15 datasets found
  1. D

    Earth Observation-On Farm Storage (OFS) Water Volume Monthly

    • data.nsw.gov.au
    • researchdata.edu.au
    arcgis rest service +2
    Updated Nov 13, 2025
    + more versions
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    NSW Department of Climate Change, Energy, the Environment and Water (2025). Earth Observation-On Farm Storage (OFS) Water Volume Monthly [Dataset]. https://data.nsw.gov.au/data/dataset/earth-observation-on-farm-storage-ofs-water-volume-monthly
    Explore at:
    wfs, pdf, arcgis rest serviceAvailable download formats
    Dataset updated
    Nov 13, 2025
    Dataset provided by
    Department of Climate Change, Energy, the Environment and Water of New South Waleshttps://www.nsw.gov.au/departments-and-agencies/dcceew
    Authors
    NSW Department of Climate Change, Energy, the Environment and Water
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Area covered
    Earth
    Description

    This product delivers a monthly timeseries of estimated water volume for On-Farm Storages (OFS) across the five valleys of the northern Murray-Darling Basin (Border River, Gwydir, Namoi, Macquarie-Castlereagh, and Barwon-Darling). OFS are critical for agricultural water supply, enabling farmers to store water for irrigation and supporting effective water resource management in the face of water scarcity, regulatory requirements, climate variability, and the need for sustainable agricultural practices.

    Estimated OFS water volume is derived through a two-step remote sensing approach. First, water surface area is calculated from multispectral satellite imagery (Landsat and Sentinel-2) using a geospatial model [1][2]. Second, LiDAR-derived storage capacity curves are applied to relate the observed surface area to water height above the Australian Height Datum (AHD), enabling calculation of the estimated water volume for each storage [3].

    The dataset is updated monthly using the latest available cloud-free satellite imagery, and historical volume are computed from archived images. The timeseries spans from 1987 to the present, providing a consistent monthly record of estimated OFS water volume across the region.

    References

    [1] https://datasets.seed.nsw.gov.au/dataset/remote-sensing-earth-observation-water-toolkit.

    [2] https://www.tandfonline.com/doi/full/10.1080/01431160600589179

    [3] https://hls.gsfc.nasa.gov

    Note: If you would like to ask a question, make any suggestions, or tell us how you are using this dataset, please visit the NSW Water Hub which has an online forum you can join.

  2. D

    State Environmental Planning Policy No 52-Farm Dams and Other Works in Land...

    • data.nsw.gov.au
    • researchdata.edu.au
    arcgis rest service +2
    Updated Oct 23, 2025
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    NSW Department of Planning, Housing and Infrastructure (2025). State Environmental Planning Policy No 52-Farm Dams and Other Works in Land and Water Management Plan Areas [Dataset]. https://data.nsw.gov.au/data/dataset/sepp-farm-dams-other-works-in-land-water-management-plan-areas
    Explore at:
    json, arcgis rest service, pdfAvailable download formats
    Dataset updated
    Oct 23, 2025
    Dataset provided by
    Department of Planning, Housing and Infrastructure of New South Waleshttps://www.nsw.gov.au/departments-and-agencies/department-of-planning-housing-and-infrastructure
    Authors
    NSW Department of Planning, Housing and Infrastructure
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The data represents Farm Dams and Other Works in Land and Water Management Plan Areas for State Environmental Planning Policy.

  3. Z

    2023 Hyper Yielding Crops Data

    • data.niaid.nih.gov
    • zenodo.org
    Updated Jul 12, 2024
    + more versions
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    Warren, Darcy; Poole, Nick; Field Applied Research Australia; Brill Ag; Brill, Rohan (2024). 2023 Hyper Yielding Crops Data [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_11069162
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    Dataset updated
    Jul 12, 2024
    Dataset provided by
    Field Applied Research Australia
    Authors
    Warren, Darcy; Poole, Nick; Field Applied Research Australia; Brill Ag; Brill, Rohan
    Description

    The GRDC Hyper Yielding Crops (HYC) project was set up to challenge the current boundaries of productivity and profitability in the high yielding regions of southern Australia. The objective was underpinned by five research centres across five states (WA, SA, Victoria, Tasmania and NSW) focusing on germplasm, disease and canopy management.

