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Geospatial 2.0

Robert Rowell

CEO and Founder, Insight GIS

TBC.

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How Royalties can fund the future of Surveying

Simon White, CEO, The Surveyors’ Trust

The Surveyors’ Trust was formed following the recognition of cadastral plan copyright ownership, creating a unique opportunity to reinvest plan royalties into initiatives that secure the future of the surveying industry. Gain a better understanding of the Trust and see how you can get involved in Tasmanian Projects that support the industry.

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From the Field to the GIS: Streamlining Asset Data Transfer at TasWater

Martin Ankor, Survey Program Coordinator, and Cal Wright, Asset Information Officer, TasWater

TasWater, like many water utilities, needs accurate spatial and attribute data for new and donated assets. This data is essential for long-term management and maintenance of those assets. To support this, TasWater provides a suite of resources to surveyors, including templates, codetables, and other tools that align with the Asset Spatial Data Standard (ASDS). We will present some examples and proposed updates aimed at making the transfer of data to TasWater simpler and more efficient, and information on how these systems tie into the quality assessment process.

SIO Plan Format, and Statutory Status

Neville McGuire

Registered Land Surveyor, N.C. McGuire & Associates Pty. Ltd.

• Does the current SIO Plan Format meet the client’s needs or expectations?
• Should there be a statutory requirement of full disclosure for the adjoining Owners?
• Is the presentation in a format that the Public can understand?
• Are SIO Plans solely prepared for the next surveyor as?

As a Private Surveyor working in my own business for 39 years and Registered since 1979 and working in the commercial world, I believe the current SIO plan does not meet the public’s requirement nor has any regard to the adjoining property owners. My experience in working in other States and the Northern Territory gives me an insight into how the SIO plan can be improved, providing what the owners require and less time consuming to prepare.

I feel we place too much emphasis in preparing a plan that only Surveyors can understand, generally not to scale, sketched and confusing to the client and public.

The SIO plan has been developed by Government authorities who don’t have communication with the public nor work in the commercial world.

Professionally, is there communication with the adjoining neighbours when we are undertaking any survey and do they need to know?

I will put forward at the meeting that we make some changes to the Survey Directions to ensure adjoining neighbours be informed and receive a copy if required of the completed SIO plan. There is a standard form for this in Queensland relating to all surveys.

I will undertake a review into this with examples and hopefully have time to debate upon completion.

I would ask all surveyors to be open minded with my suggestions and ask the question, can we do this better? Considering my suggestions on merit, as a senior practising surveyor who is still undertaking all aspects of a survey instruction.

Concluding we need to maintain our professional standing within the community.

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Spatial Statistics Workshop: When to use Geographically Weighted Regression (GWR)

Anthony O’Flaherty

Head of Business Intelligence & Analytics, RACT, and TASSIC Member

Geographically Weighted Regression (GWR) addresses a fundamental limitation of traditional regression methods: the assumption that relationships between variables remain constant across geographic space. While Ordinary Least Squares (OLS) and other global regression approaches produce single, averaged coefficients, GWR acknowledges that these relationships may vary systematically with location, generating location-specific parameter estimates that reveal spatial heterogeneity.

GWR is most appropriate when analyzing phenomena exhibiting spatial non-stationarity, particularly when regression residuals show significant spatial autocorrelation or when local parameter estimates are of substantive interest. Common applications include voting patterns, sales, epidemiology, and socio-economic analysis, where spatial context fundamentally influences the processes under investigation. The method requires sufficient spatial variation in underlying relationships and adequate sample density across the study area to produce meaningful local estimates.

The primary value of GWR over traditional regression lies in its ability to map how predictor-response relationships change across space, often resulting in improved model fit and reduced residual spatial autocorrelation. By producing surfaces of parameter values rather than single coefficients, GWR reveals local processes that would be obscured by global models, providing valuable diagnostic information about where and how relationships deviate from global trends. However, when relationships are genuinely stationary or sample sizes are limited, traditional regression may remain preferable. The choice between methods should be guided by theoretical considerations, exploratory spatial analysis, and formal tests for spatial non-stationarity. When appropriately applied, GWR offers powerful insights into spatially varying processes that traditional regression approaches cannot capture.