Forests of Australia (2023)

Abstract Forests of Australia (2023) is a continental spatial dataset of forest extent, by national forest categories and types, assembled for Australia's State of the Forests Report. It was developed from multiple forest, vegetation and land cover data inputs, including contributions from Australian, state and territory government agencies and external sources. A forest is defined in this dataset as "An area, incorporating all living and non-living components, that is dominated by trees having usually a single stem and a mature or potentially mature stand height exceeding two metres and with existing or potential crown cover of overstorey strata about equal to or greater than 20 per cent. This includes Australia's diverse native forests and plantations, regardless of age. It is also sufficiently broad to encompass areas of trees that are sometimes described as woodlands". The dataset was compiled by the Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) for the National Forest Inventory (NFI), a collaborative partnership between the Australian and state and territory governments. The role of the NFI is to collate, integrate and communicate information on Australia's forests. State and territory government agencies collect forest data using independent methods and at varying scales or resolutions. The NFI applies a national classification to state and territory data to allow seamless integration of these datasets. Multiple independent sources of external data are used to fill data gaps and improve the quality of the final dataset. The NFI classifies forests into three national forest categories (Native Forest, Commercial plantation, and other forest) and then into various forest types. Commercial plantations presented in this dataset were sourced from the National Plantation Inventory (NPI) spatial dataset (2021), also produced by ABARES. Another dataset produced by ABARES, the Catchment scale land use of Australia CLUM dataset (2020), was used to identify and mask out land uses that are inappropriate to map as forest. The Forests of Australia (2023) dataset is produced to fulfil requirements of Australia's National Forest Policy Statement and the Regional Forests Agreement Act 2002 (Cwth) and is used by the Australian Government for domestic and international reporting. Previous versions of this dataset are available on the Forests Australia website spatial data page and the Australian Government open government data portal data.gov.au. Currency Date modified: 30 November 2023 Modification frequency: Every 5 years Data extent Spatial extent North: -8.2° South: -44.4° East: 157.2° West: 109.5° Source information Data, Metadata, Maps and Interactive views are available from ABARES website. Forests of Australia (2023) – Descriptive metadata. The data was obtained from Department of Agriculture, Fisheries and Forestry - Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES). ABARES is providing this data to the public under a Creative Commons Attribution 4.0 license. Lineage statement Presented on this page is a summarised lineage on the development of state and territory datasets for Forests of Australia (2023). The dataset has been produced using the Multiple Lines of Evidence (MLE) method for publication in the Australia’s State of the Forests Report – 2023 update. Detailed lineage information can be found here. Forests of Australia (2023) is a continental spatial dataset of forest extent, by national forest categories and types, assembled for Australia's State of the Forests Report – 2023 update. It was developed from multiple forest, vegetation and land cover data inputs, including contributions from Australian, state and territory government agencies and external sources. For each state or territory, except for the ACT where there was no new data, intersection of the Forests of Australia (2018) dataset with a forest cover dataset supplied by the jurisdiction, and with other available and appropriate independent forest cover datasets, identified: High confidence areas – areas where all the examined datasets agreed with the Forests of Australia (2018) dataset that the areas were forest or non-forest. No further assessment was required for these areas. Moderate confidence areas – areas where the Forests of Australia (2018) dataset agreed with the forest cover dataset supplied by state or territory, and with external or independent datasets, that the areas were forest or non-forest. These areas were identified as potential errors and needed further analysis in order to determine the correct allocation (forest or non-forest). The required analyses and validation were conducted by ABARES, in consultation with relevant state and territory agencies, using various ancillary data including high-resolution imagery such as World Imagery by ESRI, Bing Maps and Google Earth Pro. Low confidence areas – areas where the Forests of Australia (2018) dataset disagreed with the forest cover dataset supplied by state or territory, and with external or independent datasets, that the areas were forest or non-forest. All such areas were identified as potential errors and needed further analysis in order to determine the correct allocation (forest or non-forest). The required analyses and validation were conducted by ABARES, in consultation with relevant state and territory agencies, using various ancillary data including high-resolution imagery such as World Imagery by ESRI, Bing Maps and Google Earth Pro. External or independent datasets used include: H_Woody_Fuzzy_2_Class dataset is based on the NGGI dataset produced by DCCEEW from Landsat data and was developed to support New South Wales Natural Resources Commission’s (NRC) Monitoring, Evaluation and Reporting Program. NRC applied Fuzzy Logic and Probability modelling to the NGGI dataset to derive annual layers distinguishing between forest and non-forest at 25 m raster resolution. Each of five annual layers, 2015 to 2019, was resampled to a 100 m raster by classifying as forest the 100 m pixels that had more than half their area as forest as determined from 25 m pixels. The five annual layers were combined and every pixel in the combination that had been classified as forest in any year during 2015-2019 period was allocated as forest (and the balance non-forest). This approach was taken to prevent areas where the crown cover had reduced temporarily below 20%, through events