The Queensland based data for the Australian Biomass for Bioenergy Assessment (ABBA).

ABBA provides detailed information about biomass resources across Australia. This information will assist in project development and decision making for new bioenergy projects, and provide linkages between biomass supply, through the supply chain, to the end user. To achieve this, the project collects, on a state by state basis, data on the location, volumes and availability of biomass, for inclusion on the Australian Renewable Energy Mapping Infrastructure (AREMI) platform.

For detailed information about how this data was derived download the technical methods documents.

These documents are a series of technical methods used to publish the Queensland based data for the Australian Biomass for Bioenergy Assessment (ABBA). ABBA provides detailed information about biomass resources across Australia. This information will assist in project development and decision making for new bioenergy projects, and provide linkages between biomass supply, through the supply chain, to the end user. To achieve this, the project will collect, on a state by state basis, data on the location, volumes and availability of biomass, for inclusion on the Australian Renewable Energy Mapping Infrastructure (AREMI) platform. To download the data visit the Queensland Data Portal.

The Queensland based data for the Australian Biomass for Bioenergy Assessment (ABBA). ABBA provides detailed information about biomass resources across Australia. This information will assist in project development and decision making for new bioenergy projects, and provide linkages between biomass supply, through the supply chain, to the end user. To achieve this, the project collects, on a state by state basis, data on the location, volumes and availability of biomass, for inclusion on the Australian Renewable Energy Mapping Infrastructure (AREMI) platform. For detailed information about how this data was derived download the technical methods documents.

Australia Fuel Supply: Queensland: Biomass data was reported at 0.000 MWh in 10 May 2025. This stayed constant from the previous number of 0.000 MWh for 03 May 2025. Australia Fuel Supply: Queensland: Biomass data is updated weekly, averaging 2,444.604 MWh from Oct 2021 (Median) to 10 May 2025, with 186 observations. The data reached an all-time high of 9,403.464 MWh in 19 Oct 2024 and a record low of 0.000 MWh in 10 May 2025. Australia Fuel Supply: Queensland: Biomass data remains active status in CEIC and is reported by Australian Energy Market Operator. The data is categorized under Global Database’s Australia – Table AU.RB020: Fuel Supply.

Standing above ground biomass (AGB) for the 1 hectare plot was calculated based on measurements taken in 2017. Measurements included the DBH (cm), height (m) and wood density (g/cm³) for stems ≥10 cm DBH. Estimates of AGB (kg) were based on the model 4 equation described in Chave et al. (2014): AGB = 0.0673 x (ρD²H) 0.976

In 2024, approximately *****thousand gigawatt hours of electricity from biomass energy in Australia were generated in the state of Queensland. This was followed by New South Wales, which produced around *****thousand gigawatt hours of biomass electricity.

Mangrove trees of six species were sampled in order to derive allometric relationships for estimating leaf biomass, branch biomass, stem biomass and total above-ground biomass from measurements of …Show full descriptionMangrove trees of six species were sampled in order to derive allometric relationships for estimating leaf biomass, branch biomass, stem biomass and total above-ground biomass from measurements of the diameter of the stem at breast height (DBH). Rhizophora apiculata, Rhizophora stylosa, Bruguiera gymnorhiza, Bruguiera parviflora, Ceriops tagal var. australis and Xylocarpus granatum were sampled from the mangrove forests of Hinchinbrook Island, the Murray River and the Daintree River in north Queensland between 1985 and 1988.

For each species, the diameters of stems of trees from a range of size-classes were measured. The trees were then felled and divided into leaves, branches, stem and above-ground roots. The fresh weight of each component was measured in the field and subsamples of each component were collected, weighed and taken to the laboratory for determination of dry weight. This research was undertaken to determine if allometric relationships existed between stem diameter at breast height (DBH) and above-ground biomass, which would enable reliable, non-destructive estimates of the biomass of mangrove trees. Reliable estimates of biomass combined with growth rates are required for estimates of primary productivity.

The Cape Tribulation Crane 1 ha rainforest plot at the Daintree Rainforest Observatory is situated on the lowlands in Far North Queensland, just south of Cape Tribulation. It is associated with the TERN FNQ Rainforest SuperSite. A vascular plant census were carried out in mid 2010. All data for stems ≥ 10cm DBH can be found in the DBH stem dataset. The data is being used as baseline data set to assist in tracking changes in biomass in the rainforest.

Mangrove trees of six species were sampled in order to derive allometric relationships for estimating leaf biomass, branch biomass, stem biomass and total above-ground biomass from measurements of the diameter of the stem at breast height (DBH). Rhizophora apiculata, Rhizophora stylosa, Bruguiera gymnorhiza, Bruguiera parviflora, Ceriops tagal var. australis and Xylocarpus granatum were sampled from the mangrove forests of Hinchinbrook Island, the Murray River and the Daintree River in north Queensland between 1985 and 1988.For each species, the diameters of stems of trees from a range of size-classes were measured. The trees were then felled and divided into leaves, branches, stem and above-ground roots. The fresh weight of each component was measured in the field and subsamples of each component were collected, weighed and taken to the laboratory for determination of dry weight. This research was undertaken to determine if allometric relationships existed between stem diameter at breast height (DBH) and above-ground biomass, which would enable reliable, non-destructive estimates of the biomass of mangrove trees. Reliable estimates of biomass combined with growth rates are required for estimates of primary productivity.

