Export DataAccess APIThe 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.Baseline Soil Maps: Digital Soil Modelling (DSM) outputs describing the baseline conditions of key indicators of soil condition, based on quantitative modelling techniques that relate known soil qualities with known environmental qualities and extrapolates using continuous environmental data.Metadata Portal Metadata InformationContent TitleBaselines for Soil Health and Stability in NSW RFA Regions: Baseline Soil MapsContent TypeScene Layer/Scene Layer PackageDescriptionDigital Soil Modelling (DSM) outputs describing the baseline conditions of key indicators of soil condition, based on quantitative modelling techniques that relate known soil qualities with known environmental qualities and extrapolates using continuous environmental data.Initial Publication Date14/06/2022Data Currency14/06/2022Data 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

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 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. Spatial outputs of this project are presented in this webapp. Model Information: 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.Baseline Soil Maps: Digital Soil Modelling (DSM) outputs describing the baseline conditions of key indicators of soil condition, based on quantitative modelling techniques that relate known soil qualities with known environmental qualities and extrapolates using continuous environmental data.Drivers & Trends: Maps describing trends of soil quality indicators and the impact of key drivers of soil condition change, such as Climate Change, Land Disturbance, Bushfires etc. This includes DSM models and Data Cube models using machine learning techniques.More information and the underlying datasets can be found here._______________________________________For a User Guide for this Webapp, follow this link:User GuideTo leave feedback on your experience with this we site or its data, follow this link:NRC Contact PageTo leave feedback on your experience with the Spatial Collaboration Portal, follow this link (account creation required) :Spatial Collaboration Portal Feedback__________________________________This webapp and associated webapps are part of the Forest Monitoring & Improvement Program Metadata Portal Metadata Information Content TitleBaselines for Soil Health and Stability in NSW RFA Regions WebmapContent TypeWeb MapDescriptionThis webmap describes Baselines, Drivers and Trends for soil stability and health in forest catchments across the NSW Regional Forest Agreement areas.Initial Publication Date06/06/2022Data Currency06/06/2022Data Update FrequencyOtherContent SourceFile TypeMap Feature ServiceAttributionData Theme, Classification or Relationship to other DatasetsAccuracySpatial Reference System (dataset)WGS84Spatial Reference System (web service)EPSG:4326WGS84 Equivalent ToGDA94Spatial ExtentContent LineageData ClassificationUnclassifiedData Access PolicyOpenData QualityTerms and ConditionsCreative CommonsStandard and SpecificationData CustodianNatural Resources CommissionPoint of Contactnrc@nrc.nsw.gov.auData AggregatorData DistributorAdditional Supporting InformationTRIM Number