    Data and file overview (D-3.2)

    The data presented here is the 2023 Hyper Yielding Crops Project raw data. The results cover the following sites and crops:

    2023/24 HYC Barley (SA, TAS, VIC & WA)

    2023/24 HYC Canola (NSW, SA, VIC & WA)

    2023/24 HYC Wheat (NSW, SA, TAS, VIC & WA)

    Data files

    The data are organised by approximate crop type, site and trial ID. The trial ID corresponds to trial details and analysis contained within the pdf results report.

    This repository includes:

    The most recent version of the excel data sheet(s) that record original data and contains related calculations (eg. plant density from plant counts). These are in similar formats for most trials.

    The pdf copy of the most recent report on the experiment.

    Methodological information (D-3.3)

    Experimental design and treatment summaries are contained within the Annual results report contained within this repository (HYC_Output 1_Milestone 112_2023 HYC Results UPDATED.pdf). A copy of this report is also avliablie on the FAR Australia website (https://faraustralia.com.au/resource).

    Raw data has been summarised per plot into columns representing each assessment conducted using GDM ARM trial management software. Each sheet contains a key describing units and codes for each assessment.

    Environmental/experimental conditions (D-3.4)

    The trial reports describe experimental or environmental conditions (including soil and climate details) affecting the interpretation of the relevant trial data.

    Data-specific information (D-3.5)

    The data spreadsheets are self-describing. The rows above the data typically contain the date, crop growth stage, a brief description of the assessment made and any notes made. A key is located in each sheet with further descriptions of units, codes and abreviations used.

    Acknowledgement

    The research undertaken as part of these projects is made possible by the significant contributions of growers through both trial cooperation and the support of the GRDC, the authors would like to thank them for their continued support. FAR Australia gratefully acknowledges the support of all of its research and extension partners in the Hyper Yielding Crops project. These are CSIRO, the Department of Primary Industries and Regional Development (DPIRD) in WA, Brill Ag, Southern Farming Systems (SFS), Techcrop, the Centre for eResearch and Digital Innovation (CeRDI) at Federation University Australia, MacKillop Farm Management Group (MFMG), Riverine Plains Inc and Stirling to Coast Farmers.

  4. r

    Operation environmental management plan : Woodlawn wind farm : WOO-H-2130

    • researchdata.edu.au
    • data.nsw.gov.au
    Updated Dec 4, 2018
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    NSW Department of Planning, Housing and Infrastructure (2018). Operation environmental management plan : Woodlawn wind farm : WOO-H-2130 [Dataset]. https://researchdata.edu.au/operation-environmental-management-h-2130/3853336
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    Dataset updated
    Dec 4, 2018
    Dataset provided by
    data.nsw.gov.au
    Authors
    NSW Department of Planning, Housing and Infrastructure
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Environmental Impact Statement: Operation environmental management plan : Woodlawn wind farm : WOO-H-2130

  5. Number of carcasses inspected in NSW (1999–2009) by prevalence area.

    • plos.figshare.com
    xls
    Updated Jun 7, 2023
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    Ian J. Links; Laurence J. Denholm; Marilyn Evers; Lloyd J. Kingham; Robert J. Greenstein (2023). Number of carcasses inspected in NSW (1999–2009) by prevalence area. [Dataset]. http://doi.org/10.1371/journal.pone.0246411.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 7, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Ian J. Links; Laurence J. Denholm; Marilyn Evers; Lloyd J. Kingham; Robert J. Greenstein
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    New South Wales
    Description

    Number of carcasses inspected in NSW (1999–2009) by prevalence area.

  6. f

    “Positive” consignments in NSW (1999–2009) by prevalence area.

