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  • VEACRECS25 shows recommended public land use for each Crown parcel. It portrays recommendations resulting from studies conducted by the Victorian Environmental Assessment Council (and former Environment Conservation Council and Land Conservation Council). Recommendations shown are as approved or varied by Government, and include subsequent formal amendments and revocations. Land use categories have been assigned to Crown land parcels. VicMap Property parcel layer was used as the base. Boundaries are based on the best available information at the time. Continuing approved recommendations from previous studies are also shown. Note that public land use recommendations were not made for certain cities, rural cities, towns and boroughs. ..

  • LCC_ECC_VEAC_INVESTIGATIONS shows the geographic boundaries of the Land Conservation Council (LCC), Environment Conservation Council (ECC) and Victorian Environmental Assessment Council (VEAC) investigation areas. Statewide extent investigations are not included in the dataset: Statewide Assessment of Public Land Use (1988), Rivers and Streams Special Investigation (1991), Wilderness special investigation (1991), Statewide Assessment of Public Land (2017).

  • The Statewide Marine Habitat Map 2023 was developed by DEECA applying novel machine learning methods that model and predict habitat distributions as well as a mosaic of former mapping products (listed below). The Statewide map represents 24 marine and coastal habitats complexes at Level 3, Victoria's Combined Biotope Classification Scheme (CBiCS) described by Edmunds and Flynn (2015, 2018; 2021). The final map comprises of 83% its area from predictive modelling, with the remaining 17% of area from synthesised existing habitat maps. Predictive Model: A total of 32,998 habitat survey sites (ground-truth records) were used within the model, along with 28 environmental properties mapped at a 10m resolution (including a Digital Elevation Model DEM (VCDEM2021), computed benthic terrain characteristics (toolkit: Walbridge et al. 2018), Chlorophyl a (IMOS 2000a), Sea Surface Temperature SST (IMOS 2000a), Net Primary Productivity NPP (IMOS 2000b), Sediments (Geoscience Australia; Li et al. 2011a,b,c), waves (Liu et al. 2022). To predict the distribution of habitats across Victorian waters the powerful and flexible Random Forest machine learning algorithm was applied. Random Forest is an ensemble model using bagging as the ensemble method and decision trees as the individual model (Breiman 2001). The modelling produced an accuracy (Out-of-bag) of 89%. Map Synthesis: A mosaic of former mapping products that provided higher resolution mapping by aerial imagery, field observations and high-resolution modelling were integrated into the map, classifying habitat according to the CBICS habitat classification scheme at level 3. Assessed and synthesised maps and citations include: Corangamite Coast Marine Habitat December 2009 (ANZVI0803005530); East Gippsland Marine Habitats November 2009 (ANZVI0803003974); Discovery Bay Marine National Park habitat mapping 2006 (ANZVI0803004053); Portland Coastal Habitats (ANZVI0803004236) ; Corner Inlet Mapping Marine National Park North and South 2004 (ANZVI0803004051) ; Merri Marine Sanctuary 2004 (ANZVI0803004058); Western Port Bay Biotope Mapping Fathom Pacific (2016) CBiCS-Mapping. Central Victoria Coastal Habitats (ANZVI0803004135); Mallacoota Coastal Habitats (ANZVI0803004235); Western Port Rhodolite (ANZVI0803005430) & Western Port Biogenic Reefs; Port Phillip Bay Habitat Map 2021 (ANZVI0803009278); Saltmarsh and Mangrove Habitats; DELWP 2021 Statewide Marine Habitat Map 2021 (ANZVI0803009286) and relevant citations: Ball (1999), Ball et al. (2010). Ball & Blake (2007a), Ball & Blake (2007b), Blake and Ball (2001), Blake et al. (2013), Boon et al. (2011), Cohen et al (2000), Deakin Marine Mapping (Zavalas, R et al. 2018), DELWP (1994), Edmunds &Flynn (2015), Fathom Pacific (2020), Ford et al (2016), GeoHab Victoria Estuaries Geomorphology (2010), Ierodiaconou 2007, Ierodiaconou et al. 2018, Mazor et al. (2021), Monk et al. (2011), Poore (1992), Roob and Ball (1997), Victoria Department of Transport (1999), Young et al. 2022, Zavalas, R et al. 2018. Applications: The Statewide Marine Habitat Map 2023 provides broad habitat complexes across the state and provides greater knowledge of the ecological diversity across Victoria¿s waters. The map should be used at broad scales of >25 m, and where information of larger habitat complexes is needed. This work can support the management of large-scale habitats, their condition, marine spatial planning, strategic management prospect (SMP), FeAST risk assessments, and other broad scale applications to support management decisions across Victoria. The habitat model and resulting map provides an updated broad-scale habitat map across Victoria¿s state waters and provides a baseline for future data to build upon. Full Methodology: Citation: Mazor, T., Watermeyer, K., Hobley, T., Grinter, V., Holden, R., MacDonald, K. and Ferns, L. (2023). Statewide Marine Habitat Map. Habitat Complex Modelling Method (CBiCS Level 3). The State of

