20210305 17244500 1.0 FALSE qld_landuse_current_x 593313.305800 2121665.714600 -3312368.404100 -1007999.232500 1 002 Projected GCS_GDA_1994 Linear Unit: Meter (1.000000) GDA_1994_Australia_Albers <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/2.7.0'><WKT>PROJCS[&quot;GDA_1994_Australia_Albers&quot;,GEOGCS[&quot;GCS_GDA_1994&quot;,DATUM[&quot;D_GDA_1994&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Albers&quot;],PARAMETER[&quot;False_Easting&quot;,0.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,132.0],PARAMETER[&quot;Standard_Parallel_1&quot;,-18.0],PARAMETER[&quot;Standard_Parallel_2&quot;,-36.0],PARAMETER[&quot;Latitude_Of_Origin&quot;,0.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,3577]]</WKT><XOrigin>-20220900</XOrigin><YOrigin>-14227600</YOrigin><XYScale>10000</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>3577</WKID><LatestWKID>3577</LatestWKID></ProjectedCoordinateSystem> 20210305 16195800 20210305 16195800 500000 5000 ISO19139 ISO 19139 Metadata Implementation Specification GML3.2 File Identifier - to be replaced Parent Identifier dataset Shephard Craig Remote Sensing Centre Principal Scientist (07) 3170 5664 AU qlump@qld.gov.au 20210305 ArcGIS Metadata 1.0 Senior Spatial Information Officer (Product Delivery) Department of Natural Resources and Mines Client Outcomes (Product Delivery) (07) 3405 0985 AU Discovery@dnrme.qld.gov.au Open the Queensland Spatial Catalogue (QSpatial). Select the large SEARCH button and all available records are displayed. Select one of the four filter options provided and then the further options within the filter. The resultant search is then displayed. Select your record and complete the order. QS Name 2.0 Download Service Whole of dataset, although clipped areas are available through QSpatial 50 http://qldspatial.information.qld.gov.au/catalogue/custom/search.page?q=%22Land%20use%20mapping%22 File Geodatabase Feature Class 2.0 Download Service File Geodatabase Feature Class 10.5.0 http://insite2.dnr.qld.gov.au/nr_sciences/sir/sir_connect.html Queensland Land Use Queensland Land Use 2018-03-19T00:00:00 2018-03-19T00:00:00 Data Custodian (Assistant D-G, Science Division) Department of Environment and Science Assistant Director-General, Science Division AU Shephard Craig Remote Sensing Centre Principal Scientist (07) 3170 5664 AU qlump@qld.gov.au Shephard Craig Remote Sensing Centre Principal Scientist (07) 3170 5664 AU qlump@qld.gov.au Senior Spatial Information Officer (Product Delivery) Department of Natural Resources and Mines Client Outcomes (Product Delivery) AU Data Custodian (Assistant D-G, Science Division) Department of Environment and Science Assistant Director-General, Science Division AU <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This dataset is a digital map of the most recent land use of Queensland. Land use is classified according to the Australian Land Use and Management Classification (ALUMC).</SPAN></P></DIV></DIV></DIV> Indicates the most current primary use or management objective of the land for Queensland. The Australian Collaborative Land Use and Management Program (ACLUMP) publishes land use information (including location and extent) by assigning a land use code to features (subject to mapping scale limitations). Under version 8 of the Australian Land Use and Management (ALUM) Classification, land use can include commodity type and management practice information. Sources used to compile this information include remotely sensed data, state and national ancillary datasets, field observation and expert opinion. No personal or confidential information is collected as part of the land use mapping process nor contained within the land use datasets. While every care is taken to ensure the accuracy of this information, Queensland Government makes no representations or warranties about its accuracy, reliability, completeness or suitability for any particular purpose and disclaims all responsibility and all liability (including without limitation, liability in negligence) for all expenses, losses, damages (including indirect or consequential damage) and costs which might be incurred as a result of the information being inaccurate or incomplete in any way and for any reason. © The State of Queensland 2019 Shephard Craig Remote Sensing Centre Principal Scientist (07) 3170 5664 AU qlump@qld.gov.au Shephard Craig Remote Sensing Centre Principal Scientist (07) 3170 5664 AU Craig.Shephard@qld.gov.au Queensland ANZLIC Search