%</td> <td>Western</td> <td>77.5%</td> <td>88.6%</td> </tr> <tr> <td>Central West</td> <td>89.8%</td> <td>88.3%</td> </tr> </tbody> </table>
Resource lineage
- Hierarchy level
- Dataset
Process step
- Description
- The source data was SPOT5 High Resolution Geometric (HRG) satellite imagery. It consists of 4 multispectral bands (10 m pixels), and a panchromatic band (2.5 m pixels). A time series of one image per year for the period 2008 to 2011 was acquired during dry periods where the contrast between woody vegetation and the ground cover is high. A total 1256 images were used. The images were registered with ground control. The multispectral imagery was corrected for atmospheric and bi-directional reflectance effects and sharpened to 5 m pixels using the panchromatic imagery. The images were masked for cloud, cloud shadow, topographic shadow, and water.
- Title
- Image Data
Process step
- Description
- An estimate of FPC was derived for every clear pixel in every image. This required a multiple linear regression model that related the multi-spectral reflectance to a reference data set of FPC. Each pixel contained up to 5 observations of FPC and reflectance over time. The probability of a pixel containing woody vegetation was determined using a binomial logistic regression model. The model parameters were the mean FPC, mean red reflectance, variation in FPC over time, and the climate variable vapour pressure deficit. The model was trained using 25930 observations of woody vegetation presence or absence. These points were interpreted from ADS40 aerial imagery where available (0.5 m pixels) and SPOT5 HRG panchromatic images (2.5 m pixels).
Process step
- Description
- Woody vegetation extent was mapped by applying a threshold to the probability images, with further editing by trained analysts. The mean FPC value over time was used to attribute each woody pixel.
- Title
- Mapping woody vegetation
Process step
- Description
- Two comparisons with independently-derived datasets of woody vegetation extent were performed as described in the Data Quality section.
- Title
- Accuracy assessment
Reference System Information
- Reference system identifier
- EPSG/WGS84 (EPSG:4326)
Metadata
- Metadata identifier
-
urn:uuid/5e2a56b2-45be-41da-b193-9157ff02bd49
- Title
- TERN GeoNetwork UUID
- Language
- English
- Character encoding
- UTF8
Point of contact
Type of resource
- Resource scope
- Dataset
- Metadata linkage
-
https://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/5e2a56b2-45be-41da-b193-9157ff02bd49
Point-of-truth metadata URL
- Date info (Creation)
- 2008-11-12T00:00:00
- Date info (Revision)
- 2014-06-27T11:07:36
Metadata standard
- Title
- ISO 19115-1:2014/AMD 1:2018 Geographic information - Metadata - Fundamentals
- Edition
- 1
Metadata standard
- Title
- ISO/TS 19115-3:2016
- Edition
- 1.0
Metadata standard
- Title
- ISO/TS 19157-2:2016
- Edition
- 1.0
- Title
- Terrestrial Ecosystem Research Network (TERN) Metadata Profile of ISO 19115-3:2016 and ISO 19157-2:2016
- Date (published)
- 2021
- Edition
- 1.0
Identifier
Overviews
Spatial extent
N
S
E
W
Provided by
Associated resources
Not available