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Agriculture and Forestry

Dryland In the rural heartlands of Australia

Client: Richard Ivey (02) 6845 1611 Ivey ATP

Dryland Salinity is a key land management issue causing increased costs for rural infrastructure, lower of agricultural productivity, threats to localities of natural and social hertiage . By estimating the effect of dryland salinity, land managers can make informed decisions regarding the extent of the problem and measure the effectiveness of past and current control initiatives.

To assist in this process, Spatial Vision devised a salinity "effect surface" methodology in conjunction with Ivey ATP and the Murray Darling Basin Commission from the recorded location of dryland salinity outbreaks. The effect surface is defined by a ratio of intensity (in this case, intensity is measured as effective area of saline outbreak) to distance from the outbreak. The rationale being that the more extensive the outbreak or the closer you are to an outbreak the the great the effect that outbreaks will have on the surrounding landscape. The methodology required an extensive geospatial audit across four states and numerous federal agencies to find the best available data for analysis.

Agricultural productivity was based on land cover data incorporated with Australian Bureau of Statistics (ABS) AgStat information for economic information. AgStat data is key against broad statical units call static tical local areas (SLA). The agricultural commodity information is recorded as a summary of the SLA. In order to use this data in conjunction with more spatially explicit data like salinity outbreaks the SLA-based data needed to be spatially distributed. This process of spatial distribution of AgStats involved defining the gross effective area of agricultural production in each SLA and then calculating productivity on a per hectare basis for the effective area. Spatial Vision was then required to create a comprehensive geospatial dataset and a tabular summary for economic analysis for each of the 26 catchments of the Murray Darling Basin.

Rural infrastructure such as roads and buildings can be severely effected by dryland salinity and the high water tables associated with dryland salinity. The road network used in this study was the AUSLIG 100K dataset. This information was intersected with catchment, local government and the effect surface and summaries were created for each road type. This information was used to assist in the estimation of road infrastructure costs associated with dryland salinity. In order to estimate the effect of dryland salinity on buildings ABS statistics were collated on rural and township household numbers and types. This information is keyed to the SLA and was spatially distributed as households per hectare.

Dryland salinity can have a impact on the quality and amenity of natural and cultural heritage areas and locations. Spatial Vision collated spatial data on sites of significance from the Register of National Estate and from the AUSLIG 250K reserves layer. This information was combined with catchment, local government and the effect surface to provide information that contributed to an estimate sites that may be under threat from dryland salinity.

All information that contributed to this analysis was collated into a standard format and provided on CD to the client.

Spatial Vision documented this methodology in two written documents, a technical report and a summary plain English version.

Demonstrated Capabilities

Proven capacities to organise, collate, standardise and quality test high volumes of geospatial data from distributed sources.
Proven ability to provide advice on the effect of spatial scale, quality and appropriateness of geospatial data for analysis purposes.
Proven ability to design and develop an applied grid analysis framework to support an agreed methodology that seeks to synthesis the best available data.
Proven ability to work in partnership with other organisations and professions on large projects with critical timelines