Words 2007-08-01T00:00:00 ENERGY FISHERIES Freshwater WASTE ENERGY Use HUMAN ENVIRONMENT Planning HUMAN ENVIRONMENT Housing TRANSPORTATION Air MARINE Human Impacts AGRICULTURE Crops INDUSTRY Other ENERGY Coal INDUSTRY Mining ENERGY Petroleum FISHERIES TRANSPORTATION Land HUMAN ENVIRONMENT FISHERIES Aquaculture HEALTH HUMAN ENVIRONMENT Livability WATER Wetlands VEGETATION LAND Cadastre HUMAN ENVIRONMENT Structures and Facilities ENERGY Electricity MARINE Coasts TRANSPORTATION Marine AGRICULTURE Livestock WASTE Solid INDUSTRY Manufacturing WASTE Liquid WASTE Sewage HUMAN ENVIRONMENT Economics LAND Geography AGRICULTURE Horticulture INDUSTRY Service INDUSTRY HUMAN ENVIRONMENT Urban Design UTILITIES LAND LAND Use ENERGY Renewable WATER Rivers TRANSPORTATION WATER Surface INDUSTRY Primary WATER MARINE Estuaries FORESTS Agriforestry FORESTS FISHERIES Recreational WATER Lakes FORESTS Natural FORESTS Plantation AGRICULTURE Irrigation FISHERIES Marine AGRICULTURE Common Search Terms 2018-03-19T00:00:00 QLUMP ALUMC Australia Land Use and Management Classification Queensland Land Use Mapping Program ENERGY QLUMP FISHERIES Freshwater WASTE ENERGY Use HUMAN ENVIRONMENT Planning HUMAN ENVIRONMENT Housing ALUMC TRANSPORTATION Air Australia Land Use and Management Classification MARINE Human Impacts AGRICULTURE Crops INDUSTRY Other ENERGY Coal INDUSTRY Mining ENERGY Petroleum FISHERIES TRANSPORTATION Land HUMAN ENVIRONMENT FISHERIES Aquaculture HEALTH HUMAN ENVIRONMENT Livability WATER Wetlands VEGETATION LAND Cadastre HUMAN ENVIRONMENT Structures and Facilities ENERGY Electricity MARINE Coasts TRANSPORTATION Marine AGRICULTURE Livestock WASTE Solid INDUSTRY Manufacturing WASTE Liquid WASTE Sewage HUMAN ENVIRONMENT Economics LAND Geography AGRICULTURE Horticulture INDUSTRY Service INDUSTRY HUMAN ENVIRONMENT Urban Design UTILITIES LAND LAND Use ENERGY Renewable WATER Rivers TRANSPORTATION WATER Surface INDUSTRY Primary Queensland Land Use Mapping Program WATER Queensland MARINE Estuaries FORESTS Agriforestry FORESTS FISHERIES Recreational WATER Lakes FORESTS Natural FORESTS Plantation AGRICULTURE Irrigation FISHERIES Marine AGRICULTURE This material is licensed under a Creative Commons - Attribution 4.0 Australia licence. The Department requests attribution in the following manner: Copyright State of Queensland (Department of Environment and Science) 2018. Updated data available at http://qldspatial.information.qld.gov.au/catalogue/ The Australian Collaborative Land Use and Management Program (ACLUMP) publishes land use information (including location and extent) by assigning a land use code to features (subject to mapping scale limitations). Under version 8 of the Australian Land Use and Management (ALUM) Classification, land use can include commodity type and management practice information. Sources used to compile this information include remotely sensed data, state and national ancillary datasets, field observation and expert opinion. No personal or confidential information is collected as part of the land use mapping process nor contained within the land use datasets. While every care is taken to ensure the accuracy of this information, Queensland Government makes no representations or warranties about its accuracy, reliability, completeness or suitability for any particular purpose and disclaims all responsibility and all liability (including without limitation, liability in negligence) for all expenses, losses, damages (including indirect or consequential damage) and costs which might be incurred as a result of the information being inaccurate or incomplete in any way and for any reason. © The State of Queensland 2019 This material is licensed under a Creative Commons - Attribution 4.0 Australia licence. The Department requests attribution in the following manner: Copyright State of Queensland (Department of Environment and Science) 2018. Updated data available at http://qldspatial.information.qld.gov.au/catalogue/ ISO 19115 (mapped from Qld Govt Information Security Standard IS18) <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This material is licensed under a Creative Commons - Attribution 4.0 Australia licence. The Department requests attribution in the following manner: Copyright State of Queensland (Department of Environment and Science) 201</SPAN><SPAN>9</SPAN><SPAN>. Updated data available at http://qldspatial.information.qld.gov.au/catalogue/</SPAN></P></DIV></DIV></DIV> <DIV STYLE="text-align:Left;"><P><SPAN>The Australian