This Collection contains soil and vegetation observations and measurements analysed and published in the paper:

Bartley Rebecca, Abbott Brett N., Ghahramani Afshin, Ali Aram, Kerr Rod, Roth Christian H., Kinsey-Henderson Anne (2023), "Do regenerative grazing management practices improve vegetation and soil health in grazed rangelands? Preliminary insights from a space-for-time study in the Great Barrier Reef catchments, Australia", Rangelands Journal, https://doi.org/10.1071/RJ22047 Lineage: Refer to publication (https://doi.org/10.1071/RJ22047)

The Robson Creek 25 ha rainforest plot is situated on the Atherton Tablelands in Far North Queensland. It is part of the TERN FNQ Rainforest SuperSite. The following data is collected from the core hectare 6 within the 25 ha plot. LAI and photopoints are done at the end of each wet and dry season. The vascularplant survey and six gentry transects were done in 2012. Coarse woody debris is done each year. Data for stems > 10 cm DBH can be found in the dataset - Vascular Plant Data > 10 cm DBH, Far North Queensland Rainforest SuperSite, Robson Creek, 25 ha plot, 2009-2012.

The Robson Creek 25 ha rainforest plot is situated on the Atherton Tablelands in Far North Queensland. It is part of the TERN FNQ Rainforest SuperSite. The following data is collected from the core hectare 6 within the 25 ha plot. Coarse woody debris is done each year.

In November 1996, three sites were selected along Hinchinbrook Channel, which represented the major forest types and environmental range within the channel. Six plots, each usually 400 m² were marked out at each site and all trees were tagged, identified to species level and the diameter at breast height (DBH) was measured. The biomass of each tree was estimated using previously established allometric relationships between DBH and biomass. The two year time span of this project was insufficient to reliably measure biomass accumulation within these plots. Estimates were obtained from permanent plots in Missionary Bay, which had a 5 year record. Below ground biomass accumulation was calculated using the relationship between above-ground and below-ground biomass derived for Rhizophora apiculata in Malaysia.The forest canopy was accessed from steel towers, up to 10m in height, constructed in three forest stands with different species compositions. From top to bottom, a 2x1 m section of the canopy was divided into horizontal layers of 0.5 m thickness. Within each layer, in two of the stands, (a mixed stand of Bruguiera gymnorhiza/Rhizophora stylosa and a mixed stand of Rhizophora apiculata/Rhizophora stylosa), the angle of each leaf was measured and leaves removed to measure area and dry weight. The measurements taken were used in the simulation of canopy light profiles. In all plots, indirect estimates of canopy leaf area index were obtained from measurements of light flux density with a quantum sensor.Photosynthetic rates were determined for Bruguiera gymnorhiza, Bruguiera parviflora, Ceriops australis, Ceriops tagal, Rhizophora apiculata, Rhizophora lamarkii, Rhizophora stylosa, Heritiera littoralis and Xylocarpus granatum. Rates were measured on leaves at their natural angle of inclination at different levels in the canopy using a portable photosynthesis system. This research was undertaken to estimate net canopy carbon fixation and carbon accumulation as living biomass in mangrove forests using data on stand structure and rates of photosynthesis. This study is a component of a broader investigation of carbon fixation and storage by mangrove ecosystems.

This data was used to develop allometric equations for estimating belowground biomass. This file contains supplementary information for the manuscript "Species-specific allometric equations for predicting below-ground root biomass in plantations: case study of spotted gums (Corymbia citriodora subspecies variegata) in Queensland" with detailed description of the methods used and finding reported.

The effects of three different silvicultural treatments and an untreated control on AGB recovery dynamics based on 46-years of monitoring data in permanent forest plots located in tropical north Queensland, Australia. The underlying demographic processes driving biomass changes.

MSF Sugar Pty Ltd (MSF) is undertaking to build a biomass power plant in Queensland, Australia.The project involves the construction of a 24MW biomass power plant. It includes the construction of a cooling tower, a chimney, a substation, storage tanks, ash collector units and related infrastructure, and the installation of steam turbines and generators.FGF Developments has been appointed as civil contractor.In October 2016, ThyssenKrupp Industrial Solutions was awarded as construction contractor for the project.Early excavation work on the site commenced in November 2016.Construction activities on the project commenced in May 2017.Civil works have been completed in September 2017.Construction activities are underway with completion scheduled by July 2018. Read More

