Merged and anonymised LPIS and N&P for 2019 The following attributes are available: 1) LPIS Data * HOLDING_ID, * LNU_PARCEL_ID, * DIGITISED_AREA, * MEA, * CLAIMED_AREA, * CROP_DESC, * COMMONAGE_INDICATOR, * COMMONAGE_FRACTION, * SUB_DIVISION ID, * GLAS Farm Status; * ANC Indicator, * GLAS Indicator, * Organics Status, * EFA Second Crop, * EPSG Indicator, * Crop Description, * Livestock Load, * Date of information, * Geometry. 2) Non-claimable areas (Reds Line datasets) * Non-claimable areas (Redline): * LNU, Exclusion Type, % Exclusion, * Manual Deduction Type, * Manual Deduction %, * Fixed Area Reduction Type, * ID, * Exclusion Type, * Land Cover Land Use Type, * Glas Area, * Habitat Area, * Date of information, * Geometry, * iNet geometries delineating subdivisions, 3) Dual Claims, partnership data * SPH_SPS_HOLDING_ID, * LNU_PARCEL_ID
Merged and anonymised LPIS and N&P for 2020 The following attributes are available: 1) LPIS Data * HOLDING_ID, * LNU_PARCEL_ID, * DIGITISED_AREA, * MEA, * CLAIMED_AREA, * CROP_DESC, * COMMONAGE_INDICATOR, * COMMONAGE_FRACTION, * SUB_DIVISION ID, * GLAS Farm Status; * ANC Indicator, * GLAS Indicator, * Organics Status, * EFA Second Crop, * EPSG Indicator, * Crop Description, * Livestock Load, * Date of information, * Geometry. 2) Non-claimable areas (Reds Line datasets) * Non-claimable areas (Redline): * LNU, Exclusion Type, % Exclusion, * Manual Deduction Type, * Manual Deduction %, * Fixed Area Reduction Type, * ID, * Exclusion Type, * Land Cover Land Use Type, * Glas Area, * Habitat Area, * Date of information, * Geometry, * iNet geometries delineating subdivisions, 3) Dual Claims, partnership data * SPH_SPS_HOLDING_ID, * LNU_PARCEL_ID
Merged and anonymised LPIS and N&P for 2021 The following attributes are available: 1) LPIS Data * HOLDING_ID, * LNU_PARCEL_ID, * DIGITISED_AREA, * MEA, * CLAIMED_AREA, * CROP_DESC, * COMMONAGE_INDICATOR, * COMMONAGE_FRACTION, * SUB_DIVISION ID, * GLAS Farm Status; * ANC Indicator, * GLAS Indicator, * Organics Status, * EFA Second Crop, * EPSG Indicator, * Crop Description, * Livestock Load, * Date of information, * Geometry. 2) Non-claimable areas (Reds Line datasets) * Non-claimable areas (Redline): * LNU, Exclusion Type, % Exclusion, * Manual Deduction Type, * Manual Deduction %, * Fixed Area Reduction Type, * ID, * Exclusion Type, * Land Cover Land Use Type, * Glas Area, * Habitat Area, * Date of information, * Geometry, * iNet geometries delineating subdivisions, 3) Dual Claims, partnership data * SPH_SPS_HOLDING_ID, * LNU_PARCEL_ID
Merged and anonymised LPIS and N&P (Nitrates and Phosphorus) for 2022 The following attributes are available: 1) LPIS Data • HOLDING_ID, • LNU_PARCEL_ID, • DIGITISED_AREA, • MEA, • CLAIMED_AREA, • CROP_DESC, • COMMONAGE_INDICATOR, • COMMONAGE_FRACTION, • SUB_DIVISION ID, • GLAS Farm Status; • ANC Indicator, • GLAS Indicator, • Organics Status, • EFA Second Crop, • EPSG Indicator, • Crop Description, • Livestock Load, • Date of information, • Geometry. 2) Non-claimable areas (Reds Line datasets) • Non-claimable areas (Redline): • LNU, Exclusion Type, % Exclusion, • Manual Deduction Type, • Manual Deduction %, • Fixed Area Reduction Type, • ID, • Exclusion Type, • Land Cover Land Use Type, • Glas Area, • Habitat Area, • Date of information, • Geometry, • iNet geometries delineating subdivisions, 3) Dual Claims, partnership data • SPH_SPS_HOLDING_ID, • LNU_PARCEL_ID
Anonymised LPIS data for 2023. The following attributes are available 1) LPIS Data: Applicant Herd, Herd Number, Parcel Label, Claimed Area, Crop, Digitised Area, Eligible Hectare, Commonage Denominator, Commonage Numerator, Subdivision, Commonage Indicator, Owner/Leased/Rented, Grassland, Tillage, Permanent, Arable, Straw Incorporation Measure Indicator, Basic Income Support for Sustainability, Eco-Schemes, Complementary Redistributive Income Support for Sustainability, Protein Aid, Complementary income support for young farmers, Areas of Natural Constraints, ACRES, Organic, Straw Incorporation Measure, Manual Deduction Area, Fixed Area Deduction Area, Fixed Area Deduction Description, Manual Deduction Description, Date of Extract 2) LPIS Sub Features Data: Parcel Label, Feature Label, Feature Description, Percentage, Gross Area.