Collaborative Land Use and Management Program (ACLUMP) publishes land use information (including location and extent) by assigning a land use code to features (subject to mapping scale limitations). Under version 8 of the Australian Land Use and Management (ALUM) Classification, land use can include commodity type and management practice information. Sources used to compile this information include remotely sensed data, state and national ancillary datasets, field observation and expert opinion. No personal or confidential information is collected as part of the land use mapping process nor contained within the land use datasets. </SPAN></P><P><SPAN /></P><P><SPAN>While every care is taken to ensure the accuracy of this information, Queensland Government makes no representations or warranties about its accuracy, reliability, completeness or suitability for any particular purpose and disclaims all responsibility and all liability (including without limitation, liability in negligence) for all expenses, losses, damages (including indirect or consequential damage) and costs which might be incurred as a result of the information being inaccurate or incomplete in any way and for any reason.</SPAN></P><P><SPAN /></P><P><SPAN>© The State of Queensland 2019</SPAN></P></DIV> Spatial Information Resource (SIR) Feature Class 2018-03-19T00:00:00 RSC.QLD_LANDUSE_CURRENT_X\RSC.QLD_LANDUSE_CURRENT_X 50000 50 Esri ArcGIS 12.7.0.26828 The dataset is a product of the Queensland Land use Mapping Program (QLUMP) and was produced by the Queensland Government. The dataset comprises an ESRI vector geodatabase (10.5.6491) at a nominal scale of 1:50,000. The layer is a polygon dataset with each feature having attributes describing land use. Land use is classified according to the Australian Land Use and Management Classification (ALUMC) Version 8, October 2016. Five primary classes are identified in order of increasing levels of intervention or potential impact on the natural landscape. Water is included separately as a sixth primary class. Under the three-level hierarchical structure, the minimum attribution level for land use mapping in Queensland is secondary land use. Primary and secondary levels relate to land use (i.e. the principal use of the land in terms of the objectives of the land manager). The tertiary level includes data on commodities or vegetation, (e.g. crops such as cereals and oil seeds). Where required and possible, attribution is performed to tertiary level. QLUMP maps the land use classes of sugar and cotton consistently to tertiary level. Under ACLUMP version 8, we have also mapped all conservation, intensive animal husbandry, residential, services, utilities, and transport and communication land use classes to tertiary level. Since 2015, QLUMP includes commodity level classification of banana, avocado, macadamia and mango orchards (dryland and irrigated). Refer to the contact position for additional information regarding source data. Further information relating to land use mapping can be found at http://www.qld.gov.au/environment/land/vegetation/mapping/qlump/ and http://www.agriculture.gov.au/abares/aclump/land-use/. 1 137.244792 154.104564 -8.177429 -30.308293 Public Metadata Access Level Completeness of coverage: All spatial and attribute data are complete for the entire dataset. Completeness of classification: Land use features were captured from a range of source data. Mapping from satellite imagery was generally undertaken to the smallest discrete unit able to be visually interpreted using the visual cues of colour, texture and pattern (approximately one hectare). Land use information from ancillary datasets was captured at the scale of the source data. The resulting land use dataset therefore contains features at a range of scales and resolutions. To promote consistency in the way land use features are handled and represented, project guidelines specify minimum data resolution standards appropriate to various mapping scales. At a scale of 1:50,000 the surface area of the smallest mapped feature is two hectares and minimum width for linear features is 50 metres. Land use classes were assigned according to the Australian Land Use and Management Classification Version 8, October 2016 (Australian Bureau of Agriculture and Resource Economics and Sciences, 2016). To ensure the completeness of the data, the topology rules of "Must Not Overlap" and "Must Not Have Gaps" are valid. The data is to a standard determined as fit for the purpose for which it was collected. 