This dataset includes digital soil map products of key soil condition indicators covering the Regional Forest Agreement regions of eastern NSW. Raster maps at 100 m resolution reveal baseline (approximately 2008) levels of the soil indicators soil carbon, pH, bulk density, hillslope erosion and others. Maps are presented on trends of change resulting from different human and natural disturbances such as forest harvesting, uncontrolled stock grazing, climate change and bush fire. Full description of the digital soil maps and methods are presented in: Moyce MC, Gray JM, Wilson BR, Jenkins BR, Young MA, Ugbaje SU, Bishop TFA, Yang X, Henderson LE, Milford HB, Tulau MJ, 2021. Determining baselines, drivers and trends of soil health and stability in New South Wales forests: NSW Forest Monitoring & Improvement Program, Final report v1.1 for NSW Natural Resources Commission by NSW Department of Planning, Industry and Environment and University of Sydney.

These datasets consist of soil maps generated to assess baselines, drivers and trends for soil health and stability within the NSW Regional Forest Agreement (RFA) regions. The maps are organised into empirical soil maps, digital soil maps, and data cube maps. Empirical soil maps consists of four products. Maps include topsoil pH, carbon, Emerson Aggregate Stability and Soil Profile Quality Confidence. Each map consists of 2,162 units. Maps were generated using the most representative soil profile for each unit available within the Soil and Land Information System (SALIS). The 2008 woody vegetation coverage was used as baseline. Maps reflect values when the sampling occurred with temporal changes not being accounted for. Locations with missing or of poor quality data are identified, providing a confidence rating map as part of the evaluation process. Digital soil maps include map products of key soil condition indicators covering the Regional Forest Agreement regions of eastern NSW. Raster maps of key soil indicators, such as soil carbon, pH, bulk density, hillslope erosion and others, were created at 100 m resolution. For each key soil indicator, maps include baseline (approximately 2008) levels as well as trends of change resulting from different human and natural disturbances such as forest harvesting, uncontrolled stock grazing, climate change and bush fire. Data cube maps include time series of soil organic carbon (SOC) between January 1990 and December 2020 for the Regional Forest Agreement regions of eastern NSW. Products provide estimates of SOC concentrations and associated trends through time. Modelling was carried out using a data cube platform incorporating machine learning space-time framework and geospatial technologies. Important covariates required to drive this spatio-temporal modelling were identified using the Recursive Feature Elimination algorithm (RFE). A web mapping application on the NSW Spatial Collaboration Portal depicts these datasets. Access the webapp through the link below: https://portal.spatial.nsw.gov.au/portal/home/item.html?id=af9c71935f024f4a8f64cb39f5eba007

This dataset includes four soil products using an empirical approach to assess soil condition indicators and complete a data gap analysis covering the Regional Forest Agreement regions of eastern NSW. In the empirical analysis, maps presented soil indicator values of topsoil pH, organic carbon and emerson aggregate stability for each of the 2162 soil map units, based on the unit's most representative soil profile available within the Soil and Land Information System (SALIS). Maps reflect values when the sampling occurred with temporal changes not being accounted for and used the 2008 woody vegetation coverage as the baseline extent. The dataset identifies the locations where data is missing or of poor quality, providing a confidence rating map as part of the evaluation process. Full description of the empirical maps and methods are presented in: Moyce MC, Gray JM, Wilson BR, Jenkins BR, Young MA, Ugbaje SU, Bishop TFA, Yang X, Henderson LE, Milford HB, Tulau MJ, 2021. _Determining baselines, drivers and trends of soil health and stability in New South Wales forests: NSW Forest Monitoring & Improvement Program_v1.1, Final report for NSW Natural Resources Commission by NSW Department of Planning, Industry and Environment and University of Sydney.