  • Replaced by the dataset VMADMIN_DEPI_REGION. This dataset contains the Department of Sustainability & Environment (DSE) Regional Boundaries as defined by DSE. The regions are based on the Victorian Government Regional Boundaries. The main difference is that the three metropolitan regions have been aggregated to form the Port Phillip region, and the Grampians and Barwon South-West regions have been aggregated to form the South West region. There are five regions. Aligned to Road Network - Vicmap Transport.

  • This version of the areas of the cultural heritage sensitivity dataset (ACHS) does not contain any attribute information. This dataset contains a spatial representation of "Areas of Cultural Heritage Sensitivity" as specified in Division 3, Part 2 of the Aboriginal Heritage Regulations 2018. Areas of cultural heritage sensitivity are areas that are either known to contain, or are likely to contain Aboriginal cultural heritage places and objects. These areas, which include various landforms within Victoria, are defined in the Aboriginal Heritage Regulations 2018. This polygon dataset is a representation of those areas as defined in the Regulations. The polygon features within the dataset have been derived from several sources, including geological and hydrological data. Note: This dataset is based on the best available information and should be used in conjunction the information contained in Division 3, Part 2 of the Aboriginal Heritage Regulations 2018. This data is under active revision to improve the representation as better quality source data becomes available.

  • GEDIS REFID: 10881; SOURCE MAP: G10881_parishplan_Bahgallah_31k_600dpi_colour_master.tif; SUBJECT: CALDWELL, J.J., 1941. Parish of Bahgallah 1:31,680 (40 chains:1 inch) geological map. Plan No 6p. Geological Survey of Victoria.

  • Dataset: kerang_2022nov18_sat_vis_150cm_epsg32754 Assembly: Mosaic

  • This layer contains points showing the location of groundwater bores in the Water Measurement Information System (WMIS) that have recorded co-ordinates. WMIS is the primary access point to search, discover, access and download surface water and groundwater monitoring data collected by DEPI and its partners. WMIS contains data from a range of sources, primarily from the registration of bores requiring a bore construction licence (Water Act, 1989), as well as groundwater level and groundwater chemisty data. For more detailed information on individual bores, the user is referred to the WMIS site at

  • Model-based predictions of the distribution of deer on Victorian public land. Model predictions are based on camera-trap and deer sign surveys at 317 sites across Victoria conducted between 2021 and 2023. The raster data is divided into four layers/bands for the four species analysed in this study: Sambar deer (Cervus unicolor), Fallow deer (Dama dama), Red deer (Cervus elaphus) and Hog deer (Axis porcinus). Distribution estimates are presented as a categorical value of model confidence in deer occupancy per square kilometre of public land within each grid cell. The values represent (i) the Smallest estimated range (5th percentile), (ii) the Average/median estimated range (50th percentile), and (iii) the Largest estimated range (95th percentile). The technical report accompanying this data is available from the Arthur Rylah Institute (ARI) website: The raster data may be loaded into programs such as R or QGIS for analysis. When opening the data in QGIS, undertake the following steps: 1) Follow 'Layer > Add Later > Add Raster Layer' to select the tif file to be added 2) Right-click on the added layer in the 'Layers' panel and select 'Properties' 3) Visualise the distribution of one of the four species of deer by selecting 'Symbology > Band Rendering > Render Type = Paletted/Unique Values' 4) Choose the band (species) you wish to display 5) Click the 'Classify' button 6) The layer values can be renamed according to the associated XML datafile. The values are: 0 = Not present, 1 = Largest estimated range (95th percentile), 2 = the Average/median estimated range (50th percentile), and 3 = Smallest estimated range (5th percentile)

  • This dataset is derived from the Melway directory and contains the map indices for the 1:25 000 Phillip Island maps.