2018-03-19T00:00:00 The data is to a standard determined as fit for the purpose for which it was collected. true Delineation of land use attributes was based on visual interpretation of multi-temporal Landsat, SPOT6 and SPOT7 satellite imagery, Earth-i imagery, Planet imagery, high-res ortho photography, scanned aerial photography as well as ancillary data sets containing land use information, field observations and personal communication with regional Queensland Government staff. Assignment of land use classes was based on ALUMC Version 8 (October 2016). An independent accuracy assessment of the completed dataset was undertaken using a modified version of the methods described in "Guidelines for land use mapping in Australia: principles, procedures and definitions", 4th edition, 2011 (ABARES). Each region or catchment have independant accuracy assessments and have an accuracy of at least 80%. See the full accuracy assessment in the report as: https://www.qld.gov.au/environment/land/vegetation/mapping/qlump-reports/. Points were assessed based on a stratified random sampling strategy, using the map classes (area and frequency) as the strata. The column prop (%) is the relative proportion in area of the classes that were assessed, not of the region as a whole. Note also that the Grazing modified pastures (dryland 3.2.0 and irrigated 4.2.0) were excluded from the validation as identifying and separating these using imagery, aerial photography and field observation is known to be unreliable. 2018-03-19T00:00:00 The data is to a standard determined as fit for the purpose for which it was collected. true Land use polygons were derived from datasets with a range of scales, as well as on-screen hand digitising from imagery. The positional accuracy of source datasets was variable ranging from approximately 25 metres for information derived from 1:50,000 scale datasets, to 50 metres for information derived from 1:100,000 scale datasets. Hand digitising was undertaken to an error of approximately one millimetre (50 metres at map scale). Where there were inconsistencies between polygon boundaries defined by source datasets (vector coverages) and imagery, they were adjusted to conform to the imagery as this was considered to have higher positional accuracy. An independent accuracy assessment of the completed dataset was undertaken using a modified version of the methods described in "Guidelines for land use mapping in Australia: principles, procedures and definitions", 4th edition, 2011 (ABARES). Each region or catchment have independant accuracy assessments and have an accuracy of at least 80%. See the full accuracy assessment in the report as: https://www.qld.gov.au/environment/land/vegetation/mapping/qlump-reports/. Points were defined based on a stratified random sampling strategy, using the map classes (area and frequency) as the strata. The column prop (%) is the relative proportion in area of the classes that were assessed, not of the region as a whole. Note also that the Grazing modified pastures (dryland 3.2.0 and irrigated 4.2.0) were excluded from the validation as identifying and separating these using imagery, aerial photography and field observation is known to be unreliable. 2018-03-19T00:00:00 The data is to a standard determined as fit for the purpose for which it was collected. true Several classes were highlighted as being susceptible to misclassification and issues arose which increased uncertainty in others. Livestock grazing occurs on a range of pasture types including native and exotic as well as mixtures of both. Identifying and separating these using imagery, aerial photography and field observation is difficult and unreliable. Areas of pasture which appeared to be harvested for fodder or grazed often were mapped as Cropping (3.3.0). This may contribute to an over-estimation of cropping in the region. Other areas mapped as grazing include road reserves, cleared and uncleared land adjacent to rivers and streams as well as land immediately adjacent to or between cropped paddocks. Other minimal use (1.3.0) and Remnant native cover (1.3.3) may also be confused with this class. The appearance of these can be highly variable and classification may therefore not be consistent. The areas mapped as cropping and irrigated cropping include features such as tracks and drainage lines which are too small to be mapped separately at the scale of 1:50,000. Guidelines for mapping