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  • Victorian Water Asset Database (VWAD), contains the identification of water assets and their attributes for the state of Victoria. The VWAD includes features such as lakes, rivers, creeks, wetlands, water storages, estuaries, groundwater aquifers, springs, large marine intertidal zones, but does not include specific irrigation and water supply infrastructure such as irrigation channels, bores and irrigation distribution networks.

  • Victorian Water Asset Database (VWAD), contains the identification of water assets and their attributes for the state of Victoria. The VWAD includes features such as lakes, rivers, creeks, wetlands, water storages, estuaries, groundwater aquifers, springs, large marine intertidal zones, but does not include specific irrigation and water supply infrastructure such as irrigation channels, bores and irrigation distribution networks.

  • Land cover mapping data is an annual component of the Victorian Land Use Information System, the VLUIS. The land cover information has been created specifically for the VLUIS using time series analysis of the MOD13Q1 or MYD13Q1 products produced by NASA using data collected by the MODIS sensor and freely available on the Reverb | ECHO website. Ground data is collected annually across Victoria using a stratified random sampling approach for calibration of the annual seasonal curves and validation of the classification output. The ground data is split into three groups with 50% used to develop classification rules, 25% used to produce interim validation results that feed back into the rule development process with the remaining 25% used to independently validate the final classification. Error matrices for each land cover dataset from 2009 have been produced from this final validation. The TIMESAT GUI is used to create smoothed annual time series for the Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and the Red and Near Infrared (NIR) MOD13Q1 or MYD13Q1 bands using the Savitsky-Golay algorithm. A time series of 21 images was used and a suite of 11 seasonal parameters created that each numerically describe features of the annual seasonal curves for each band. In addition the standard deviation of the annual seasonal curve is calculated for each band and used in conjunction with the seasonal parameters. A three-tiered hierarchical classification was developed to assign a dominant land cover class to each pixel. Initially, rules developed using the data mining tool See5 and / or expert knowledge were applied to the seasonal parameters and the annual standard deviation in conjunction with a GIS data-set of water bodies greater than 12.5ha in area to classify each pixel as either Tree, Non-tree or Water based on two data sets from the corporate spatial data library, HY_WATER_AREA_POLY.shp and VM_LITE_HY_WATER_AREA.shp; and are combined to form the water bodies layer. In addition, the primary classes are cross checked using data from preceding and following years to reduce misclassification prior to the secondary classification. A secondary classification developed using rules based on expert knowledge and / or See5 is applied to split the primary class Tree into the secondary classes Native Woody Cover and Treed Production and the primary class Non-tree into the secondary classes Pasture/ Grassland and Crops. Finally, a tertiary classification further divides the secondary class Treed Production into the tertiary classes Hardwood Plantation, Softwood Plantation and evergreen or deciduous Woody Horticulture and the secondary class Crops into the tertiary classes Brassicas, Legumes, Cereals and Non-Woody Horticulture based on rules developed using the data mining tool See5 and modified where appropriate by expert knowledge. Additional information on land cover mapping, including map symbology, can be found on Victorian Resources Online. DOI 10.4226/92/590aba615a44d

  • The Victorian Land Use Information System (VLUIS) 2016 dataset has been created by the Spatial Sciences Group of the Agriculture Victoria Research Division in the Department of Economic Development, Jobs, Transport, and Resources. It covers the entire landmass of Victoria and separately describes the land tenure, land use and land cover across the state at the cadastral parcel level. The methodology for creating the VLUIS is described in Morse-McNabb et al. (2015) with the following notable changes: 1. Land use data provided by the Office of the Valuer-General of Victoria for the 2014 year has been used as a base input. Readily available sources of land use information from government and industry have been used to provide updates to the land tenure and land use components of the 2016 dataset. This update process has not been exhaustive and will continue as new data sources become available. Parcels that have been updated and the source of their updates have been recorded in the attribute table of the dataset. The land cover mapping method remains unchanged to previous versions of the VLUIS. 2. Land parcels within urban areas, mapped in previous versions, have been masked out vastly reducing the size of the 2016 dataset. The data is in the form of an ESRI feature class. To use the VLUIS data correctly it is important to understand the difference between the three components of VLUIS. The Guidelines for land use mapping in Australia: principles, procedures and definitions, Edition 3 published in 2006 by the Commonwealth of Australia, defines them as follows: Land tenure is the form of an interest in land. Some forms of tenure (such as pastoral leases or nature conservation reserves) relate directly to land use and land management practice. Land use means the purpose to which the land cover is committed. Some land uses, such as agriculture, have a characteristic land cover pattern. These usually appear in land cover classifications. Other land uses, such as nature conservation, are not readily discriminated by a characteristic land cover pattern. For example, where the land cover is woodland, land use may be timber production or nature conservation. Land cover refers to the physical surface of the earth, including various combinations of vegetation types, soils, exposed rocks and water bodies as well as anthropogenic elements, such as agriculture and built environments. Land cover classes can usually be discriminated by characteristic patterns using remote sensing. A metadata statement, for the VLUIS product, and ESRI symbology files for the data can be freely downloaded from the VLUIS project page on the Victorian Resources Online website: http://vro.agriculture.vic.gov.au/dpi/vro/vrosite.nsf/pages/vluis DOI 10.4226/92/590abbe6ea3f1

