Today, Many GIS users are unaware that metre-level misalignments between WGS84 basemaps and modern Authoritative GDA2020 datasets are common. This can cause confusion and lower confidence in the accuracy of authoritative datasets and basemaps.
As of May 2023, the national and state governments of Australia have spatially improved their foundational datasets from GDA94 to GDA2020 (Geocentric Datum of Australia 2020), or have documented accommodations to the import and export of GDA2020 datasets. This migration to GDA2020 has been ongoing since 2017 when GDA2020 was defined as the new national datum. Many local governments have followed this migration and now major utilities, resource companies and other private organisations have committed or have moved to this new datum.
A significant driver has been the economic benefits assessments for precise positioning and GNSS augmentation, e.g. Ernst & Young (2018), ACIL Allen (2024). GDA2020 was developed in anticipation of public access to high-accuracy positioning capabilities and was designed to better align with global positioning systems such as GNSS, by shifting the coordinate system approximately 1.8m northeast to account for tectonic motion that occurred over the last 30 years.
For authoritative data this is particularly important as the rollout of SouthPAN (2022 – 2028) to mobile devices will provide sub-meter accuracy. Field workers using compatible mobile devices will be able to locate assets with 10 cm accuracy. This publicly available technology will provide accuracies not previously attainable unless costly differential GNSS techniques were acquired and utilised.
Authoritative spatial datasets gain the most value when visualised in context to other spatial datasets, including basemaps. Generally, basemaps are defined and delivered in the WGS 84 Web Mercator (Auxiliary Sphere) projection and are a combination of many source datasets. In most, if not all cases, the lineage of the source data is not known or poorly understood and as a result, these basemaps have no defined accuracy, hence they are termed Ensemble, being made up of many sources of data.
There is a common misunderstanding that the basemaps provide spatially accurate reference data. In the past metre-level misalignments may have arisen when global basemaps were gathered or delivered in WGS 84 Web Mercator and then overlayed with authoritative GDA2020 datasets.
It is important to understand that there may be a need to transform data to correctly align datasets. In the past (around 1994), in Australia, GDA94 aligned with the then current WGS84 realisation via a ‘NULL’ transformation. In effect, GDA94 data was (and often still is today) ‘re-badged’ as WGS 84 for web mapping purposes. When data sets are mixed and not correctly transformed the result is a misalignment by the offset between GDA94 and GDA2020 (~1.8 m). This is because both GDA94 data and GDA2020 data are transformed to WGS84 by a “NULL” transformation. This null transformation suited the times but is no longer fit for purpose.
In addition, WGS 84 has been re-defined six times since its inception and is updated annually to track tectonic motion for its primary user, GPS. WGS 84 is now more closely aligned to GDA2020 than to GDA94!
Fortunately, Esri provides all available transformations between GDA2020, WGS84 and GDA94 in their current software products. The matrix below links available transformations with the Esri products that supports them and provides guidance when aligning data in Esri software:
NOTE: “Additional Download” in the table refers to the ArcGIS Coordinate Systems Data Install, which is an extra piece of software that should be installed along with ArcGIS Pro, ArcGIS Reality and ArcGIS Enterprise and is available at https://my.esri.com.
More information on GDA2020 is available from ICSM via https://icsm.gov.au/gda2020
The table below lists the transformations, their EPSG code, name and approximate transformation accuracy.
| EPSG | NAME | Description | Accuracy |
|---|---|---|---|
| 8048 | GDA94 to GDA2020 (1) | 7 parameter transformation (3D) | 0.01 m |
| 8447 | GDA94 to GDA2020 (2) | NTv2 Conformal and Distortion transformation (2D) | 0.05 m |
| 8446 | GDA94 to GDA2020 (3) | NTv2 Conformal transformation (2D) | 0.05 m |
| 1150 | GDA94 to WGS 84 (1) | Null transformation to WGS 84 ensemble (3D). Approximation at ± 3m using assumption that GDA94 is equivalent to low accuracy WGS 84 (ensemble) | 3 m |
| 9688 | GDA94 to WGS 84 (2) | 7 parameter transformation: Equivalent to 8048 (7P) plus 8450 (NULL) (3D) | 3 m |
| 9689 | GDA94 to WGS 84 (3) | NTv2 Conformal and Distortion: Equivalent to 8447 (NTv2) plus 8450 (NULL) (2D) | 3 m |
| 8450 | GDA2020 to WGS 84 (2) | Null transformation to WGS 84 ensemble (3D). Approximation at ± 3m using assumption that GDA2020 is equivalent to low accuracy WGS 84 (ensemble) | 3 m |
| 9690 | WGS 84 to GDA2020 (3) | 7 parameter transformation: Equivalent to 8048 (7P) plus 1150 (NULL) (3D) | 3 m |
| 9691 | WGS 84 to GDA2020 (4) | NTv2 Conformal and Distortion: Equivalent to 8447 (NTv2) plus 1150 (NULL) (2D) | 3 m |
These are all single-step, direct transformations from one datum to another.
ArcGIS also provides two step transformations where data where data must go through an intermediate datum before ending up at the desired datum. A full list of transformations is available at: https://pro.arcgis.com/en/pro-app/latest/help/mapping/properties/pdf/geographic_transformations.pdf
Esri Australia Technical Blog 
Awesome post Gordon. ArcGIS GeoAnlaytics Engine also supports all those transformations which is useful for those working with geospatial content in environments like databricks, microsoft fabric or AWS Redshift.