The Victorian Coastal Digital Elevation Model 2021 (VCDEM) incorporates several new datasets to previous versions of the dataset created in 2017 and 2010, integrating new bathymetric datasets to the VCDEM product. The VCDEM dataset is foundational to the Victorian Coastal Mapping Program (VCMP) and updates to the VCDEM will improve the understanding of dynamic coastal processes and their associated risks advanced by the VCMP. The VCDEM2021 produced by Veris is comprised of two major outputs: 1. HIGH RESOLUTION VCDEM2021 Contains gridded data sources with a gridded spatial resolution (pixel size) equal or superior to 10m in addition to vertical uncertainty meeting IHO Order 1b specifications (ie better than 0.5m). The high resolution VCDEM2021 will necessarily contain gaps where data does not meet these conditions. 2. SEAMLESS VCDEM2021 Contains gridded data sources with a gridded spatial resolution (pixel size) equal or superior to 10m in addition to vertical uncertainty meeting IHO Order 1b specifications (ie better than 0.5m). Low resolution bathymetric data is used in areas with no high resolution bathymetric coverage and algorithms are used to merge bathymetric to a seamless product.

test dataset for mt12

The Victorian Coastal Digital Elevation Model 2021 (VCDEM) incorporates several new datasets to previous versions of the dataset created in 2017 and 2010, integrating new bathymetric datasets to the VCDEM product. The VCDEM dataset is foundational to the Victorian Coastal Mapping Program (VCMP) and updates to the VCDEM will improve the understanding of dynamic coastal processes and their associated risks advanced by the VCMP. The VCDEM2022 produced by Veris is comprised of two major outputs: 1. HIGH RESOLUTION VCDEM2021 Contains gridded data sources with a gridded spatial resolution (pixel size) equal or superior to 10m in addition to vertical uncertainty meeting IHO Order 1b specifications (ie better than 0.5m). The high resolution VCDEM2021 will necessarily contain gaps where data does not meet these conditions. 2. SEAMLESS VCDEM2021 Contains gridded data sources with a gridded spatial resolution (pixel size) equal or superior to 10m in addition to vertical uncertainty meeting IHO Order 1b specifications (ie better than 0.5m). Low resolution bathymetric data is used in areas with no high resolution bathymetric coverage and algorithms are used to merge bathymetric to a seamless product.

Abstract This project represents a timeslice series of historical aerial photography datasets around Warrnambool-Mepunga, Kingston, Latrobe Valley and Mallacoota from the 1930's to the 1990's.The purpose of creating the ortho photo mosaics was to detect and measure changes (long term, progressive or cyclic). The type of shoreline change the photography aimed to identify included sandy beach-dune, scarped 'soft-rock', muddy mangrove shores and asset removal/construction. A secondary purpose of the photography was to map the change of vegetation. To achieve the purpose, a time series of repeated aerial photography was planned with epoch intervals of approximately 10 years (and a minumum of five years separation). The seven epochs planned for were 1930's,1940's,1950's,1960's,1970's 1980's and 1990's. For any given epoch where the study area was not covered completely by a historic photography project (series of air-photos taken on the same date or within a few days of each other) then the next most recent photography project was identified, processed and used for comparison. The aim was to keep each epoch as close as possible, This data is only available for Whole of Victorian Government use.

Model-based predictions of average deer abundance 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). Abundance estimates are provided as a numeric decimal of deer per square kilometre of public land within each grid cell. The technical report accompanying this data is available from the Arthur Rylah Institute (ARI) website: https://www.ari.vic.gov.au/__data/assets/pdf_file/0035/686591/ARI-Technical-Report-368-Deer-abundance-in-Victoria.pdf 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 abundance of one of the four species of deer by selecting 'Symbology > Band Rendering > Render Type = Singleband Pseudocolor' 4) Choose the band (species) you wish to display 5) Apply the changes

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: https://www.ari.vic.gov.au/__data/assets/pdf_file/0035/686591/ARI-Technical-Report-368-Deer-abundance-in-Victoria.pdf 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)