Metadata Name Descriptions
Resource Name: Soil Grids of Victorian - Soil pH (CaCl2)
Title: Soil Grids of Victorian - Soil pH (CaCl2)
Anzlic ID: ANZVI0803005795
Custodian: Department of Jobs, Precincts and RegionsDepartment of Jobs, Precincts and Regions
Abstract:
A set of Digital Soil Maps (mean, 5th and 95th percentile prediction values) of soil pH (of 1:5 soil/0.01M calcium chloride extract) 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.
Search Words: Geoscientific information
Currency Date: 18 May 2022
Dataset Status: Under development
Progress: Victoria
Access Constraint:
Creative Commons by Attribution

Whilst the Soil Grids 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. Site based assessments should be made when assessing and making decisions at local scales.
Data Existence:
Metadata Name Descriptions
Resource Name: Soil Grids of Victorian - Soil pH (CaCl2)
Title: Soil Grids of Victorian - Soil pH (CaCl2)
Anzlic ID: ANZVI0803005795
Custodian: Department of Jobs, Precincts and RegionsDepartment of Jobs, Precincts and Regions
Owner: Department of Jobs, Precincts and Regions
Jurisdiction: Victoria
Abstract:
A set of Digital Soil Maps (mean, 5th and 95th percentile prediction values) of soil pH (of 1:5 soil/0.01M calcium chloride extract) 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.
Search Words: Geoscientific information
Purpose:
                        
Geographic Extent Polygon:
Geographic Bounding Box:
-34
141 150
-39
Beginning to Ending Date: 1958-01-01 - 2016-12-31
Maintainence and Update Frequency: Not planned
Stored Data Format: DIGITAL geotiff 3
Available Format(s) Types: DIGITAL geotiff
Lineage:
Dataset Source: The soil grids have been produced by Agriculture Victoria Research, a division of the Department of Economic Development, Jobs, Transport and Resources.

Development of the grids has involved methodologies generally referred to as Digital Soil Mapping (DSM). The International Union of Soil Sciences Digital Soil Mapping Working Group defines DSM as creation and the population of a geographically referenced soil database, generated at a given resolution by using field and laboratory observation methods coupled with environmental data through quantitative relationships. In essence, it uses more easily obtained, spatially exhaustive, `predictor¿ datasets to infer likely soil property values at a given location and resolution. The Soil Grids of Victoria are a contribution to other State, National and International digital soil mapping efforts. The grids are Victoria¿s first state-wide attempt at this efficient and cost-effective approach to mapping soils at fine-scale resolution in a consistent and easy to use format.

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.

Although, the maps have been produced at a fine spatial scale, 90 m grid resolution, the predicted value within each grid pixel has been derived from models calibrated from available data across Victoria. This means the effects of localised conditions may be somewhat muted. Furthermore, each property has been modelled independently. Co-variation between properties such as particle size distribution, i.e. proportion of sand, silt and clay, and field capacity and wilting point have not been considered. 

Input soil data is of varying quality being influenced by measurement technique, spatial geo-referencing and age. In all instances, data from a variety of measurement techniques have been combined and this data has been modified as it has been harmonised to target depths. Pragmatic decisions have been made when sourcing and treating data to maximise the amount and distribution of data across Victoria to develop the predictive models. Except for pH and Bulk Density, the model calibration and validation data has included estimated values derived from MIR spectroscopy. These data have a larger uncertainty than direct laboratory measurements and therefore impact the accuracy of resulting map predictions.

Input site data has been sourced from soil surveys, many dating back to the 1950s. For dynamic soil properties, such as soil pH, it should be noted that no date filter has been applied. 

Dataset Originality: Derived
Positional Accuracy:
Not Known
Attribute Accuracy:
Model fit summary statistics (pH CaCl2)

Depth   5cm   15cm   30cm   60cm   100cm   200cm
R2	   0.68	   0.73	   0.75	   0.75	   0.75	   0.71
LCCC	   0.82	   0.85	   0.86	   0.86	   0.86	   0.84
RMSE	   0.697	   0.656	   0.689	   0.749	   0.789	   0.87
ME	   -0.055	   0.005	   -0.053	   -0.071	   0.016	   0.027
Av Obs.	   6.1	   6.22	   6.64	   7.15	   7.44	   7.57
Av Mod.	6.05	6.23	6.59	7.08	7.45	7.6
	
Lin¿s concordance correlation co-efficient (LCCC) assesses covariation and correspondence between the predictions and the original data. Values > 0.9 denote near perfect agreement, values between 0.75 and 0.9 show substantial agreement, between 0.6 and 0.75 show moderate agreement and those < 0.6 indicate poor agreement (Lin 1989). The Root Mean Square Error quantifies the inaccuracy of the predictions and the Mean Error the prediction bias.
Logical Consistency:
Not Known
Data Source:
Dataset Source: The soil grids have been produced by Agriculture Victoria Research, a division of the Department of Economic Development, Jobs, Transport and Resources.

Development of the grids has involved methodologies generally referred to as Digital Soil Mapping (DSM). The International Union of Soil Sciences Digital Soil Mapping Working Group defines DSM as creation and the population of a geographically referenced soil database, generated at a given resolution by using field and laboratory observation methods coupled with environmental data through quantitative relationships. In essence, it uses more easily obtained, spatially exhaustive, `predictor¿ datasets to infer likely soil property values at a given location and resolution. The Soil Grids of Victoria are a contribution to other State, National and International digital soil mapping efforts. The grids are Victoria¿s first state-wide attempt at this efficient and cost-effective approach to mapping soils at fine-scale resolution in a consistent and easy to use format.

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.

Although, the maps have been produced at a fine spatial scale, 90 m grid resolution, the predicted value within each grid pixel has been derived from models calibrated from available data across Victoria. This means the effects of localised conditions may be somewhat muted. Furthermore, each property has been modelled independently. Co-variation between properties such as particle size distribution, i.e. proportion of sand, silt and clay, and field capacity and wilting point have not been considered. 

Input soil data is of varying quality being influenced by measurement technique, spatial geo-referencing and age. In all instances, data from a variety of measurement techniques have been combined and this data has been modified as it has been harmonised to target depths. Pragmatic decisions have been made when sourcing and treating data to maximise the amount and distribution of data across Victoria to develop the predictive models. Except for pH and Bulk Density, the model calibration and validation data has included estimated values derived from MIR spectroscopy. These data have a larger uncertainty than direct laboratory measurements and therefore impact the accuracy of resulting map predictions.

Input site data has been sourced from soil surveys, many dating back to the 1950s. For dynamic soil properties, such as soil pH, it should be noted that no date filter has been applied. 

Dataset Originality: Derived
Contact Organisation: Department of Jobs, Precincts and Regions
Contact Position: Senior Researcher - Agriculture Research Division
Address: PO Box 3100 Bendigo Delivery Centre Bendigo VIC 3554 Australia
Telephone: +61 3 5430 4309
Facsimile:
Email Address: steve.williams@ecodev.vic.gov.au
Metadata Date: 2021-07-14
Additional Metadata:
                            
                              Related Documents: None
                            
                          
No attributes