This dataset comprises lineaments interpreted from the State's 100m x 100m resolution Digital Terrain Model (DTM). The interpretation has been completed on a regional or sub-regional scale using geophysical remote sensing techniques and has confirmed that topography is a key structural analysis dataset. This is because it frequently shows strong evidence of the recent reactivation of older fault structures. The analysis identified a number of key topography lineament directions across the state: ENE-WSW: the dominant set of long and persistent linear features; WNW-ESE: the next most obvious interpreted topographic lineament dataset; N-S to NNE-SSW: trends mostly associated with known terrane boundaries. Generally, only lineaments which have not been published in existing datasets developed by the former Department of Primary Industries (DPI) have been identified in this study. The dataset was compiled by GHD to inform the report 'Potential Influences of Geological Structures on Groundwater Flow Systems' for DEPI's Secure Allocation Future Entitlements (SAFE) Project.

This dataset was derived using 50m gridded radiometrics data including: Plain raster images of individual channels (TC, K, Th & U) Individual channels (TC, K, Th & U) draped over topography RGB false colour images of K (red), Th (green) and U (blue) with and without topography and lineaments and compared to topography and lineaments. (where Total Count - TC, Potassium - K, Thorium - Th and Uranium -U) . The interpretation was completed on a regional or sub-regional scale using geophysical remote sensing techniques. By combining the radiometrics and topography datasets, a pseudo-geomorphology is created. The radiometrics respond to soil cover in first the 0.5m of depth. As soils may change across small fault boundaries, radiometric lineaments bear the best relationship with topographic lineaments. From the various radiometric outputs the following key observations have been made: The ENE-WSW lineaments are evident but not as extensively as in the interpreted topographic dataset; The NNW-SSE lineament datasets is most dominant in the radiometric data; In the Otway Basin, many radiometric lineaments are parallel to the cost and are due to strandlines or basin faults; In the Murray Basin, strandlines are obvious as they are evident in the topographic data; In some cases, the soil radiometric chemistry changes across topographic lineaments, supporting the interpretation of topographic lineaments as evidence of small palaeo-fault movement. The dataset was compiled by GHD to inform the report 'Potential Influences of Geological Structures on Groundwater Flow Systems' for DEPI's Secure Allocation Future Entitlements (SAFE) Project.

The ISC2010_VEGETATION_WIDTH_S table is the Statistical Summary table for the Vegetation Width Metric at the 100m Section level. The ISC2010_VEGETATION_WIDTH_S table is designed to JOIN to the ISC2010_RIVER_CENTRELINES_S feature class. River condition in Victoria is assessed every 5 years using the Index of Stream Condition (ISC). The Department of Environment and Primary Industries (DEPI) developed a methodology to assess the Physical Form and Riparian Vegetation components of the ISC using remote sensing data, specifically LIDAR and aerial photography. A State Wide mapping project was undertaken in 2010-13 to accurately map the Physical Form and Riparian Vegetation metrics of the ISC . Other ISC metrics were not assessed in the project and were derived from other sources. The Physical Form and Riparian Vegetation Metric products are a combination of mapped Vector and Raster data as well as Tabular Summary Statistics about the mapped features. In the context of the project, the term Metrics is used to refer to both the mapped features and the summary statistics. Remote sensing data used includes 15cm true colour and infra-red aerial photography and four return multi-pulse LiDAR data. This source data was used to derive a variety of Raster data sets including Digital Terrain Models, Slope, Vegetation Height and Vegetation Cover. The Digital Terrain and Slope rasters were used to map Physical Form metrics including Stream Bed, Top of Bank and River Centre Lines while the Vegetation Height and Cover rasters were used to map the Riparian Vegetation metrics. The Project Report "Aerial Remote Sensing for Physical Channel Form and Riparian Vegetation Mapping" describes the remote sensing and mapping approach used to create this data set.

Projection data is described in the gridcode column of the attribute table. This number is 1000 times the actual value (retained in this form to capture significant figures through map processing). For example, "Gridcode -23599" equates to -24% (rainfall) and "Gridcode 1986" equates to 2.0 degrees Celsius (temperature). The results are from 23 climate models that were available for the IPCC Fourth Assessment Report (2007). It is assumed that that the model results give a representation of the real world response to a specific emissions scenario. The IPCC (2007) estimates of global warming are relative to the period 1980-1999. For convenience, the baseline is often called 1990. Projections are given for 2030 and 2070 but, of course, individual years can vary markedly within any climate period, so the values can be taken as representative of the decade around the single year stated, i.e. projections for 2030 are representative of 2026-2035. Natural variability (independent of greenhouse gas forcing) can cause decadal means to vary and estimates of this effect are included in the estimates of uncertainties. The projections comprise a central estimate and a range of uncertainty. The central estimate is the median – or 50th percentile - of the model results, while the uncertainty range is based on two extreme values – the 10th and 90th percentiles. 10% of values fall below the 10th percentile and 10% of values lie above the 90th percentile. Greater emphasis is given to projections from models that best simulate the present climate. The weightings are based on statistical measures of how well each model can simulate the 1975-2004 average patterns of rainfall, temperature, and sea level pressure over Australia. Subregions of Victoria are indicated. Victoria has an integrated catchment management system established under the Catchment and Land Protection Act 1994 (the CaLP Act). Under the CaLP Act, Victoria is divided into ten catchment regions, with a Catchment Management Authority (CMA) established for each region. (See: http://www.water.vic.gov.au/governance/catchment_management_authorities)

Energy use profiles support effective planning and targeting of energy saving and decarbonising energy supply programs and community engagement. The Department of Sustainability and Environment (DSE) has developed energy consumption profiles for Victorian Local Government Areas. This tool transforms postcode-level source data provided by the Victorian energy distributors into consumption profiles across the municipality. It provides a profile of energy use by SLA for households across the municipality. Year to year comparisons can show changing patterns of energy use for households and on a per capita and per household basis. The tool also has the capacity to incorporate Commercial and Industrial energy use and trends over time.

