Data

3 second abiotic environmental raster data for the NARCLIM region of Australia aggregated from various sources for modelling biodiversity patterns

Commonwealth Scientific and Industrial Research Organisation
Harwood, Tom ; King, Darran ; Nolan, Martin ; Gallant, John ; Ware, Chris ; Austin, Jenet ; Williams, Kristen
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
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All Rights (including copyright) CSIRO 2018.

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Data is accessible online and may be reused in accordance with licence conditions

Brief description

This collection of 9-second raster data was compiled for use in modelling biodiversity pattern by developers engaged in supporting the New South Wales Biodiversity Indicators Program. Substrate and landform data derive from existing collections and have been altered from their native format to fill missing and erroneous data gaps as described in the lineage. Climate data were derived using existing methods as described in the lineage. Masks derived or adopted for use in processing the data are included in this collection. Data are supplied in ESRI float grid format, GCS GDA94 Geographic Coordinate System Geocentric Datum of Australia (GDA) 1994.

Lineage

The abiotic environmental data in this collection are grouped by broad type - climate, substrate and landform. Datasets are provided in separate compressed folders (*.zip or *.7z). An excel spreadsheet is included with the collection that list and briefly describes all datasets and their source URLs, and the processing location of the data in the CSIRO project archive. A lineage document summarises the mask and gap filling processes. Mask data were developed from existing spatial boundary data including Australian coastline, State and administration boundaries, and previous raster modelling masks for the NARCLIM region. The data gap filling process was conducted in three stages (python processing scripts are included in this collection). In the first stage, the process used a 10 cell Inverse Distance Weighted (IDW) algorithm to fill no Data areas with data. The IDW algorithm used the distance of data values in the search radius as inverse weights in a neighbourhood average. To deal with remaining larger gaps, a second stage IDW was run on the outputs of the first stage with an increased radius of 500 cells. Any remaining data gaps were filled with a global data average. This process of data filling may make the data unsuitable for other uses and should be carefully considered before use. Images of each dataset are provided in the collection for ease of reference. Data are supplied in ESRI float grid format, GCS GDA94 Geographic Coordinate System Geocentric Datum of Australia (GDA) 1994.

Data time period: 1975-01-01 to 2016-01-01

Click to explore relationships graph

153.702083,-23.57625 153.702083,-39.38125 135.99875,-39.38125 135.99875,-23.57625 153.702083,-23.57625

144.8504165,-31.47875

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