Dataset Information

VLUIS, a land use data product for Victoria, Australia, covering 2006 to 2013.

ABSTRACT: Land Use Information is a key dataset required to enable an understanding of the changing nature of our landscapes and the associated influences on natural resources and regional communities. The Victorian Land Use Information System (VLUIS) data product has been created within the State Government of Victoria to support land use assessments. The project began in 2007 using stakeholder engagement to establish product requirements such as format, classification, frequency and spatial resolution. Its genesis is significantly different to traditional methods, incorporating data from a range of jurisdictions to develop land use information designed for regular on-going creation and consistency. Covering the entire landmass of Victoria, the dataset separately describes land tenure, land use and land cover. These variables are co-registered to a common spatial base (cadastral parcels) across the state for the period 2006 to 2013; biennially for land tenure and land use, and annually for land cover. Data is produced as a spatial GIS feature class.

SUBMITTER: Morse-McNabb E

PROVIDER: S-EPMC4658571 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

VLUIS, a land use data product for Victoria, Australia, covering 2006 to 2013.

Morse-McNabb Elizabeth E Sheffield Kathryn K Clark Rob R Lewis Hayden H Robson Susan S Cherry Don D Williams Steve S

Scientific data 20151124

Land Use Information is a key dataset required to enable an understanding of the changing nature of our landscapes and the associated influences on natural resources and regional communities. The Victorian Land Use Information System (VLUIS) data product has been created within the State Government of Victoria to support land use assessments. The project began in 2007 using stakeholder engagement to establish product requirements such as format, classification, frequency and spatial resolution. ...[more]

PMID: 26602150

Similar Datasets

Project description:Background and aimsDespite increases in opioid prescribing and related morbidity and mortality, few studies have comprehensively documented harms across opioid types. We examined a population-wide indicator of extramedical pharmaceutical opioid-related harm to determine if the supply-adjusted rates of ambulance presentations, the severity of presentations or other attendance characteristics differed by opioid type.DesignRetrospective observational study of coded ambulance patient care records related to extramedical pharmaceutical opioid use, January 2013 to September 2018.SettingAustralia CASES: Primary analyses used Victorian data (n = 9823), with available data from other Australian jurisdictions (n = 4338) used to determine generalizability.MeasurementsWe calculated supply-adjusted rates of attendances using Poisson regression, and used multinomial logistic regression to compare demographic, presentation severity, mental health, substance use and other characteristics of attendances associated with seven pharmaceutical opioids.FindingsIn Victoria, the highest rates of attendance [per 100?000 oral morphine equivalent mg (OME)] were for codeine (0.273/100?000) and oxycodone (0.113/100?000). The lowest rates were for fentanyl (0.019/100?000) and tapentadol (0.005/100?000). Oxycodone-naloxone rates (0.031/100 000) were lower than for oxycodone as a single ingredient (0.113/100?000). Fentanyl-related attendances were associated with the most severe characteristics, most likely to be an accidental overdose, most likely to have naloxone administered and least likely to be transferred to hospital. In contrast, codeine-related attendances were more likely to involve suicidal thoughts/behaviours, younger females and be transported to hospital. Supply-adjusted attendance rates for individual opioids were stable over time. Victorian states were broadly consistent with non-Victorian states.ConclusionsIn Australia, rates and characteristics of opioid-related harm vary by opioid type. Supply-adjusted ambulance attendance rates appear to be both stable over time and unaffected by large changes in supply.

Project description:Land-use change is one of the biggest threats to biodiversity globally. The effects of land use on biodiversity manifest primarily at local scales which are not captured by the coarse spatial grain of current global land-use mapping. Assessments of land-use impacts on biodiversity across large spatial extents require data at a similar spatial grain to the ecological processes they are assessing. Here, we develop a method for statistically downscaling mapped land-use data that combines generalized additive modeling and constrained optimization. This method was applied to the 0.5° Land-use Harmonization data for the year 2005 to produce global 30″ (approx. 1 km(2)) estimates of five land-use classes: primary habitat, secondary habitat, cropland, pasture, and urban. The original dataset was partitioned into 61 bio-realms (unique combinations of biome and biogeographical realm) and downscaled using relationships with fine-grained climate, land cover, landform, and anthropogenic influence layers. The downscaled land-use data were validated using the PREDICTS database and the geoWiki global cropland dataset. Application of the new method to all 61 bio-realms produced global fine-grained layers from the 2005 time step of the Land-use Harmonization dataset. Coarse-scaled proportions of land use estimated from these data compared well with those estimated in the original datasets (mean R (2): 0.68 ± 0.19). Validation with the PREDICTS database showed the new downscaled land-use layers improved discrimination of all five classes at PREDICTS sites (P < 0.0001 in all cases). Additional validation of the downscaled cropping layer with the geoWiki layer showed an R (2) improvement of 0.12 compared with the Land-use Harmonization data. The downscaling method presented here produced the first global land-use dataset at a spatial grain relevant to ecological processes that drive changes in biodiversity over space and time. Integrating these data with biodiversity measures will enable the reporting of land-use impacts on biodiversity at a finer resolution than previously possible. Furthermore, the general method presented here could be useful to others wishing to downscale similarly constrained coarse-resolution data for other environmental variables.

Dataset Information

VLUIS, a land use data product for Victoria, Australia, covering 2006 to 2013.

Publications

VLUIS, a land use data product for Victoria, Australia, covering 2006 to 2013.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets