ASDST Rock Art Current Model

The Aboriginal Sites Decision Support Tool ASDST extends the Aboriginal Heritage Information Management System (AHIMS) by illustrating the potential distribution of site features recorded in AHIMS.
ASDST was first developed in 2012 by the Office of Environment and Heritage (OEH) to support landscape planning of Aboriginal Heritage. The Tool produces a suite of raster GIS modelled outputs and is held in Esri GRID format.  The first suite was published in 2016 as Version 7 at 100m resolution and in Lamberts Conic Conformal Projection (LCC). The current Version 7.5 was produced by the now Department of Planning, Industry and Environment (DPIE) in 2020 at 50m resolution in Geographic Coordinate System (GCS).  Each layer covers the extent of NSW.  
The suite of layers includes separate predictive layers for different Aboriginal site feature types. The feature codes used in layer naming conventions are:

ALL = model for all feature types combined 
AFT = predicted likelihood for stone artefacts 
ART = predicted likelihood for rock art 
BUR = predicted likelihood of burials 
ETM = predicted likelihood of western mounds and shell 
GDG = predicted likelihood of grinding grooves 
HTH = predicted likelihood of hearths 
SHL = predicted likelihood of coastal middens 
STQ = predicted likelihood of stone quarries and 
TRE = predicted likelihood of scarred trees. 

The feature models have been derived in two forms:


The first form (“p1750XXX” where XXX denotes three letter feature code) predicts likelihood of feature distribution prior to European colonisation of NSW. 


The second form (“curr_XXX” where XXX denotes three letter feature code) predicts feature likelihood in the current landscape. 


For both sets of feature likelihood layers, cell values range from 0 – 1000, where 0 indicates low likelihood and 1000 is high likelihood. 
Please note the scale is likelihood and NOT probability. Likelihood is defined as a relative measure indicating the likelihood that a grid cell may contain the feature of interest relative to all other cells in the layer. 
Additionally, there are other derived products as part of the suite. These are: 


drvd_imp = which is a model of accumulated impacts, derived by summing the difference between the pre colonisation and current version of all feature models. Cell values range from 0 – 1000, where 1000 is a high accumulated impact.


drvd_rel = which is a model of the reliability of predictions based on an environmental distance algorithm that looks at recorded site density across the variables used in the models.


drvd_srv = which is a survey priority map, which considers model reliability (data gap), current likelihood and accumulated impact. Cell values range from 0 – 1000 where 1000 indicates highest survey priority relative to the rest of the layer.


For more details see the technical reference on the ASDST website.
NB. Old layers with a suffix of “_v7” indicate they are part of ASDST Version 7 produced in 2016. The current models (Version 7.5) do not contain a version number in their name and will continue to be named generically in future versions for seamless access.
Updates applied to ASDST version 7.5
For all ASDST 7.5 data sets, the resolution was increased from a 100m cell to a 50m cell. All data sets were clipped and cleaned to a refined coastal mask. Cell gaps in the mask were filled using a Nibble algorithm. The pre-settlement data sets were derived by resampling the version 7 pre-settlement data sets to 50m cell size. The present-day data sets were derived from the version 7.5 pre-settlement layers and 2017-18 land-use mapping and applying the same version 7 parameters for estimating the preservation of each feature type on each land-use. For version 7.5, the model reliability data set was derived by resampling the version 7 data set to 50m cell size.  Accumulated impact and survey priority version 7.5 data sets were derived by applying the version 7 processing algorithm but substituting the version 7.5 pre-settlement and present-day ASDST models.

Tags: Aboriginal sites, Cultural mapping, Site predictive model
Organization: NSW Department of Climate Change, Energy, the Environment and Water