Value
MagicDirt Value is a consultancy-based service that provides property values for large-scale planning and analysis in rural NSW.
Information on the current market for large zones of interest allows for the benefits of a big picture approach when compared to single property statistics, but our methodology for data and mapping retains the accuracy you need.
We work with you to scope out your requirements and produce a project deliverable and are there to support your understanding of the data and its representation. MagicDirt Value provides the information you need to move your project forward with efficiency and accuracy.
Applications:
Analysis on property value can be carried out with a focus on vegetative properties. For example, you may be interested in properties with a minimum quantity of vegetation or on those with a minimum threshold of arable area. MagicDirt Value can provide information with specific parameters.
Information is managed in mapping formats so the output can be analysed in the context of other geospatial information. Of particular benefit when dealing with large-scale infrastructure projects, the spatial format of the MagicDirt Value dataset allows rapid feasibility costing of partial and whole properties. By adding an overlay of the proposed infrastructure, land classes intersected by it (the overlay / infrastructure) will better reflect high and low value portions of property than if average values were used.
What information is included as part of consultancy and how can I use it?
Our mapping systems allow for the development of a spatial database layer detailing the estimated land value covering every patch of privately-owned rural land in NSW.
Because the foundation datasets have a resolution much finer than the property scale, we can differentiate parts of properties and provide the value of each land class within them. From a set of 7 typical land classes found in rural NSW, the four largest of these within a holding are reported.
Value
The Data
We start with rural property listings and put them on a map.
We then track official sales of those listed properties and input this data into our system.
To develop the estimate of value of rural land, we look at sales of vacant land without improvements as well as land which is entirely timbered or entirely cultivated.
The result is an estimate of current land market value, informed by weekly updates of sale information – results that reflect buyer behaviour without introducing hypotheticals or black box AI.
You are probably aware that rural property value is strongly related to classes of land within the property. Buyers will visit the land in person, look at aerial imagery and form an opinion of value based on the extent and type of land classes - timber, cultivation and grazing country.
How do we reach our values?
More on methodology
Service Limitations: The services provided as MagicDirt are not professional valuations and should not be considered as such. The information provided in the services described above is general advice and the user is required to verify the details by other sources and their own investigations.
Rural land is classified based on publicly available datasets which have been constructed according to nationally agreed protocols. These datasets have 10+ years of lineage and strong consistency across LGAs, regions and states. This consistency of application and a methodical approach to dealing with sales, greatly improves our precision of modeling property value.
Property sales are appraised on the same basis that a rural property valuation would normally be carried out. The model method is referred to as Appraisal Assisted AVM or appraisal emulation. As part of this method, a valuer guides the AVM prior to the determination of value - making selections, corrections, rankings and adjustments to the data to be submitted to the AVM for valuation. Consistency is tested according to the standard published by the International Association of Assessing Officers (IAAO), based in the US. Calculations of land value are straightforward, and the method uses transparent calculations.