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 2017 Landuse captures how the landscape in NSW is being used for food production, forestry, nature conservation, infrastructure and urban development. It can be used to monitor changes in the landscape and identify impacts on biodiversity values and individual ecosystems. The NSW 2017 Landuse mapping is dated September 2017. This is version 1.5 of the dataset, published December 2023. Version 1.5 of the 2017 Landuse incorporates the following updates: Fine scale mapping of the Central Coast, Illawarra and Shoalhaven regions Mapping enhancements to regional centres to improve the mapping accuracy for these centres NSW road network based on road centreline data from Transport NSW, with standardised buffer applied to approximate the carriage width based on the road type Plantation type (native hardwood and softwood) information within State Forest Estates Horticulture data to tertiary or commodity level present in September 2017 from Australian Tree Crop Map Dashboard developed by University of New England - Applied Agricultural Remote Sensing Centre https://www.une.edu.au/research/research-centres-institutes/applied-agricultural-remote-sensing-centre/collaborative-r-and-d-opportunities/industry-applications-and-maps Fixes to identified errors since published version 1.2 Previous Versions *Version 1.4 internal update (not published) * Version 1.3 internal update (not published) * Version 1.2 published 24 June 2020 - Fine scale update to Greater Sydney Metropolitan Area * Version 1 published August 2019 The 2017 Landuse is based on Aerial imagery and Satellite imagery available for NSW. These include, but not limited to; digital aerial imagery (ADS) captured by NSW Department of Customer Service (DCS), high resolution urban (Conurbation) digital aerial imagery captured on behalf of DCS, SPOT 5, 6 & 7(Airbus), Planet™, Sentinel 2 (European Space Agency) and LANDSAT (NASA) Satellite Imagery. Mapping also includes commercially available imagery from Nearmap™ and Google Earth™, along with Google Street View™. Mapping takes into consideration ancillary datasets such as tenure such as National Parks and State forests, cadastre, roads parcels, land zoning, topographic information and Google Maps, in conjunction with visual interpretation and field validation of patterns and features on the ground. The 2017 Landuse was captured on screen using ARC GIS (Geographical Information Software) at a scale of 1:8,000 scale (or better) and features are mapped down to 2 hectares in size. Exceptions were made for targeted Landuse classes such as horticulture, intensive animal husbandry and urban environments, which were mapped at a finer scale. The 2017 Landuse has complete coverage of NSW. It also includes updates to the fine scale Horticulture mapping for the east coast of NSW - Newcastle to the Queensland boarder and Murray-Riverina Region. This horticultural mapping includes operations to the commodity level based on field work and high-resolution imagery interpretation. Landuse classes assigned are based on activities that have occurred in the last 5-10 years that may be part of a rotational practice. Time-series LANDSAT information has been used in conjunction with more recent Satellite Imagery to determine whether grasslands have been disturbed or subject to ongoing land management activities over the past 30 years. The 2017 Landuse was captured on screen using ARC GIS (Geographical Information Software) at a scale of 1:8,000 scale (or better) and features are mapped down to 2 hectares in size. Exceptions were made for targeted Landuse classes such as horticulture, intensive animal husbandry and urban environments (including Greater Sydney Metropolitan region), which were mapped at a finer scale. The reliability scale of the dataset is 1:10,000. Mapping has been subject to a peer review and quality assurance process. Land use information has been captured in accordance with standards set by the Australian Collaborative Land Use Mapping

The Forest Monitoring Steering Committee commissioned the University of New England and the NSW Departments of Primary Industries and Planning, Industry and Environment to deliver baselines, drivers and trends for species occupancy and distribution in NSW forests across tenures. Over 15 leading scientists formed a project team lead by Nick Reid.This work delivered a comprehensive suite of models to baseline species occupancy and distribution and help explore drivers in change.Find out more about the project here.This webmap contains those models of a selected group of vulnerable flora & fauna.Model Information:Maximum Entropy (Maxent) & Species Occupancy Model (SOM) outputs are combination outputs dependent on known species occurrence in the landscape, the species relationship with environmental variables (covariates) such as temperature, rainfall and topography; and its predicted occurrence based on covariate analysis. Maxent models do not predict actual occupancy, but rather habitat suitability, while SOMs predict actual occupancy. confounding factors such as inter-species competition, geographical barriers and disturbance events play a significant role in species occurrence, and are not considered in Maxent or SOM.To find more information about the models and processes involved, or to access the underlying data, click here.________For a User Guide for this Webapp, follow this link:User GuideTo leave feedback on your experience with this web site or its data, follow this link:NRC Contact PageTo leave feedback on your experience with the Spatial Collaboration Portal, follow this link:Spatial Collaboration Portal Feedback________This webmap and associated webapps are part of the Forest Monitoring & Improvement Program. Metadata Portal Metadata Information Content TitleSpecies Occupancy and Distribution Baselines in NSW RFA Regions WebmapContent TypeWeb MapDescriptionThis Webmap contains a series of spatial outputs describing probabilistic species predictive occupancy (Species Occupancy Models, or SOM) & habitat suitability (Maximum Entropy, or Maxent) surfaces.Initial Publication Date06/06/2022Data Currency01/01/2000Data Update FrequencyOtherContent SourceFile TypeMap Feature ServiceAttributionData Theme, Classification or Relationship to other DatasetsAccuracySpatial Reference System (dataset)WGS84Spatial Reference System (web service)EPSG:4326WGS84 Equivalent ToGDA94Spatial ExtentContent LineageData ClassificationUnclassifiedData Access PolicyOpenData QualityTerms and ConditionsCreative CommonsStandard and SpecificationData CustodianNatural Resources CommissionPoint of Contactnrc@nrc.nsw.gov.auData AggregatorData DistributorAdditional Supporting InformationTRIM Number