The Department of Agriculture, Food and the Marine (DAFM) provide data for the private forest estate only. These data include new forests planted up to the end of 2020. Within the dataset provided is a file showing the attribute information such as: Species List, Land use types, Ownership, Polygon area in hectares.
The Department of Agriculture, Food and the Marine (DAFM) provide data for the private forest estate only. These data include new forests planted up to the end of 2021. Within the dataset provided is a file showing the attribute information such as: Species List, Land use types, Ownership, Polygon area in hectares.
The Department of Agriculture, Food and the Marine (DAFM) provide data for the private forest estate only. These data include new forests planted up to the end of 2023. Within the dataset provided is a file showing the attribute information such as: Species List, Land use types, Ownership, Polygon area in hectares.
Water Quality Review Implementation Map for 2024 - Maximum stocking rate of 220 kg livestock manure nitrogen per hectare applies for Nitrates Derogation holdings in these areas for 2024.
Following Storm Darragh and Storm Éowyn during the winter of 2024/2025, and noting that many forests have been windblown around the country, Minister for Agriculture, Food and the Marine, Martin Heydon, and Minister of State for Forestry, Horticulture and Farm Safety, Michael Healy-Rae, invited key stakeholders to join department officials on a taskforce to ensure that storm-damaged forests were managed safely and appropriately. A Forestry Windblow Taskforce was set up to quantify forest damage and to identify approaches to facilitate the mobilisation of wind damaged timber. Part of the Taskforce’s work involved initiating a detailed mapping assessment using high-resolution satellite imagery to provide information at a local or forest stand level scale. The detailed assessment of windblow damage was undertaken using high resolution satellite imagery from SkySat, and supplemented with pre and post storm Sentinel-2 and PlanetScope satellite data. In addition, drone imagery was also acquired for a number of specific locations. The mapping exercise relied on the tasking of SkySat imagery during cloud-free weather conditions to acquire the necessary imagery data. The mapping was conducted largely between early February and the beginning of April 2025. The mapping effort focused on a target area of interest where the damage was deemed most likely to have occurred. These target areas were forests stands that were predominantly coniferous species and at least 15 years of age. These age and species criteria were used to filter both Coillte’s sub-compartment database and DAFM’s private forest dataset to confine the wind damage mapping exercise to the most relevant forests. The windblow mapping exercise utilised a range of available EO datasets of varying spatial and temporal resolution which included: SkySat: 75% (c. 0.50 m resolution), Sentinel-2/PlanetScope: 20% (c. 10 m resolution/c. 3 m resolution), and drone imagery: 5% ( c. 0.2 m resolution). The national estimate of private wind damage area (11,414 ha) as included in the private forest wind damage spatial database is within approximately +/- 500 hectares of the actual windblown private forest area. This uncertainty is due in part to the fact that for some parts of the country, SkySat satellite imagery has not yet been acquired. It is expected that there will be an ongoing refinement of the private forest windblow area estimate when new SkySat or other Earth Observation data becomes available over the coming months. As part of this mapping exercise, “older” windblown areas, i.e. windblown forest areas that are more than 4 years old, were also identified and mapped. It is estimated these damage forest areas represent between 750 and 1,000 hectares of the total national area estimate of private wind damaged forest. The area of wind damage in broadleaf stands may be greater than identified in the private forest wind damage database given the focus in the mapping exercise on coniferous species that were at least 15 years of age. This is also due in part to the fact that the identification of windblow in broadleaf stands is more challenging, particularly if the damage impacts individual trees. The output from the mapping assessment is an ESRI Shapefile polygon database of wind damaged, privately owned forest areas greater than or equal to 0.1 hectares. The Shapefile is provided in the Irish Transverse Mercator geographic coordinate system. The main attribute included the spatial database table is area in hectares for each wind damaged forest area delineated. These data are provisional in that they are a record of DAFM data holding in relation to private wind damaged forest at this time (May 2025). They are not published as legal definitions of the current actuality with regard to their geographic extent. They may contain errors and omissions and it should also be noted that the data cannot be taken as being absolutely current. Therefore they should be treated as indicative of the actual geographic situation. The Department of Agriculture, Food and the Marine will accept no liability for any loss or damage suffered by those using this data for any purpose whatsoever.