{"help": "https://www.planningportal.nsw.gov.au/opendata/api/3/action/help_show?name=package_show", "success": true, "result": {"alternative_title": "Determining baselines, drivers and trends of soil health and stability in NSW forests \u2013 Regional Forest Agreement regions: Digital soil maps ", "approvaldate": "2022-05-17", "asset_details": "{\"package_id\": \"19911054-9ab9-49bc-b670-41d8aa6ebeaa\", \"identify\": [false, false, false, false, false, false, false, false, false, false], \"asset_location\": \"M:\\\\themes\\\\soil_condition\\\\NRC_forest_soil_condition_2021\\\\Digital_soil_maps\", \"opendata_ready\": true, \"institutional\": [true, true, true, true, true], \"coherence\": [true, true, true, false, true], \"accessibility\": [true, true, true, true, true], \"oeh_theme_two\": \"--Nothing selected--\", \"storage_format\": \"Zip; Tif\", \"id\": \"080e2ae0-1413-4faa-afee-4ca168f6061f\", \"source_system\": \"not applicable\", \"security\": \"Official\", \"accuracy\": [true, false, false, true, true], \"interpretability\": [false, true, true, true, true], \"oeh_theme_one\": \"biodiversity\", \"bit_dqs\": 33513279, \"creator\": {\"business_unit\": \"DPIE, Science, Economics and Insights Division\", \"id\": \"edd7e40b-30c2-40ad-acfb-c0afa914aa7e\", \"position\": \"Senior Scientist, Digital Soil Mapping\", \"role\": \"creator\", \"name\": \"Jonathan Gray\", \"email\": \"jonathan.gray@environment.nsw.gov.au\", \"contact\": \"02 9895 6519\", \"package_id\": \"19911054-9ab9-49bc-b670-41d8aa6ebeaa\"}, \"owner\": {}, \"custodian\": {\"business_unit\": null, \"id\": \"a032825f-ffee-45c5-ace2-80bc22d121d5\", \"position\": \"Natural Resources Commissioner\", \"role\": \"custodian\", \"name\": null, \"email\": null, \"contact\": null, \"package_id\": \"19911054-9ab9-49bc-b670-41d8aa6ebeaa\"}, \"steward\": {\"business_unit\": null, \"id\": \"8b01d164-434d-453d-aef6-e72ef39daaf8\", \"position\": \"Senior Team Leader, Metrics and Forecasting\", \"role\": \"steward\", \"name\": \"Mark Littleboy\", \"email\": \"mark.littleboy@environment.nsw.gov.au\", \"contact\": null, \"package_id\": \"19911054-9ab9-49bc-b670-41d8aa6ebeaa\"}}", "author": null, "author_email": null, "creatorName": "", "creator_user_id": "0106c1f2-85ad-4f5e-a17d-a5b8f7030b95", "dataset_template": "raster", "datum": "GDA94 / Geographic", "edition": "version 1", "extent_supplemental": "Majority of baseline soil condition maps represent the years 2008-09. Soil erosion maps represent period 2001-2020. Climate change maps derived from NARCliM 1.0 project represent period centred around 2070.", "field_of_research": "Soil Sciences not elsewhere classified", "geospatial_representation": "raster", "geospatial_topic": ["environment"], "hierarchy_weight": "0", "id": "4604aaa3-0679-439a-8f88-d44e047d54d9", "identification_status": "completed", "isopen": true, "keywords_string": "SOIL,SOIL-Erosion,FORESTS,CLIMATE-AND-WEATHER-Climate-change,HAZARDS-Fire,LAND-Use", "language": "eng", "license_id": "cc-by", "license_title": "Creative Commons Attribution", "license_url": "http://www.opendefinition.org/licenses/cc-by", "lineage": "Soil data comprised approximately 2100 profile points derived from SALIS, comprising data mainly from NSW soil survey program and 2008 -09 Monitoring Evaluation and Reporting (MER) program. Digital soil mapping used multiple linear regression (MLR) and random forest modelling techniques in R statistical program framework. Modelling established relationships of soil indicators with 15 environmental variables, available as 100 m spatial grids across the study area. Validation of maps was achieved using a 20% validation dataset initially separated from the 80% training dataset. Modelling of the influence of human and natural disturbances was achieved by applying \"space-for-time substitution\" modelling concepts. Hillslope erosion modelling involved application of the Revised Universal Soil Loss Equation (RUSLE). Methods are described fully in the accompanying Technical Report (Moyce et al. 2021)   ", "maintainer": null, "maintainer_email": null, "metadata_created": "2021-10-05T04:09:14.513362", "metadata_modified": "2025-10-23T01:20:12.999779", "name": "nsw-eastern-forest-soil-condition", "notes": "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:\r\nMoyce 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_](https://datasets.seed.nsw.gov.au/dataset/nsw-eastern-forest-soil-condition-report), Final report v1.1 for NSW Natural Resources Commission by NSW Department of Planning, Industry and Environment and University of Sydney.  ", "num_resources": 7, "num_tags": 6, "oeh_publishing_state": "yes", "organization": {"id": "8951d4f1-e598-4384-a43c-fab77d3ee733", "name": "nsw-natural-resources-commission", "title": "NSW Natural Resources Commission", "type": "organization", "description": "The Natural Resources Commission (the Commission) is an independent body with broad investigating and reporting functions for the purposes of establishing a sound evidence basis for the properly informed management of natural resources in the social, economic and environmental interests of the State.\r\n\r\nThe Commission aims to be of service to the people of NSW through providing independent, evidence based advice and thought leadership to Government to secure triple bottom line outcomes in natural resource management.", "image_url": "2022-01-13-002700.792694imageupload", "created": "2022-01-13T11:27:00.809887", "is_organization": true, "approval_status": "approved", "state": "active"}, "owner_org": "8951d4f1-e598-4384-a43c-fab77d3ee733", "package_type": "dataset", "parent_id": "nsw-eastern-forest-soil-condition-report", "place_name": "Regional Forest Agreement Regions of eastern NSW", "presentation_form": "mapDigital", "private": false, "purpose": "For monitoring and managing soil condition in eastern NSW forests into the future", "restriction": "licence", "spatial_coverage": "{\"type\": \"Polygon\", \"coordinates\": [[[148, -37.7], [148, -28], [154, -28], [154, -37.7], [148, -37.7]]]}", "spatial_distance": "100", "spatial_units": "m", "state": "active", "syndicate": "true", "temporal_coverage_from": "2001-01-01", "temporal_coverage_to": "2020-12-31", "title": "NSW eastern forest soil condition: digital soil maps", "type": "dataset", "update_freq": "asNeeded", "url": null, "use_limitation": "This data is provided under a Creative Commons Attribution 4.0 licence <a href='http://creativecommons.org/licenses/by/4.0'>http://creativecommons.org/licenses/by/4.0</a>. Attribute 'NSW Natural Resources Commission' in publications using this data.", "version": null, "data_quality": [{"date": "2021-06-30", "details": "Covers area within Regional Forest Agreement regions that has woody vegetation as mapped in NSW 2008 woody vegetation layer ", "type": "mdq:DQ_CompletenessCommission"}, {"date": "2021-06-30", "details": "Did not include areas with non woody vegetation and those outside of NSW RFA regions.", "type": "mdq:DQ_CompletenessOmission"}, {"date": "2021-06-30", "details": "Imperfect coverage of all environmental regimes in study area, ie, insufficient soil data in some areas of covariate space, and different temporal coverage of soil data. Potential limitations in assumptions made for modelling of change in soil condition with disturbance, for example (i) using forest management zones to represent differing levels of human disturbance and (ii) using broad spatial data on bushfire history to spatially model extent of change in soil condition from bushfire. ", "type": "mdq:DQ_ConceptualConsistency"}, {"date": "2021-06-30", "type": "mdq:DQ_TopologicalConsistency"}, {"date": "2021-06-30", "details": "The validation of the digital soil maps revealed only moderate statistical reliability, eg, Lin's concordance correlation coefficients (CCC) generally 0.3 to 0.4. Even though the maps have a spatial resolution of 100 m, they cannot be relied upon at this fine scale. Nevertheless, there is confidence in the broad spatial and temporal trends revealed by the study.  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