The NSW Carbon Monitoring project is a collaboration between the Natural Resources Commission of NSW and Mullion Group to develop a spatial time-series dataset of forest carbon history for the state of NSW at ~25m resolution. The project used FLINTpro software to integrate historical environmental and land management data to model carbon stock and fluxes. Aboveground biomass refers to the amount of carbon stored within aboveground forest components (pools) which includes leaves, branches, bark and stems. Belowground biomass refers to the amount of carbon stored within belowground forest components (pools) which includes coarse and fine roots. Dead Organic Matter refers to the amount of carbon stored within dead forest components (pools) which includes leaf litter, branch litter, bark litter, stem litter, and dead roots. Carbon stored within soil and harvested wood products is not included within any of these datasets. This dataset has been superseeded by NSW Forest Carbon Stock - Aboveground, Belowground and Dead Organic Matter Carbon Mass 1990-2021

This publication is the final report of a project that assessed the baselines, drivers and trends for soil health and stability within the NSW Regional Forest Agreement (RFA) regions. The NSW Department of Planning, Industry and Environment (DPIE) and the University of Sydney with collaboration from the University of New England, were engaged by the NSW Natural Resource Commission (NRC) to prepare this report as part of the NSW Forest Monitoring and Improvement Program. Full descriptions of the soil map products, methods and results are presented in this technical report: Moyce MC, Gray JM, Wilson BR, Jenkins BR, Young MA, Ugbaje SU, Bishop TFA, Yang X, Henderson LE, Milford HB, Tulau MJ, 2021. Determining baselines, drivers and trends of soil health and stability in New South Wales forests: NSW Forest Monitoring & Improvement Program. Version 1.1 Supporting data packages of deliverables can be sourced from the following three datasets below: NSW eastern forest soil condition: digital soil maps NSW eastern forest soil condition: empirical soil maps NSW eastern forest soil condition: Spatio-temporal data cube maps

The NSW Carbon Monitoring project is a collaboration between the Natural Resources Commission of NSW and Mullion Group to develop a spatial time-series dataset of forest carbon history for the state of NSW at ~25m resolution. The project used FLINTpro software to integrate historical environmental and land management data to model carbon stock and fluxes. Aboveground biomass refers to the amount of carbon stored within aboveground forest components (pools) which includes leaves, branches, bark and stems. Belowground biomass refers to the amount of carbon stored within belowground forest components (pools) which includes coarse and fine roots. Dead Organic Matter refers to the amount of carbon stored within dead forest components (pools) which includes leaf litter, branch litter, bark litter, stem litter, and dead roots. Carbon stored within soil and harvested wood products is not included within any of these datasets

This dataset contains spatial layers describing Forest Canopy Loss and Recovery from 1998-2019 in NSW Regional Forest Agreements (RFA) Areas along the eastern coast. These have been based off the National Greenhouse Gas Inventory (NGGI) National Carbon Accounting System (NCAS) National Forest and Sparse Woody Vegetation Data grids (ABARES, 2020). These base grids are Landsat in origin and have a resolution of 25m. For this dataset product and the processing of metrics, aspects of canopy loss and disturbances in the forest estate were investigated. Measures of canopy loss and recovery are seen as one of the multiple indicators of forest health. This is related to agents or pressures that affect the capacity of native forests and commercial operations to maintain normal ecosystem functions and sustainably provide productive capacity. To attribute disturbances, as a driver of change, a Multiple Lines of Evidence (MLE) approach was used that leveraged available spatial datasets. This allowed for a project-wide disturbance and disturbance context layer to be generated. This information can be interpreted back against forest cover extent change outputs, in particular the differences between individual years, to identify the areas of change and the likely reasons why. Therefore, landscape trends in forest loss can be potentially assigned or at the very least investigated. The time taken, in terms of years, for areas to recover from losses in forest canopy cover extent can has also been determined. This process identifies the time taken for a patch of forest to return to a 20% canopy cover threshold, and other characteristics such as the forest type and likely disturbance or loss event. Forest Canopy Loss and Recovery uses measures of canopy loss and disturbances which can be interpreted back against forest cover extent change outputs, in particular the differences between individual years, to identify the areas of change and the likely reasons why. Therefore, landscape trends in forest canopy loss can be potentially assigned or at the very least investigated. Time taken in years for areas to recover for losses has also been determined, as-well as other characteristics such as forest type and likely disturbance/loss event. Base cover extent grids used are from the NSW RFA Historic Forest Canopy Cover Extent – 1995 to 2019 product. Read more about the project on the Natural Resources Commission website: https://www.nrc.nsw.gov.au/fmip-baselines-ecosystem-health-projectfe1 This dataset is superseded by 'NSW Forest Monitoring and Improvement Program State-Wide Historic Forest Canopy Loss and Recovery - 1998 to 2020'