    • figshare.com
    xls
    Updated Jun 10, 2023
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    Ian J. Links; Laurence J. Denholm; Marilyn Evers; Lloyd J. Kingham; Robert J. Greenstein (2023). “Positive” consignments in NSW (1999–2009) by prevalence area. [Dataset]. http://doi.org/10.1371/journal.pone.0246411.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 10, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Ian J. Links; Laurence J. Denholm; Marilyn Evers; Lloyd J. Kingham; Robert J. Greenstein
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    New South Wales
    Description

    “Positive” consignments in NSW (1999–2009) by prevalence area.

  7. SenseFuture Dataset: Novel Agronomy for Resilient Farming Systems

    • data.csiro.au
    • researchdata.edu.au
    Updated Oct 10, 2025
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    Han Eusun; Jonathan Richetti; John Kirkegaard (2025). SenseFuture Dataset: Novel Agronomy for Resilient Farming Systems [Dataset]. http://doi.org/10.25919/ec32-hk55
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    Dataset updated
    Oct 10, 2025
    Dataset provided by
    CSIROhttp://www.csiro.au/
    Authors
    Han Eusun; Jonathan Richetti; John Kirkegaard
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Time period covered
    May 1, 2021 - Sep 30, 2024
    Area covered
    Dataset funded by
    CSIROhttp://www.csiro.au/
    University of Copenhagen
    Aarhus University
    Description

    Data acquired in Australia through the EU Horizon2020 MSCA-Global fellowship by Dr Eusun Han, project number 884364.

    Funding: EU Horizon 2020, MSCA-IF (SenseFuture: 884364)

    High-resolution RGB, multispectral, and thermal drone imagery from the Iandra field site (2021–2023), supporting crop monitoring, grazing trials, and digital agronomy research.

    FULL DESCRIPTION

    This dataset contains raw and processed UAV imagery collected at the CSIRO Iandra field site (Greenethorpe, NSW) as part of the SenseFuture: Novel Agronomy for Resilient Farming Systems project. The imagery captures crop and pasture responses to experimental treatments (including grazing, mowing, and plot management) over multiple growing seasons.

    The Iandra field site, located at Iandra Castle near Greenethorpe, NSW, is a key CSIRO farming systems research site. It hosts long-term experiments evaluating crop sequences, soil health, and water use efficiency under varying management practices. Trials include wheat–canola rotations and integration of legumes such as fababean to improve nitrogen fixation and sustainability. The site combines small-plot trials with farm-scale demonstrations and provides critical data on productivity, soil fertility, and system resilience in southern NSW.

    The dataset includes flights taken with different sensor configurations:

    RGB imagery collected using a DJI Phantom 4 Pro at ~30 m altitude, providing high-resolution (centimetre scale) orthomosaics. Multispectral imagery from a Micasense camera, used to generate reflectance-calibrated bands and vegetation indices (e.g. NDVI, NDRE). Thermal imagery from DJI M2EA test flights, used to explore canopy temperature variation.

    TEMPORAL COVERAGE

    June–September 2021 (pre-grazing, post-grazing, mowing, and multiple growth stages) July–September 2022 (RGB and thermal test flights) 2023 imagery [details to confirm]

    SPATIAL COVERAGE

    Iandra research trial, near Greenethorpe, NSW, Australia Approx. 34°31′21.698″ S, 148°18′6.484″ E (WGS84) Experimental plots within grazing and cropping trials.

    FILE CONTENTS

    The collection contains: Raw project files (.p4d) for Pix4DMapper workflows Processed reports (.pdf) describing Pix4D processing outputs and quality checks Stitched datasets (.zip archives, 15–70 GB each) containing orthomosaics, reflectance maps, and metadata Ancillary GIS outputs for integration into QGIS and other geospatial software

    See files for more information. Lineage: Flights were conducted at key crop growth stages during 2021–2023. Imagery was processed using Pix4DMapper to generate orthomosaics and vegetation indices, with quality reports included. GIS layers were prepared for integration into QGIS. File sizes range from 100 MB (thermal) to ~70 GB (RGB orthomosaics).