the class 'Intensive animal husbandry' (5.2.0) have changed in ALUMC Version 8. Only the infrastructure associated with intensive animal production should be classified as 5.2.0 (e.g. dairy sheds, 5.2.1). The surrounding pastures should generally mapped as 'Grazing modified pastures' (3.2.0) or 'Grazing irrigated modified pastures' (4.2.0). Rural residential with Agriculture (5.4.2) areas are a source of possible error. Properties on the fringes of suburban settlements, hobby farms and subdivisions in isolated localities with comparatively small lot sizes were mapped to this class. The use of QVAS (valuation information) was useful, based on whether or not the land owner was classified as a primary producer. This class may be misclassified with Grazing native vegetation (2.1.0) and Other Minimal Use (1.3.0), especially on larger properties. The distinction between dryland and irrigated cropping (3.3.0 and 4.3.0) was not always evident and it is likely there is some misclassification in these classes. Proximity to water sources (watercourse or dam) and local knowledge was used to confirm areas of irrigation as much as possible. Areas mapped as irrigated cropping are potentially only irrigated on a supplementary basis and may not have actually been irrigated in the current mapping year. The Queensland Herbarium's wetlands dataset provided the basis for mapping marsh/wetlands (6.5.0), lakes (6.1.0) and reservoir or dams (6.2.0). The ephemeral nature of many of these can lead to confusion insofar as they may be present in imagery of one date and either absent or of differing extent in imagery of subsequent or previous dates. For this reason, only wetlands, lakes and dams that were commonly or permanently inundated were included in the dataset. As a result, there is likely to be errors & omissions and some disagreement in the mapping of features such as farm dams, reservoirs, lakes, wetlands & other water features. Many water features whilst exceeding the minimum mappable area requirements, do not meet the criteria for linear or uniform features. The land use datasets are a snapshot of what was interpreted as the primary land use for a particular year. However, effort was given to distinguishing between an actual land use change and a rotation. For example, an area that is usually cropped, but is not used for that particular purpose in the year of interest, was still mapped as cropping even though no crop was present in that year. This was not considered an actual land use change, but rather a rotation, as the primary land use for that paddock would still be cropping. The revised land use mapping has been improved through the interpretation of the most suitable imagery available. On occasion this will be Landsat (30m), which raises some uncertainty in respect of accurately classifying the intensive land use classes. The minimum mapping unit (2ha) also contributes to the uncertainty through the aggregation of otherwise individual land use features, particularly at cadastral parcel level. These limitations may therefore lead to omission and commission errors in the classification of the intensive land use classes in earlier mapping products and the land use change products which are derived from them. An independent accuracy assessment of the completed dataset was undertaken using a modified version of the methods described in "Guidelines for land use mapping in Australia: principles, procedures and definitions", 4th edition, 2011 (ABARES). Each region or catchment have independant accuracy assessments and have an accuracy of at least 80%. See the full accuracy assessment in the report as: https://www.qld.gov.au/environment/land/vegetation/mapping/qlump-reports/. Points were assessed based on a stratified random sampling strategy, using the map classes (area and frequency) as the strata. The column prop (%) is the relative proportion in area of the classes that were assessed, not of the region as a whole. Note also that the Grazing modified pastures (dryland 3.2.0 and irrigated 4.2.0) were excluded from the validation as identifying and separating these using imagery, aerial photography and field observation is known to be unreliable. 