  • The Victorian Land Use Information System (VLUIS) dataset has been created by the Spatial Information Sciences Group of the Agriculture Research Division in the Department of Economic Development, Jobs, Transport, and Resources. The method used to create VLUIS is significantly different to traditional methods used to create land use information and has been designed to create regular and consistent data over time. It covers the entire landmass of Victoria and separately describes the land tenure, land use and land cover for each cadastral parcel across the state, biennially for land tenure and use and annually for land cover; for each year from 2006 to 2015. The data is in the form of a feature class. To use the VLUIS data correctly it is important to understand the difference between the three components of VLUIS. The Guidelines for land use mapping in Australia: principles, procedures and definitions, Edition 3 published in 2006 by the Commonwealth of Australia, defines them as follows: Land tenure is the ownership and leasehold interests in land (VLUIS only reports ownership). Land use means the purpose to which the land cover is committed or the property type. Land cover refers to the physical surface of the earth, including various combinations of vegetation types, soils, exposed rocks and water bodies as well as anthropogenic elements, such as agriculture and built environments. The Victorian Land Use Information System (VLUIS) is an ongoing project designed to maintain and manage the Victorian land use mapping dataset. The methodology is still being refined and as such the dataset is subject to improvements and the release of later versions. It is important you speak to the custodian to be advised of the technical details of the dataset and its utility for your desired use. Land cover classification accuracy varies between classes and the overall classification accuracy may be misleading in terms of the accuracy of an individual class. Users are asked to contact the data custodians for detailed class accuracy information if required for their purposes. Irrigation activity is included when available. The data was not available in 2006-07 and there was incomplete coverage in 2012-13 and therefore the irrigation activity was not included in either of those datasets. The dataset does not replace LandUse100 which is still valid for the time in which it was created (1996 - 2005). A metadata statement, for the VLUIS 2006/07 product, and ESRI symbology files for the data can be freely downloaded from the VLUIS project page: http://vro.depi.vic.gov.au/dpi/vro/vrosite.nsf/pages/vluis DOI: http://dx.doi.org/10.5061/dryad.n08t0

  • The Victorian Land Use Information System (VLUIS) dataset has been created by the Spatial Information Sciences Group of the Agriculture Research Division in the Department of Economic Development, Jobs, Transport, and Resources. The method used to create VLUIS is significantly different to traditional methods used to create land use information and has been designed to create regular and consistent data over time. It covers the entire landmass of Victoria and separately describes the land tenure, land use and land cover for each cadastral parcel across the state, biennially for land tenure and use and annually for land cover; for each year from 2006 to 2015. The data can be provided as a spatial dataset or in tabular format. To use the VLUIS data correctly it is important to understand the difference between the three components of VLUIS. The Guidelines for land use mapping in Australia: principles, procedures and definitions, Edition 3 published in 2006 by the Commonwealth of Australia, defines them as follows: Land tenure is the ownership and leasehold interests in land (VLUIS only reports ownership). Land use means the purpose to which the land cover is committed or the property type. Land cover refers to the physical surface of the earth, including various combinations of vegetation types, soils, exposed rocks and water bodies as well as anthropogenic elements, such as agriculture and built environments. The Victorian Land Use Information System (VLUIS) is an ongoing project designed to maintain and manage the Victorian land use mapping dataset. The methodology is still being refined and as such the dataset is subject to improvements and the release of later versions. It is important you speak to the custodian to be advised of the technical details of the dataset and its utility for your desired use. Land Cover 2014: Land cover classification accuracy statements for the entire state may not be representative of land cover classification accuracy levels in the north-west of the state due to a paucity of ground truth data in this area (particularly west of Swan Hill and north of Sea Lake). Users are advised to use this land cover information with discretion and contact the data custodians for further information if required. Land cover classification accuracy varies between classes and the overall classification accuracy may be misleading in terms of the accuracy of an individual class. Users are asked to contact the data custodians for detailed class accuracy information if required for their purposes. The dataset does not replace LandUse100 which is still valid for the time in which it was created (1996 - 2005). A metadata statement, for the VLUIS 2014/15 product, and ESRI symbology files for the data can be freely downloaded from the VLUIS project page on the Victorian Resources Online website: http://vro.agriculture.vic.gov.au/dpi/vro/vrosite.nsf/pages/vluis DOI 10.4226/92/58e72ebae5380