The 2013 land use captures how the landscape in NSW is being used for food production, forestry, nature conservation, infrastructure and urban development. It can also be used to monitor changes in the landscape and identify resulting impacts on biodiversity values and individual ecosystems. The state wide land use data is a compilation of the best available land use information for NSW that was available in August 2017. Land use and tenure datasets from a variety of projects have been compiled, these include; Landuse mapping 2017 – 1:10,000 scale mapping using 2013 SPOT 5 satellite imagery and ADS digital aerial imagery. Covering rural zoned, agricultural areas. These areas are applicable to Local Land Services Act 2016. NSW Horticulture mapping project – Fine scale mapping (1:5,000) mapping of horticulture production to the commodity level (where applicable), on the mid-north and north coast of NSW. This was in response to the outbreak of Panama disease, Tropical Race 4, found in a banana plantation in Northern Queensland. It is part of a collaborative mapping project to improve Biosecurity information between state jurisdictions and the commonwealth. It also covers plantation forestry for the project area. Hunter 2013 mapping – 1:10,000 scale mapping covering most of the Hunter catchment based on 2013 SPOT5 imagery. It was part of a pilot land use update trial for intended use in Department of Planning Regional Growth Plans. This is an update of the 2005 Land use Hunter catchment and 2008 Upper Hunter catchment land use mapping projects, also available on SDE and P drive. National Parks and State Forest Tenure mapping 2017 Sydney Map sheet 2012 – Detailed urban mapping (1:10,000 scale) trial using high resolution Digital aerial imagery Existing Land use information (circa 2003) has been used for non-rural zoned areas and not covered by the other projects mentioned above. This component of the 2013 land use has a reliability scale of 1:25,000. The areas where the circa 2003 land use product used include; urban, industrial, commercial and environmental local government LEP (Local Environment Planning) zones. It also includes areas of metropolitan Sydney that are excluded from the LLS Act 2016. Land use information has been captured in accordance with standards set by the Australian Collaborative Land Use Mapping Program (ACLUMP) and using the Australian Land Use and Management ALUM Classification. The ALUM classification is based upon the modified Baxter & Russell classification and presented according to the specifications contained in http://www.agriculture.gov.au/abares/aclump/land-use/alum-classification. The 2013 land use, that was mapped for the purposes of the Local Land Services Act, was commenced in July 2016 and completed by August 2017. It covers all rural zoned (agricultural) areas, and was based on most appropriate SPOT5 imagery to represent land use at June 2013. It includes values in the attribute fields of source, source date, source scale, reliability and land use mapping (currency) date. The reliability scale of areas mapped form 2012 onward is 1:10,000. For areas where circa 2003 land use information has been used the reliability scale is 1:25,000. This is identified in the source scale attribute for each feature in the dataset. The date of the data set is set as the land use occurring at the time the imagery (satellite or aerial) was acquired, which can range from 2003 to 2013. This dataset was updated in August 2017 to include values in the attribute fields of Source, Source Date, Source Scale, Reliability and LU Mapping (Currency) Date. A national catchment scale land use product is also available as a 50m raster - Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) http://www.agriculture.gov.au/abares/aclump/land-use/data-download.

This dataset was derived from the primary ‘SLATS Landsat woody change data (25m) for 1988 – 2010’ raster (grid) layers used to generate the annualised woody vegetation change rates for the 2010 NSW Annual Report of Native Vegetation. This data describes the areas and type of woody vegetation change (loss) based on the analysis of multi-date Landsat imagery covering NSW. This data is based on a biennial LANDSAT coverage between 1988-2006 and annual coverage 2006-2010. LANDSAT Imagery 1988-2008 was processed by Geoscience Australia at 25m resolution. 2008 onwards is based on USGS processed LANDSAT at 30m resolution. Note, this vector data may generate slightly different aerial statistics to those generated from the source raster data. This is due to variation caused by the data transformation and vector cleaning processes applied in generating the vector data.

This dataset created by the University of Sydney, includes time series digital soil map products of soil organic carbon (SOC) between January 1990 and December 2020 for the Regional Forest Agreement regions of eastern NSW. Modelling was completed using a data cube platform incorporating machine learning space-time framework and geospatial technologies. Products provide estimates of SOC concentrations and associated trends through time. Also important covariates required to drive this spatio-temporal modelling are identified using the Recursive Feature Elimination algorithm (RFE), which including a range of predictors that vary in space, time and space and time. 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. The metadata's data packages section includes project scripts and code, final project report and an external Cloudstor link to download the predicted SOC map products,