The Ground Cover Reference Sites Database of Queensland has been collected by Department of Environment and Science, Queensland as part of the Ground Cover Monitoring for Australia project. The data is being used to calibrate, validate and improve vegetation fractional cover products derived from remote sensing, in particular the satellite sensors MODIS and Landsat. The data is being used to improve the national fractional vegetation cover product of Guerschman et al. (2009) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). This algorithm enables national, monthly identification of ground cover separating the photosynthetic and non-photosynthetic components by applying a linear unmixing methodology for spectral reflectance every 8 days as 16-day composites. For confidence in its ground cover estimates, the results were verified in the field at selected sites across Australia to allow more extensive calibration, validation and verification of accuracy of the remote sensing method. The Ground Cover Reference Sites Database represents the results of the field validation of remotely determined cover measurements by observing cover along point intersects with a total of 300 points (or 200 points with crops). It also has additional observations and measures such as landscape features, fire evidence, erosion evidence, biotic disturbance evidence, biomass estimates, basal area measurements, soil features and dominant vegetation species, as well as site photographs. The Ground Cover Reference Sites Database focuses on sites in extensive grazing systems of the rangelands and, to a lesser extent, in the mixed farming or intensive land use zone. Field validation aims at obtaining a wide spatial coverage of sites, with limited site revisits for temporal coverage.

Measurement of variation in plant biomass is essential for answering many ecological and evolutionary questions. Quantitative estimates require plant destruction for laboratory analyses, while field studies use allometric approaches based on simple measurement of plant dimensions. We estimated the biomass of individual shrub-sized plants, using a low cost Unmanned Aerial System (drone), enabling rapid data collection and non-destructive sampling. We compared volume measurement (a surrogate for biomass) and sampling time, from the simple dimension measurements and drone, to accurate laboratory-derived biomass weights. We focused on three Australian plant species which are ecologically important to their floodplain and terrestrial ecosystems: porcupine grass Triodia scariosa, Queensland bluebush Chenopodium auricomum and lignum Duma florulenta. Estimated volume from the drone was more accurate than simple dimension measurements for porcupine grass and Queensland bluebush, compared to estimates from laboratory analyses but, not for lignum. The latter had a sparse canopy, with thin branches, few vestigial leaves and a similar colour to the ground. Data collection and analysis consistently required more time for the drone method than the simple dimension measurements, but this would improve with automation. Methods We estimated dry weight biomass by measuring volume with two field methods: a simple dimension measurement and a drone. Volume was not directly comparable between methods, as the drone method detected detailed structure, not simple dimensions, and so we harvested samples destructively to quantify dry weight biomass. We randomly stratified sampling using each size class and species’ combination, ensuring individuals (n=3) were under full sunlight and in good health, representative of most individuals in the field. For simple dimension measurements, we measured height from ground level to the tallest plant part and crown circumference, using the longest horizontal dimension of the plant and its perpendicular axis to produce a 3D octahedron. This allowed estimation of volume. We then surveyed each individual plant, using a DJI Phantom 3 professional drone (DJI, Shenzhen, China) with its standard mounted camera (12 megapixel (MP) camera, fixed lens and focal length, mounted with a stabilising unit). Ground control points of known dimensions were placed for each plant, to generate two perpendicular scale constraints, increasing the accuracy of the resulting point cloud. We flew a manually-navigated grid pattern at 10 m above ground and within 3 hours of solar midday to minimise shadows, using a combination of downwards (nadir) and angled (non-nadir) images, with at least 70% overlap of each image. Where plants were close together, multiple plants were surveyed in one flight. The elevation provided about 40 high resolution images (<1 mm ground sample distance) for each plant, recorded as red, green and blue (RGB) jpeg files in the visible spectrum. After collecting field measurements, we destructively sampled each plant for laboratory measurements of dry and wet biomass by harvesting all above ground plant matter. Plants were stored in plastic bags with moist paper towels for transport. Subsequently, wet weight biomass of each plant was measured (stems and leaves amalgamated) before drying it in an oven (70 oC for at least 72 hours), after which dry biomass was weighed. We used SfM (using Pix4Dmapper software, Pix4D SA, 2018) to generate a 3D model (point cloud) of each plant, allowing estimation of volume. Each plant point cloud was set with scale constraints from the ground control points to improve measurement precision. We manually selected each plant from point clouds using CloudCompare (V2.8.1, 2018), ensuring that nearby plants (e.g. grasses) were not included. We exported the point cloud for each plant into the R statistical software environment (R Core Team, 2018) and calculated the minimum convex hull of the plant using RLiDAR.

The Robson Creek 25 ha rainforest plot is situated on the Atherton Tablelands in Far North Queensland. It is part of the TERN FNQ rainforest supersite. This dataset is for stems ≥10cm diameter at breast height only for the entire 25 ha. Data is: Species name, DBH, POM, height, and geographic coordinates. Vegetation data for the supersite single core hectare 6 is located in the database – Vascular Plant Data, Far North Queensland Rainforest Supersite, Robson Creek, Core 1 ha.

The Robson Creek 25 ha rainforest plot is situated on the Atherton Tablelands in Far North Queensland. It is part of the TERN FNQ Rainforest SuperSite. The following data is collected from the core hectare 6 within the 25 ha plot. LAI and photopoints are done at the end of each wet and dry season. The vascularplant survey and six gentry transects were done in 2012. Coarse woody debris is done each year.