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  • A spatial map layer of soil type (Australian Soil Classification) for Victoria. The harmonised map consists of 3,300 land units (totaling about 225,000 polygons) derived from around 100 soil and land surveys carried out in Victoria over the past 70 years. The land units have been attributed according to the Australian Soil Classification (Order and Suborder levels of the classification scheme) based on their likely dominant soil type. Particular attention was given to harmonising land units across survey boundaries. A reliability index has been assigned to each land unit based on the quality and relevance of the originating survey, providing a qualitative reliability measure to support interpretation and data use. Soil site data contained in the Victorian Soil Information System (VSIS), and information on the Victorian Resources Online (VRO) website and original study reports have been combined with landscape knowledge to develop the new maps. Data from approximately 10,000 existing sites recorded, mostly recorded in the VSIS have been used. The soil type is based on land mapping conducted at different times, at variable scale, and for different purposes. Land units are therefore of variable scale and quality in relation to the soil they are representing. Many units will be comprised of multiple soil types and a range of soil properties, and local variability (e.g. at paddock scale level) can also sometimes be high. The mapping, therefore, is intended to represent the dominant, or most prevalent, broad soil type within the map unit. It is therefore adequate for regional or state-wide overviews but may not often be accurate enough for localised or within-farm assessments. For more detailed soil and land information, users are advised to refer to the original land study for any given map unit (e.g. via Victorian Resources Online website).

  • 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

  • A set of Digital Soil Maps (mean, 5th and 95th percentile prediction values) of soil silt % across Victoria in geotiff format. Silt is considered to be the 2 - 20 um mass fraction of the < 2mm soil material. Grids of key soil properties have been produced for Victoria. These grids, in raster format, provide prediction and confidence interval values for key soil properties at a 90 m grid resolution for six set depths; 0 to 5 cm, 5 to 15 cm, 15 to 30 cm, 30 to 60 cm, 60 to 100 cm and 100 to 200 cm, across Victoria. The grids have been designed to meet the specifications created by GlobalSoilMap (www.globalsoilmap.net) to develop and deliver detailed soil information in a consistent form. The grids are a spatial interpolation of key soil properties to support modelling and decision making in resource management, agricultural production, land use policy and planning, and in further research such as ecosystem modelling. The methodology used to develop the Soil Grids of Victoria has been based on that refined by the Australian Soil and Landscape Grid. Data and knowledge embedded into existing soil related datasets, e.g. soil profile and land mapping collections, have been key inputs. Whilst the new maps show an immense amount of fine scale detail, and are our best spatially continuous and exhaustive estimates of soil attributes across all of Victoria, they are most appropriately used for assessments of regional to state-wide trends of soil properties and their relationship with their environment and pedogenesis. Care should be taken when using the grids for local assessments and it is recommended that the confidence intervals are included at this scale.

  • This dataset is the primary data output from the Wimmera land resource assessment project undertaken in 2004-06. It contains soil and land information at a scale of 1:100 000 for all freehold land in the Wimmera region of Victoria. The dataset was developed by the project "A Land Resource Assessment of the Wimmera Region" conducted by Robinson et al. (2006). This project was undertaken by DPI's PIRVic Division for the Wimmera Catchment Management Authority to provide consistent land resource information across the region. It utilised data from existing soil surveys at varying scales and intensity conducted over the previous 60 years, remote sensing information and additional field work to develop updated 1:100 000 scale soil/landform mapping across the region. The nominal scale of the dataset is appropriate for broadscale assessment of land capability and regional planning. At the map scale of this dataset soil-landform units are not homogeneous. For each defined soil-landform unit, soil types were identified and an assessment of their risk of degradation (compaction, erosion, sodicity and acidity) was made. Importantly it should be noted that soil attributes (for example texture, sodicity, pH) are expected to vary between acquired soil sites. As the variability of soil attributes within a map unit is difficult to predict, it is important to note that representative soils should be used as a guide only. The study report describing the project methodology and dataset attributes is available from the Victorian Resources Online website. DOI 10.4226/92/58e729e8aea3e

  • A set of Digital Soil Maps (mean, 5th and 95th percentile prediction values) of soil clay % across Victoria in geotiff format. Soil clay is considered to be the <2 um mass fraction of the < 2mm soil material. Grids of key soil properties have been produced for Victoria. These grids, in raster format, provide prediction and confidence interval values for key soil properties at a 90 m grid resolution for six set depths; 0 to 5 cm, 5 to 15 cm, 15 to 30 cm, 30 to 60 cm, 60 to 100 cm and 100 to 200 cm, across Victoria. The grids have been designed to meet the specifications created by GlobalSoilMap (www.globalsoilmap.net) to develop and deliver detailed soil information in a consistent form. The grids are a spatial interpolation of key soil properties to support modelling and decision making in resource management, agricultural production, land use policy and planning, and in further research such as ecosystem modelling. The methodology used to develop the Soil Grids of Victoria has been based on that refined by the Australian Soil and Landscape Grid. Data and knowledge embedded into existing soil related datasets, e.g. soil profile and land mapping collections, have been key inputs. Whilst the new maps show an immense amount of fine scale detail, and are our best spatially continuous and exhaustive estimates of soil attributes across all of Victoria, they are most appropriately used for assessments of regional to state-wide trends of soil properties and their relationship with their environment and pedogenesis. Care should be taken when using the grids for local assessments and it is recommended that the confidence intervals are included at this scale.

