AURICL: Riverine Landscape Classifier
AURICL: Riverine Landscape Classifier
AURICL (AUstralian RIverine landscape CLassifier) is a facility designed to assist researchers and policy makers to make better decisions about riverine landscapes. It is a dynamic and flexible system for classifying and comparing tropical catchments and their rivers based on the similarity, or dissimilarity, of a wide range of parameters.
The project was originally developed through the Tropical Rivers and Coastal Knowledge (TRaCK) program (Commonwealth Environmental Research Facility) and the National Water Commission (NWC).
How AURICL works
The AURICL classification service is based on an analysis of discrete river segments of the drainage network within the National Catchments Boundaries dataset, which were derived from a hydrologically corrected 9 second DEM . The river segments are the objects being classified within AURICL. There are approximately 350,000 segments in the dataset covering the TRaCK Northern Australia region.
Each river segment can be associated with a value from an “attribute” data table. For example, there is an attribute table called Mean Rainfall which contains the derived rainfall value at each river segment. Most attributes describe a segment’s immediate surrounds, whilst some are integrated over the contributing catchment area upstream of a segment. Any data that can be usefully interpreted at the scale of these segments could be used as an AURICL Attribute.
The AURICL analysis is formulated as either a comparison or a classification. A comparison is expressed through a coefficient of similarity. A classification applies an iterative non-hierarchical clustering method which places each segment into one of a user specified number of classes.
To create a classification, the user first decides if they want a degree of similarity or range of classes. Then they select desired data attributes and weight them according to relative importance in the output. After providing some additional metadata, the batch request is sent to AURICL laboraties where the classification is generated.
An output package contains the resulting data table, an shapefile, and an analysis document providing details of the classification run. The data table and map layer supports the comparison/classification to be integrated or visualised as best suits the end user.
How AURICL can help
Depending on the specific objectives of the user, different types of classifications having quite different objectives can be derived. Example classifications could be:
- identification of similar river reaches to a research location for a fish species, based on rock type and catchment area as predictors of habitat;
- visualisation of similarities and differences between rivers according to the combination of their geology and climate to gain a broad understanding of the catchments.
As it is currently formulated, the classification can be based on any combination of approximately 50 attributes, however, there is no design limitation to additional variables. One of the benefits of this system is that it is a living classification system, which can be updated as new data becomes available.
At present the input data sets are organised under the five broad headings of:
- Terrain: topographic and stream network characteristics;
- Substrate/Geology: these are generally a function of catchment/stream network geology;
- Modelled Hydrology: hydrological parameters modelled from rainfall-runoff characteristics;
- Climatic Variables: rainfall and erosivity
- Land Use: Population density, water resource development, River disturbance index etc.
- Socio economic: Household composition, income, demographics etc.
Getting started: OzCoasts
Create an account
(coming soon!) Frequent users will be able to request and pick up their classifications through a personalised account.