  8. Number of vaccine doses sold in NSW (1999–2009) by prevalence area.

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Ian J. Links; Laurence J. Denholm; Marilyn Evers; Lloyd J. Kingham; Robert J. Greenstein (2023). Number of vaccine doses sold in NSW (1999–2009) by prevalence area. [Dataset]. http://doi.org/10.1371/journal.pone.0246411.t006
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Ian J. Links; Laurence J. Denholm; Marilyn Evers; Lloyd J. Kingham; Robert J. Greenstein
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    New South Wales
    Description

    Number of vaccine doses sold in NSW (1999–2009) by prevalence area.

  9. Distribution of flocks and sheep in NSW (2000–2009) by prevalence area.

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Ian J. Links; Laurence J. Denholm; Marilyn Evers; Lloyd J. Kingham; Robert J. Greenstein (2023). Distribution of flocks and sheep in NSW (2000–2009) by prevalence area. [Dataset]. http://doi.org/10.1371/journal.pone.0246411.t007
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Ian J. Links; Laurence J. Denholm; Marilyn Evers; Lloyd J. Kingham; Robert J. Greenstein
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    New South Wales
    Description

    Distribution of flocks and sheep in NSW (2000–2009) by prevalence area.

  10. Estimated % of sheep vaccinated in NSW (1999–2009) by prevalence area.

    • plos.figshare.com
    xls
    Updated Jun 10, 2023
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    Ian J. Links; Laurence J. Denholm; Marilyn Evers; Lloyd J. Kingham; Robert J. Greenstein (2023). Estimated % of sheep vaccinated in NSW (1999–2009) by prevalence area. [Dataset]. http://doi.org/10.1371/journal.pone.0246411.t008
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 10, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Ian J. Links; Laurence J. Denholm; Marilyn Evers; Lloyd J. Kingham; Robert J. Greenstein
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    New South Wales
    Description

    Estimated % of sheep vaccinated in NSW (1999–2009) by prevalence area.

  11. Total number of sheep inspected in “positive” consignments (1999–2009) by...

    • plos.figshare.com
    xls
    Updated Jun 9, 2023
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    Ian J. Links; Laurence J. Denholm; Marilyn Evers; Lloyd J. Kingham; Robert J. Greenstein (2023). Total number of sheep inspected in “positive” consignments (1999–2009) by prevalence area. [Dataset]. http://doi.org/10.1371/journal.pone.0246411.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 9, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Ian J. Links; Laurence J. Denholm; Marilyn Evers; Lloyd J. Kingham; Robert J. Greenstein
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Total number of sheep inspected in “positive” consignments (1999–2009) by prevalence area.

  12. r

    Genome x Tillage Greenhouse Gas Emission Data, University of Sydney, Plant...

    • researchdata.edu.au
    Updated Mar 24, 2014
    + more versions
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    Robert Simpson; Mark Adams (2014). Genome x Tillage Greenhouse Gas Emission Data, University of Sydney, Plant Breeding Institute, Narrabri NSW, 2013- [Dataset]. https://researchdata.edu.au/genome-x-tillage-nsw-2013/350809
    Explore at:
    Dataset updated
    Mar 24, 2014
    Dataset provided by
    N2O Network
    Authors
    Robert Simpson; Mark Adams
    Time period covered
    Jan 21, 2013 - May 1, 2013
    Area covered
    Description

    This data is part of the Improved carbon and greenhouse gas outcomes through better understanding and management of soils and plant inputs at the farm scale program at the University of Sydney.

  13. Total number of sheep with OJD lesions in “positive” consignments by...

    • plos.figshare.com
    xls
    Updated Jun 9, 2023
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    Ian J. Links; Laurence J. Denholm; Marilyn Evers; Lloyd J. Kingham; Robert J. Greenstein (2023). Total number of sheep with OJD lesions in “positive” consignments by prevalence area. [Dataset]. http://doi.org/10.1371/journal.pone.0246411.t005
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 9, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Ian J. Links; Laurence J. Denholm; Marilyn Evers; Lloyd J. Kingham; Robert J. Greenstein
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Total number of sheep with OJD lesions in “positive” consignments by prevalence area.