  • A spatial dataset of soil and landform classification in Gippsland. The map units are broad `packages' of land - divided primarily on the basis of soil type, landform pattern and geology. It contains soil and land information at a scale of 1:100 000 for all land in the region. The dataset has been derived from a combination of past studies and has been collated primarily by Ian Sargeant and Mark Imhof from 1994 to 2013. Data from older surveys have also been included in this consolidated dataset. Mapping in east and northern Gippsland regions is restricted to freehold lands. Webpages on Victorian Resources Online provide a description of each of the map units and indicate source studies used to define the map unit. In June 2013 a dominant soil type was assigned to each unit (by David Rees, Mark Imhof and Ian Sargeant) to facilitate the creation of a digital soil map of Victoria. Australian Soil Classification (Order and SubOrder) have been included in the dataset's attribute table. At the map scale of this dataset soil-landform units are not homogeneous. For each defined soil-landform unit, the number and proportion of landforms and soil types will vary. Representative sites and their associated profile properties are recorded on the Victorian Resources Online website (http://vro.depi.vic.gov.au/dpi/vro/wgregn.nsf/pages/wg_soil_detailed). Importantly it should be noted that soil attributes (for example texture, sodicity, pH) are expected to vary between acquired soil sites. As the variability of soil attributes within a map unit is difficult to predict, it is important to note that representative soils should be used as a guide only. DOI 10.4226/92/58e719aeb6e7c

  • 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

  • This dataset is the primary data output from the north-east land resource assessment project undertaken in 2001-02. It contains soil and land information at a scale of 1:100 000 for all freehold land in north-east Victoria. It also includes generic soil erosion risk assessments and agricultural capability. At the map scale of this dataset soil-landform units are not homogeneous. For each defined soil-landform unit, dominant soil types were identified prior to assessing their capability to support various enterprises. Often a co-dominant and minor soil type have been described as part of this process. Importantly it should be noted that soil attributes (for example texture, sodicity, pH) are expected to vary between acquired soil sites. As the variability of soil attributes within a map unit is difficult to predict, it is important to note that representative soils should be used as a guide only. The study report describing the project methodology and dataset attributes is available from the Victorian Resources Online website (http://vro.depi.vic.gov.au/dpi/vro/neregn.nsf/pages/ne_soil_landform_survey) DOI 10.4226/92/58e71be578ac0

  • A set of Digital Soil Maps (mean, 5th and 95th percentile prediction values) of soil pH (of a 1:5 soil water solution) across Victoria in geotiff format. Grids of key soil properties have been produced for Victoria. These grids, in raster format, provide prediction and confidence interval values for key soil properties at a 90 m grid resolution for six set depths; 0 to 5 cm, 5 to 15 cm, 15 to 30 cm, 30 to 60 cm, 60 to 100 cm and 100 to 200 cm, across Victoria. The grids have been designed to meet the specifications created by GlobalSoilMap (www.globalsoilmap.net) to develop and deliver detailed soil information in a consistent form. The grids are a spatial interpolation of key soil properties to support modelling and decision making in resource management, agricultural production, land use policy and planning, and in further research such as ecosystem modelling. The methodology used to develop the Soil Grids of Victoria has been based on that refined by the Australian Soil and Landscape Grid. Data and knowledge embedded into existing soil related datasets, e.g. soil profile and land mapping collections, have been key inputs. Whilst the new maps show an immense amount of fine scale detail, and are our best spatially continuous and exhaustive estimates of soil attributes across all of Victoria, they are most appropriately used for assessments of regional to state-wide trends of soil properties and their relationship with their environment and pedogenesis. Care should be taken when using the grids for local assessments and it is recommended that the confidence intervals are included at this scale.

  • This dataset is the primary data output from the Goulburn Broken Dryland Regional Development Project conducted from 1998 to 2000. It contains soil and land information at a scale of 1:100 000 for all land in the region. At the map scale of this dataset soil-landform units are not homogeneous. For each defined soil-landform unit, the number and proportion of landforms and soil types will vary. A group or groups of soils have been associated with each unit. Representative sites and their associated profile properties are recorded in the study report. Importantly it should be noted that soil attributes (for example texture, sodicity, pH) are expected to vary between acquired soil sites. As the variability of soil attributes within a map unit is difficult to predict, it is important to note that representative soils should be used as a guide only.