Export DataThe Forest Monitoring Steering Committee commissioned a consortium between the NSW Department of Planning, Industry and Environment and the University of Sydney to deliver Baselines, Drivers and Trends for soil stability and health in forest catchments across the NSW Regional Forest Agreement areas.Find out more about the project here.Empirical Soil Maps: Soil data collected using an empirical approach, presented on 2162 units, based on the unit's most representative soil profile available within the Soil and Land Information System (SALIS). Maps reflect values when the sampling occurred with temporal changes not being accounted for.Metadata Portal Metadata InformationContent TitleBaselines for Soil Health and Stability in NSW RFA Regions: Empirical Soil MapsContent TypeScene Layer/Scene Layer PackageDescriptionSoil data collected using an empirical approach, presented on 2162 units, based on the unit's most representative soil profile available within the Soil and Land Information System (SALIS). Maps reflect values when the sampling occurred with temporal changes not being accounted for.Initial Publication Date30/05/2022Data Currency30/05/2022Data Update FrequencyOtherContent SourceOtherFile TypeMap Feature ServiceAttributionData Theme, Classification or Relationship to other DatasetsAccuracySpatial Reference System (dataset)OtherSpatial Reference System (web service)OtherWGS84 Equivalent ToOtherSpatial ExtentContent LineageData ClassificationUnclassifiedData Access PolicyOpenData QualityTerms and ConditionsCreative CommonsStandard and SpecificationData CustodianNSW Natural Resources CommissionPoint of ContactEmma Pearce (Emma.Pearce@nrc.nsw.gov.au)Data AggregatorData DistributorSpatial VisionAdditional Supporting InformationTRIM Number

The 2022 NSW Forest extent layer was created by the NSW DPIRD Forest Science team applying spatio-temporal analysis of the 2017-2022 National Forest and sparse woody vegetation data (Version 7.0 - 2022 Release) (Department of Climate Change, Energy, the Environment, and Water's). The data is available on data.gov.au. The dataset was further analysed and masked to exclude non-forest areas and create a forest extent layer with a 20 percent canopy cover for the NSW UTM Zones 55 & 56. The mask layer includes various datasets such as NSW Land use 2017, State Vegetation Type map (SVTM), Land Zoning, Water body, etc. The DPIRD Plantation unit's Authorised plantation layer (current as Aug 2024) was used to characterise forest types, i.e. Native forest and Plantation.

The spatial layers in this dataset detail forest cover extent over NSW. They have been created for the NSW Natural Resources Commission to detail historic baseline and trends of forest cover extent coverage for NSW for all land tenures, including all RFAs and IFOAs. These have been based off the National Greenhouse Gas Inventory (NGGI) National Carbon Accounting System (NCAS) National Forest and Sparse Woody Vegetation Data grids (ABARES, 2021). These base grids are Landsat in origin and have a resolution of 25m. These base grids have been processed through a series of land use and vegetation type exclusion masking and a through a fuzzy-logic based certainty analysis to reflect a forest cover extent coverage for NSW that is reflective of past and current coverage. These grids cover the years from 1995 to 2020. The year gaps are triennial or biennial data layers from 1995 to 2004. 1996,1997,1999,2001,2003 years missing as these were not assessed in original applied database. From 2004 to 2020 data layers become annualised. Read more about the project on the Natural Resources Commission website: https://www.nrc.nsw.gov.au/fmip-baselines-ecosystem-health-projectfe1 This dataset supersedes "NSW Forest Monitoring and Improvement Program RFA Historic Forest Cover Extent – 1995 to 2019". https://portal.tern.org.au/metadata/TERN/fef2d61b-7c5e-42be-88c1-849a3fc6a70a.