such as fire, harvesting, drought or disease, from being incorrectly classified as non-forest. State-wide Land and Tree Study (SLATS) dataset is based on data collected by the Landsat satellite. This dataset was available for Queensland only. Foliage Projective Cover (FPC) values of 11 or greater (equivalent to crown cover 20% or greater) were considered as forest candidates in this SLATS dataset. The National Vegetation Information System (NVIS) version 6.0 dataset was used to identify areas in this SLATS dataset that met the height requirements of the forest definition used by the National Forest Inventory. The National Greenhouse Gas Inventory (NGGI) dataset is produced from Landsat satellite Thematic Mapper™, Enhanced Thematic Mapper Plus (ETM+) and Operational Land Image (OLI) images for the Australian Government Department of the Climate Change, Energy, the Environment and Water (DCCEEW), and identifies woody vegetation of height or potential height greater than 2 metres, crown cover greater than 20%, and with a minimum patch size of 0.2 hectares (DISER, 2021a) . The dataset is compiled using time-series data since 1972 and is produced at a 25 m × 25 m resolution. The NGGI dataset used was developed from the five annual layers (2016-2020, inclusive) from the ‘National Forest and sparse woody vegetation data (Version 5.0) spatial dataset produced using the algorithms for land-use change allocation developed for the National Inventory Reports (DISER, 2021b). Each layer of the original 25 m resolution, three-class (forest, sparse woody and non-forest) dataset was resampled to a binary (forest and non-forest) 100 m raster by classifying as forest the 100 m pixels that had more than half their area as forest; the sparse woody and non-forest classes were combined into a non-forest class. The five annual layers were then combined and every pixel in the combination that had been classified as forest in any year during 2016-2020 period was allocated as forest (and the balance non-forest). This approach was taken to prevent areas where the crown cover had reduced temporarily below 20%, through events such as fire, harvesting, drought or disease, from being incorrectly classified as non-forest. All input datasets were converted to 100m rasters (ESRI GRID format), aligning with relevant standard NFI state or territory masks (also known as NFI SNAP grids), in Albers projection. Where the input dataset was in polygon format, the Polygon to Raster tool was used to convert the polygon dataset to raster format, using the Maximum_Combined_Area option. Validation assessment results were incorporated to give improved and high-confidence forest cover datasets for each state or territory. Look-up tables translating the state or territory forest cover data to NFI forest types were used where provided. Where this information was not provided, it was derived by ABARES from translating Levels 5 and 6 of the National Vegetation Information System (NVIS) version 6.0 attribute information to NFI forest types. This dataset has been converted from GeoTIFF to Multidimensional Cloud Raster Format (CRF) to facilitate publishing to the Digital Atlas of Australia (DAA). Date of extraction: February 2024. Data dictionary Attribute name Description VALUE Identifier of every unique combination of the following attributes: STATE, FOR_SOURCE, FOR_CODE, FOR_TYPE, FOR_CAT, HEIGHT and COVER. COUNT Number of cells that belong to a particular VALUE. For this dataset, in which cell resolution is 100 by 100 metres. The COUNT value is equivalent to area in hectares. FOR_CATEGO NFI forest category description. Valid values are: Non- Forest; Native Forest; Commercial plantation and Other forest. FOR_TYPE NFI forest type name – broad name defined by dominant species and formation or structure. FOR_CODE Code linking the NFI forest type name (FOR_TYPE) to a COVER class and HEIGHT class. Each unique combination of the three attributes gives a forest formation value. See metadata document for all possible values. COVER_CODE Code linking an NFI forest type to a crown cover class. The Cover Code table below describes each code and value. HT_CODE Code linking an NFI forest type to a height category. The Height Code table below describes each code and value. FOREST Binary field where: Value of 0 indicates non-forest and Value 1 indicates forest. STATE State or territory in which the cell occurs. FOR_SOURCE Information about the source of the data for decision on: - whether to classify as forest or non-forest - NFI forest type - whether land use is appropriate for forest allocation See table Forest Source below for explanation of values available or used in the dataset. Red, Green, Blue RGB values for classification colours HT_CODE Height Code Forest height class (metres) Description 1 2–10 Low 2 >10–30 Medium 3 >30 Tall 4 n/a Plantation 5 >=2 Unknown 6 Non Forest COVER_CODE Cover Code Forest crown cover Description 1 20–50% Woodland 2 >50–80% Open 3 >80% Closed 4 n/a Plantation 5 >=20% Unknown 6 <20% Non Forest FOR_SOURCE Forest Source Description BLANK non-forest CLUM Areas not suitable to be mapped as forest owing to their land use type as determined from the Catchment scale land use of Australia (CLUM) dataset (2020). Examples of such land use areas include cropping, horticulture, irrigation, residential, industrial and utilities. Aus_For18 Areas determined by the Multiple Lines of Evidence method to be forest and the Forests of Australia (2018) dataset was used to allocate NFI forest types NT_CLUM Areas of sandalwood in Northern Territory as determined from the Land Use Mapping Project of the Northern Territory, 2016 - 2022 (LUMP). Global Mangroves Areas determined by the Multiple Lines of Evidence method to be forest and forest type was determined from the Global Mangrove Watch (2018) dataset. NPI spatial Commercial plantation forest areas identified by the National Plantation Inventory (2021) spatial dataset. NVIS 6.0 Areas determined by the Multiple Lines of Evidence method to be forest and the National Vegetation Information System 6.0 dataset (Level 5, Level 6, MVG and MVS attributes) was used to allocate NFI forest types. Tas Forest Comms Areas determined by the Multiple Lines of Evidence method to be forest and the Tasmania Forest Communities with NVIS Groups 2020 dataset was used to allocated NFI forest types Contact Department of Agriculture, Fisheries and Forestry (ABARES), [e-mail]