Energy use profiles support effective planning and targeting of energy saving and decarbonising energy supply programs and community engagement. The Department of Sustainability and Environment (DSE) has developed energy consumption profiles for Victorian Local Government Areas. This tool transforms postcode-level source data provided by the Victorian energy distributors into consumption profiles across the municipality. It provides a profile of energy use by SLA for households across the municipality. Year to year comparisons can show changing patterns of energy use for households and on a per capita and per household basis. The tool also has the capacity to incorporate Commercial and Industrial energy use and trends over time.

Projection data is described in the gridcode column of the attribute table. This number is 1000 times the actual value (retained in this form to capture significant figures through map processing). For example, "Gridcode -23599" equates to -24% (rainfall) and "Gridcode 1986" equates to 2.0 degrees Celsius (temperature). The results are from 23 climate models that were available for the IPCC Fourth Assessment Report (2007). It is assumed that that the model results give a representation of the real world response to a specific emissions scenario. The IPCC (2007) estimates of global warming are relative to the period 1980-1999. For convenience, the baseline is often called 1990. Projections are given for 2030 and 2070 but, of course, individual years can vary markedly within any climate period, so the values can be taken as representative of the decade around the single year stated, i.e. projections for 2030 are representative of 2026-2035. Natural variability (independent of greenhouse gas forcing) can cause decadal means to vary and estimates of this effect are included in the estimates of uncertainties. The projections comprise a central estimate and a range of uncertainty. The central estimate is the median – or 50th percentile - of the model results, while the uncertainty range is based on two extreme values – the 10th and 90th percentiles. 10% of values fall below the 10th percentile and 10% of values lie above the 90th percentile. Greater emphasis is given to projections from models that best simulate the present climate. The weightings are based on statistical measures of how well each model can simulate the 1975-2004 average patterns of rainfall, temperature, and sea level pressure over Australia. Subregions of Victoria are indicated. Victoria has an integrated catchment management system established under the Catchment and Land Protection Act 1994 (the CaLP Act). Under the CaLP Act, Victoria is divided into ten catchment regions, with a Catchment Management Authority (CMA) established for each region. (See: http://www.water.vic.gov.au/governance/catchment_management_authorities)

The ISC2010_VEGETATION_OVERHANG_S table is the Statistical Summary table for the Vegetation Overhang Metric at the 100m Section level. The ISC2010_VEGETATION_OVERHANG_S table is designed to JOIN to the ISC2010_RIVER_CENTRELINES_S feature class. River condition in Victoria is assessed every 5 years using the Index of Stream Condition (ISC). The Department of Environment and Primary Industries (DEPI) developed a methodology to assess the Physical Form and Riparian Vegetation components of the ISC using remote sensing data, specifically LIDAR and aerial photography. A State Wide mapping project was undertaken in 2010-13 to accurately map the Physical Form and Riparian Vegetation metrics of the ISC . Other ISC metrics were not assessed in the project and were derived from other sources. The Physical Form and Riparian Vegetation Metric products are a combination of mapped Vector and Raster data as well as Tabular Summary Statistics about the mapped features. In the context of the project, the term Metrics is used to refer to both the mapped features and the summary statistics. Remote sensing data used includes 15cm true colour and infra-red aerial photography and four return multi-pulse LiDAR data. This source data was used to derive a variety of Raster data sets including Digital Terrain Models, Slope, Vegetation Height and Vegetation Cover. The Digital Terrain and Slope rasters were used to map Physical Form metrics including Stream Bed, Top of Bank and River Centre Lines while the Vegetation Height and Cover rasters were used to map the Riparian Vegetation metrics. The Project Report "Aerial Remote Sensing for Physical Channel Form and Riparian Vegetation Mapping" describes the remote sensing and mapping approach used to create this data set.

Energy use profiles support effective planning and targeting of energy saving and decarbonising energy supply programs and community engagement. The Department of Sustainability and Environment (DSE) has developed energy consumption profiles for Victorian Local Government Areas. This tool transforms postcode-level source data provided by the Victorian energy distributors into consumption profiles across the municipality. It provides a profile of energy use by SLA for households across the municipality. Year to year comparisons can show changing patterns of energy use for households and on a per capita and per household basis. The tool also has the capacity to incorporate Commercial and Industrial energy use and trends over time.

This dataset is a model of watertable depth at 100m resolution containing interval values of <5m, 5-10m, 10-20m, 20-50m and >50m.The model was compiled as the difference between Digital Terrain Model (DTM) and watertable elevation in mAHD. Both models are at a raster resolution of 100m.