2018-03-19T00:00:00 The data is to a standard determined as fit for the purpose for which it was collected. true Several classes were highlighted as being susceptible to misclassification and issues arose which increased uncertainty in others. Livestock grazing occurs on a range of pasture types including native and exotic as well as mixtures of both. Identifying and separating these using imagery, aerial photography and field observation is difficult and unreliable. Areas of pasture which appeared to be harvested for fodder or grazed often were mapped as Cropping (3.3.0). This may contribute to an over-estimation of cropping in the region. Other areas mapped as grazing include road reserves, cleared and uncleared land adjacent to rivers and streams as well as land immediately adjacent to or between cropped paddocks. Other minimal use (1.3.0) and Remnant native cover (1.3.3) may also be confused with this class. The appearance of these can be highly variable and classification may therefore not be consistent. The areas mapped as cropping and irrigated cropping include features such as tracks and drainage lines which are too small to be mapped separately at the scale of 1:50,000. Guidelines for mapping the class 'Intensive animal husbandry' (5.2.0) have changed in ALUMC Version 8. Only the infrastructure associated with intensive animal production should be classified as 5.2.0 (e.g. dairy sheds, 5.2.1). The surrounding pastures should generally mapped as 'Grazing modified pastures' (3.2.0) or 'Grazing irrigated modified pastures' (4.2.0). Rural residential with Agriculture (5.4.2) areas are a source of possible error. Properties on the fringes of suburban settlements, hobby farms and subdivisions in isolated localities with comparatively small lot sizes were mapped to this class. The use of QVAS (valuation information) was useful, based on whether or not the land owner was classified as a primary producer. This class may be misclassified with Grazing native vegetation (2.1.0) and Other Minimal Use (1.3.0), especially on larger properties. The distinction between dryland and irrigated cropping (3.3.0 and 4.3.0) was not always evident and it is likely there is some misclassification in these classes. Proximity to water sources (watercourse or dam) and local knowledge was used to confirm areas of irrigation as much as possible. Areas mapped as irrigated cropping are potentially only irrigated on a supplementary basis and may not have actually been irrigated in the current mapping year. The Queensland Herbarium's wetlands dataset provided the basis for mapping marsh/wetlands (6.5.0), lakes (6.1.0) and reservoir or dams (6.2.0). The ephemeral nature of many of these can lead to confusion insofar as they may be present in imagery of one date and either absent or of differing extent in imagery of subsequent or previous dates. For this reason, only wetlands, lakes and dams that were commonly or permanently inundated were included in the dataset. As a result, there is likely to be errors & omissions and some disagreement in the mapping of features such as farm dams, reservoirs, lakes, wetlands & other water features. Many water features whilst exceeding the minimum mappable area requirements, do not meet the criteria for linear or uniform features. The land use datasets are a snapshot of what was interpreted as the primary land use for a particular year. However, effort was given to distinguishing between an actual land use change and a rotation. For example, an area that is usually cropped, but is not used for that particular purpose in the year of interest, was still mapped as cropping even though no crop was present in that year. This was not considered an actual land use change, but rather a rotation, as the primary land use for that paddock would still be cropping. The revised land use mapping has been improved through the interpretation of the most suitable imagery available. On occasion this will be Landsat (30m), which raises some uncertainty in respect of accurately classifying the intensive land use classes. The minimum mapping unit (2ha) also contributes to the uncertainty through the aggregation of otherwise individual land use features, particularly at cadastral parcel level. These limitations may therefore lead to omission and commission errors in the classification of the intensive land use classes in earlier mapping products and the land use change products which are derived from them. An independent accuracy assessment of the completed dataset was undertaken using a modified version of the methods described in "Guidelines for land use mapping in Australia: principles, procedures and definitions", 4th edition, 2011 (ABARES). Each region or catchment have independant accuracy assessments and have an accuracy of at least 80%. See the full accuracy assessment in the report as: https://www.qld.gov.au/environment/land/vegetation/mapping/qlump-reports/. Points were assessed based on a stratified random sampling strategy, using the map classes (area and frequency) as the strata. The column prop (%) is the relative proportion in area of the classes that were assessed, not of the region as a whole. Note also that the Grazing modified pastures (dryland 3.2.0 and irrigated 4.2.0) were excluded from the validation as identifying and separating these using imagery, aerial photography and field observation is known to be unreliable. 