  • The Victorian Land Use Information System (VLUIS) dataset has been created by the Spatial Information Sciences Group of the Agriculture Research Division in the Department of Economic Development, Jobs, Transport, and Resources. The method used to create VLUIS is significantly different to traditional methods used to create land use information and has been designed to create regular and consistent data over time. It covers the entire landmass of Victoria and separately describes the land tenure, land use and land cover for each cadastral parcel across the state, biennially for land tenure and use and annually for land cover; for each year from 2006 to 2015. The data is in the form of a feature class. To use the VLUIS data correctly it is important to understand the difference between the three components of VLUIS. The Guidelines for land use mapping in Australia: principles, procedures and definitions, Edition 3 published in 2006 by the Commonwealth of Australia, defines them as follows: Land tenure is the ownership and leasehold interests in land (VLUIS only reports ownership). Land use means the purpose to which the land cover is committed or the property type. Land cover refers to the physical surface of the earth, including various combinations of vegetation types, soils, exposed rocks and water bodies as well as anthropogenic elements, such as agriculture and built environments. The Victorian Land Use Information System (VLUIS) is an ongoing project designed to maintain and manage the Victorian land use mapping dataset. The methodology is still being refined and as such the dataset is subject to improvements and the release of later versions. It is important you speak to the custodian to be advised of the technical details of the dataset and its utility for your desired use. Land cover classification accuracy varies between classes and the overall classification accuracy may be misleading in terms of the accuracy of an individual class. Users are asked to contact the data custodians for detailed class accuracy information if required for their purposes. Irrigation activity is included when available. The data was not available in 2006-07 and there was incomplete coverage in 2012-13 and therefore the irrigation activity was not included in either of those datasets. The dataset does not replace LandUse100 which is still valid for the time in which it was created (1996 - 2005). A metadata statement, for the VLUIS 2010/11 product, and ESRI symbology files for the data can be freely downloaded from the VLUIS project page: http://vro.depi.vic.gov.au/dpi/vro/vrosite.nsf/pages/vluis DOI: http://dx.doi.org/10.5061/dryad.n08t0

  • The Victorian Land Use Information System (VLUIS) dataset has been created by the Spatial Information Sciences Group of the Agriculture Victoria Research Division in the Department of Energy, Environment and Climate Action (DEECA). Land use plays a critical role in global cycle of greenhouse gases. Accurate and current land use information is vitally important to properly account land-based emissions, and to develop effective mitigation strategies for climate targets. VLUIS datasets are available for access through https://www.data.vic.gov.au/, and have previously been published for 2006/07, 2008/09, 2010/11, 2012/13, 2014/15 and 2016/17. VLUIS has been revised to provide contemporary and spatially detailed information to support ‘Agriculture Climate Spatial Tool’ (ACST) under Victoria’s ‘Agriculture Sector Pledge’ towards emission reduction targets.

