Show ONLY these Collection Types:
Show ONLY these Licence Types:
Show ONLY these Categories:
Show ONLY these People:
Show ONLY these Projects:
Showing results for: [ Physical Geography and Environmental Geoscience not elsewhere classified ]
These data provide consistent rasterised layers of edaphic (physical and chemical conditions of the soil) and land surface physiography (landform and geomorphology) variables hypothesised to explain s... morepatial patterns in biological diversity at continental scales for immediate use with statistical modelling tools. These data are intended to be used along with a similarly compiled and spatially standardised set of climatic layers. Consistent "stacks" of raster variables are needed for spatially-explicit biodiversity modelling using tools such as MAXENT or Generalised Dissimilarity Modelling (GDM). Full details of each dataset, with a list of data sources and bibliography, are provided in a table as part of the data collection. Additional information provided with the 1km gridded raster is relevant to some these data and provided here also. Each dataset will need to be separately cited. These data have also been made available for use in the Atlas of Living Australia's Spatial Portal. less
Closed DIISR ALA Exp-Geosptl Data Mngmnt - Stack of Environmental Variables for Biodiversity Modelling - Published 12 Jun 2017
The Revised Universal Soil Loss Equation (RUSLE) estimates the annual soil loss that is due to erosion using a factor-based approach with rainfall, soil erodibility, slope length, slope steepness and ... morecover management and conservation practices as inputs. The collection is (i) a set of maps that represent the RUSLE factors, (ii) a map of the RUSLE estimates of soil erosion in Australia and (iii) a map of the uncertainty in the estimates of erosion.less
1181.2 TERN Facility No9 InfoGrid GRUNDY - National Soil Grid - Published 17 Nov 2016
The Physiographic Regions of Australia (Pain, Gregory, Wilson and McKenzie 2011) are a modification of those compiled by Jennings and Mabbutt (1977), and are based on a visual interpretation of landfo... morerms as expressed on the Shuttle Radar Terrain Mission (SRTM) digital elevation model (DEM). Apart from its descriptive role, a map of physiographic regions provides a regional system of reference for geomorphological and related physical geographical accounts. Through the groupings of physiographic regional characteristics at different levels, the action of underlying controls, for instance geologic or climatic, may be made apparent. Further, the map can provide a regional basis for an understanding of land characteristics that are dependent upon landforms, for example the distribution of soils or natural vegetation. Jennings J.N. and Mabbutt J.A. (1977) Physiographic outlines and regions. In 'Australia, a geography. Volume 1. The natural environment.' (Ed. DN Jeans) (Sydney University Press: Sydney).less
CLSD DAFF/ACLEP 2009-10/(C2009/10948) - ASRIS Data - Published 01 Aug 2016
The Recharge-Discharge Estimation software suite provides water managers with valuable tools to estimate groundwater recharge and/or discharge in areas where no field based recharge or discharge studi... morees have been undertaken. It is comprised of two stand-alone tools in the Microsoft Excel™ spreadsheet format, which when coupled with data that is usually readily available and/or accessible, provides recharge and discharge estimates using simple approximations. Australian spatial datasets for use with the Recharge-Discharge Estimator Suite spreadsheets are available via: http://www.ga.gov.au/metadata-gateway/metadata/record/83878. These data layers are provided as an ESRI® File Geodatabase.less
Groundwater recharge in data poor areas - Nationally consistent approach to recharge and discharge estimation for data poor areas. - Published 11 Aug 2015
These data provide rasterised layers of climatic variables hypothesised to explain spatial patterns in biological diversity at continental scales for use with statistical modelling tools. Specificall... morey, these data were derived for modelling the compositional pattern of multiple species with environmental factors such as climate, soil and topography using the statistical technique Generalised Dissimilarity Modelling applied to continental Australia.
Climate variables are monthly mean values for minimum temperature, maximum temperature, relative humidity, vapour pressure, precipitation, aridity, solar radiation, evaporation, wind and others. Some of these monthly variables were used to generate growth indices (using the GROCLIM module of ANUCLIM).
These data for Generalised Dissimilarity Modelling (GDM) analysis were masked to consistently define data/nodata values and supplied in DIVA-GIS floating-grid format in the WGS84 geographic reference system.
NOTE: Full details of the data, with a list of data sources and bibliography, are provided in a PDF file included as part of the data collection.less
Closed DEWHA Harness Cntnnt-wide Bdvrsty - Spatial Environmental Data Preparation - Published 29 Jan 2015