2018-03-19T00:00:00 The data is to a standard determined as fit for the purpose for which it was collected. true The land use features were identified using satellite image and ancillary data interpretation. The mapping is verified through field mapping and/or meeting with local officers or extension officers. Validation is conducted at the desktop using a stratified random sample of points. The existing 1999 baseline (or later where available) land use dataset (vector) formed the basis for the 2009, 2011, 2012, 2013, 2015 and 2016 land use mapping. The datasets were then updated primarily by interpretation of multi-temporal Landsat, SPOT5/6 imagery, Earth-i imagery, Planet imagery, high-res orthophotography, scanned aerial photography and inclusion of expert local knowledge. This was performed in an ESRI ArcSDE geodatabase replication infrastructure. The DCDB, QVAS, Estates, Nature Refuge, Plantation, Queensland Herbarium Wetlands, Recreation Land and other point data (piggeries, aquaculture, feedlots, poultry farms, saw mills, sugar mills and cotton gins) datasets were used to assist in identification and delineation of property and land use type boundaries. Digitised areas of uniform land use type were assigned to land use classes according to ALUMC Version 8 (October 2016). This "current" land use mapping product presents a complete state-wide land use map of Queensland, after collating the most current land use datasets within a single mapping layer. An independent validation was undertaken to assess the thematic (attribute) and spatial accuracy under the ALUM classification. Please refer to the original source data for the validation results. Shephard Craig Remote Sensing Centre Principal Scientist (07) 3170 5664 AU Craig.Shephard@qld.gov.au Shephard Craig Remote Sensing Centre Principal Scientist (07) 3170 5664 AU Craig.Shephard@qld.gov.au Queensland Government Land use mapping; Landsat TM, ETM+ and OLI imagery; Spot5/6/7 imagery; Earth-i imagery; Planet imagery; High-res ortho photography through the Spatial Imagery Subscription Plan (SISP); Queensland Digital Cadastral Database (DCDB), Queensland Valuation and Sales Database (QVAS); Queensland Estates; Scanned aerial photography (1997-2017). Additional verbal & written information on land uses & their locations was obtained from regional Queensland Government officers, Local Government Authorities, land owners & managers, private industry as well as from field observations. 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Esri Sequential unique whole numbers that are automatically generated. YEAR Year SmallInteger 2 0 0 Year of land use observation QLUMP Integer (4 digit) for year of observation QLUMP_CODE QLUMP_Code SmallInteger 2 0 0 Land use classification code for internal use QLUMP String ALUM_CODE ALUM_Code String 10 0 0 ALUM classification land use code ALUM Classification String PRIMARY Primary String 150 0 0 Primary land use classification as string ALUM Classification String SECONDARY Secondary String 150 0 0 Secondary land use classification as string ALUM Classification String TERTIARY Tertiary String 150 0 0 Tertiary land use classification as string ALUM Classification String COMMODITY Commodity String 150 0 0 Commodity observation as string ALUM Classification String MANAGEMENT Management String 150 0 0 Land management practice observation as string ALUM Classification String RULEID RULEID Integer 4 0 0 Internal use QLUMP Integer OVERRIDE OVERRIDE Blob 0 0 0 Internal use QLUMP Blob SHAPE Shape Geometry 0 0 0 Feature geometry. Esri Coordinates defining the features. SHAPE_Length SHAPE_Length Double 8 0 0 Length of feature in internal units. Esri Positive real numbers that are automatically generated. SHAPE_Area SHAPE_Area Double 8 0 0 Area of feature in internal units squared. Esri Positive real numbers that are automatically generated.