  14. Number of flocks vaccinated in the high prevalence area 2007–2012 (Pfizer...

    • plos.figshare.com
    xls
    Updated Jun 10, 2023
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    Ian J. Links; Laurence J. Denholm; Marilyn Evers; Lloyd J. Kingham; Robert J. Greenstein (2023). Number of flocks vaccinated in the high prevalence area 2007–2012 (Pfizer database). [Dataset]. http://doi.org/10.1371/journal.pone.0246411.t010
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 10, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Ian J. Links; Laurence J. Denholm; Marilyn Evers; Lloyd J. Kingham; Robert J. Greenstein
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Number of flocks vaccinated in the high prevalence area 2007–2012 (Pfizer database).

  15. WorkCover News - Issue 61 (June - August 2005)

    • data.nsw.gov.au
    pdf
    Updated Nov 14, 2025
    + more versions
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    NSW Government (2025). WorkCover News - Issue 61 (June - August 2005) [Dataset]. https://data.nsw.gov.au/data/dataset/3-14378-workcover-news---issue-61--june---august-2005-
    Explore at:
    pdf(1108384)Available download formats
    Dataset updated
    Nov 14, 2025
    Dataset provided by
    Government of New South Waleshttp://nsw.gov.au/
    Authors
    NSW Government
    Description

    WorkCover News, the workplace safety and injury management magazine. This Issue includes: - National Farm Safety - WorkCover addresses truck driver safety - Young people and safety at work

    Note: This resource was originally published on opengov.nsw.gov.au. The OpenGov website has been retired. If you have any questions, please contact the Agency Services team at transfer@mhnsw.au

    Agency

    • WorkCover Authority [WorkCover NSW]
  16. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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NSW Department of Climate Change, Energy, the Environment and Water (2025). Earth Observation-On Farm Storage (OFS) Water Volume Monthly [Dataset]. https://data.nsw.gov.au/data/dataset/earth-observation-on-farm-storage-ofs-water-volume-monthly

Earth Observation-On Farm Storage (OFS) Water Volume Monthly

Explore at:
wfs, pdf, arcgis rest serviceAvailable download formats
Dataset updated
Nov 13, 2025
Dataset provided by
Department of Climate Change, Energy, the Environment and Water of New South Waleshttps://www.nsw.gov.au/departments-and-agencies/dcceew
Authors
NSW Department of Climate Change, Energy, the Environment and Water
License

Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
License information was derived automatically

Area covered
Earth
Description

This product delivers a monthly timeseries of estimated water volume for On-Farm Storages (OFS) across the five valleys of the northern Murray-Darling Basin (Border River, Gwydir, Namoi, Macquarie-Castlereagh, and Barwon-Darling). OFS are critical for agricultural water supply, enabling farmers to store water for irrigation and supporting effective water resource management in the face of water scarcity, regulatory requirements, climate variability, and the need for sustainable agricultural practices.

Estimated OFS water volume is derived through a two-step remote sensing approach. First, water surface area is calculated from multispectral satellite imagery (Landsat and Sentinel-2) using a geospatial model [1][2]. Second, LiDAR-derived storage capacity curves are applied to relate the observed surface area to water height above the Australian Height Datum (AHD), enabling calculation of the estimated water volume for each storage [3].

The dataset is updated monthly using the latest available cloud-free satellite imagery, and historical volume are computed from archived images. The timeseries spans from 1987 to the present, providing a consistent monthly record of estimated OFS water volume across the region.

References

[1] https://datasets.seed.nsw.gov.au/dataset/remote-sensing-earth-observation-water-toolkit.

[2] https://www.tandfonline.com/doi/full/10.1080/01431160600589179

[3] https://hls.gsfc.nasa.gov

Note: If you would like to ask a question, make any suggestions, or tell us how you are using this dataset, please visit the NSW Water Hub which has an online forum you can join.

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