  • Land cover mapping data is an annual component of the Victorian Land Use Information System, the VLUIS. The land cover information has been created specifically for the VLUIS using time series analysis of the MOD13Q1 or MYD13Q1 products produced by NASA using data collected by the MODIS sensor and freely available on the Reverb | ECHO website. Ground data is collected annually across Victoria using a stratified random sampling approach for calibration of the annual seasonal curves and validation of the classification output. The ground data is split into three groups with 50% used to develop classification rules, 25% used to produce interim validation results that feed back into the rule development process with the remaining 25% used to independently validate the final classification. Error matrices for each land cover dataset from 2009 have been produced from this final validation. The TIMESAT GUI is used to create smoothed annual time series for the Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and the Red and Near Infrared (NIR) MOD13Q1 or MYD13Q1 bands using the Savitsky-Golay algorithm. A time series of 21 images was used and a suite of 11 seasonal parameters created that each numerically describe features of the annual seasonal curves for each band. In addition the standard deviation of the annual seasonal curve is calculated for each band and used in conjunction with the seasonal parameters. A three-tiered hierarchical classification was developed to assign a dominant land cover class to each pixel. Initially, rules developed using the data mining tool See5 and / or expert knowledge were applied to the seasonal parameters and the annual standard deviation in conjunction with a GIS data-set of water bodies greater than 12.5ha in area to classify each pixel as either Tree, Non-tree or Water based on two data sets from the corporate spatial data library, HY_WATER_AREA_POLY.shp and VM_LITE_HY_WATER_AREA.shp; and are combined to form the water bodies layer. In addition, the primary classes are cross checked using data from preceding and following years to reduce misclassification prior to the secondary classification. A secondary classification developed using rules based on expert knowledge and / or See5 is applied to split the primary class Tree into the secondary classes Native Woody Cover and Treed Production and the primary class Non-tree into the secondary classes Pasture/ Grassland and Crops. Finally, a tertiary classification further divides the secondary class Treed Production into the tertiary classes Hardwood Plantation, Softwood Plantation and evergreen or deciduous Woody Horticulture and the secondary class Crops into the tertiary classes Brassicas, Legumes, Cereals and Non-Woody Horticulture based on rules developed using the data mining tool See5 and modified where appropriate by expert knowledge. Additional information on land cover mapping, including map symbology, can be found on Victorian Resources Online. DOI 10.26279/5b98592d6b27d

  • Land cover mapping data is an annual component of the Victorian Land Use Information System, the VLUIS. The land cover information has been created specifically for the VLUIS using time series analysis of the MOD13Q1 or MYD13Q1 products produced by NASA using data collected by the MODIS sensor and freely available on the Reverb | ECHO website. Ground data is collected annually across Victoria using a stratified random sampling approach for calibration of the annual seasonal curves and validation of the classification output. The ground data is split into three groups with 50% used to develop classification rules, 25% used to produce interim validation results that feed back into the rule development process with the remaining 25% used to independently validate the final classification. Error matrices for each land cover dataset from 2009 have been produced from this final validation. The TIMESAT GUI is used to create smoothed annual time series for the Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and the Red and Near Infrared (NIR) MOD13Q1 or MYD13Q1 bands using the Savitsky-Golay algorithm. A time series of 21 images was used and a suite of 11 seasonal parameters created that each numerically describe features of the annual seasonal curves for each band. In addition the standard deviation of the annual seasonal curve is calculated for each band and used in conjunction with the seasonal parameters. A three-tiered hierarchical classification was developed to assign a dominant land cover class to each pixel. Initially, rules developed using the data mining tool See5 and / or expert knowledge were applied to the seasonal parameters and the annual standard deviation in conjunction with a GIS data-set of water bodies greater than 12.5ha in area to classify each pixel as either Tree, Non-tree or Water based on two data sets from the corporate spatial data library, HY_WATER_AREA_POLY.shp and VM_LITE_HY_WATER_AREA.shp; and are combined to form the water bodies layer. In addition, the primary classes are cross checked using data from preceding and following years to reduce misclassification prior to the secondary classification. A secondary classification developed using rules based on expert knowledge and / or See5 is applied to split the primary class Tree into the secondary classes Native Woody Cover and Treed Production and the primary class Non-tree into the secondary classes Pasture/ Grassland and Crops. Finally, a tertiary classification further divides the secondary class Treed Production into the tertiary classes Hardwood Plantation, Softwood Plantation and evergreen or deciduous Woody Horticulture and the secondary class Crops into the tertiary classes Brassicas, Legumes, Cereals and Non-Woody Horticulture based on rules developed using the data mining tool See5 and modified where appropriate by expert knowledge. Additional information on land cover mapping, including map symbology, can be found on Victorian Resources Online. DOI 10.26279/5b98601d6b27e