AndreaBozzo/ceres-open-data-index huggingface dataset:
Landsat 5 Satellite Imagery for selected areas of Great Barrier Reef and Torres Strait (NERP TE 13.1, eAtlas AIMS, source: NASA)

This dataset contains Landsat 5 imagery for selected areas of Queensland, currently Torres Strait and around Lizard Island and Cape Tribulation. 

This collection was made as a result of the development of the Torres Strait Features dataset. It includes a number (typically 4 - 8) of selected Landsat images for each scene from the entire Landsat 5 archive. These images were selected for having low cloud cover and clear water. The aim of this collection was to allow investigation of the marine features.

The complete catalogue of Landsat 5 for scenes 96_70, 96_71, 97_67, 97_68, 98_66, 98_67, 98_68_99_66, 99_67 and 99_68 were downloaded from the Google Earth Engine site ( https://console.developers.google.com/storage/earthengine-public/landsat/ ). The images were then processed into low resolution true colour using GDAL. They were then reviewed for picture clarity and the best ones were selected and processed at full resolution to be part of this collection.

The true colour conversion was achieved by applying level adjustment to each channel to ensure that the tonal scaling of each channel was adjusted to give a good overall colour balance. This effectively set the black point of the channel and the gain. This adjustment was applied consistently to all images.



Red: Channel B3, Black level 8, White level 58

Green: Channel B2, Black level 10, White level 55

Blue: Channel B1, Black level 32, White level 121


Note: A constant level adjustment was made to the images regardless of the time of the year that the images were taken. As a result images in the summer tend to be brighter than those in the winter.

After level adjustment the three channels were merged into a single colour image using gdal_merge. The black surround on the image was then made transparent using the GDAL nearblack command.

This collection consists of 59 images saved as 4 channel (Red, Green, Blue, Alpha) GeoTiff images with LZW compression (lossless) and internal overviews with a WGS 84 UTM 54N projection.

Each of the individual images can be downloaded from the eAtlas map client (Overlay layers: eAtlas/Imagery Base Maps Earth Cover/Landsat 5) or as a collection of all images for each scene.

Data Location:

This dataset is filed in the eAtlas enduring data repository at: data\NERP-TE\13.1_eAtlas\QLD_NERP-TE-13-1_eAtlas_Landsat-5_1988-2011

Tags: marine
Organization: Australian Ocean Data Network
NERP TE Project 9.2 - Design and implementation of Management Strategy Evaluation for the Great Barrier Reef inshore (MSEGBR), 2011-2014 (CSIRO)

This project will develop a Management Strategy Evaluation (MSE) framework to build understanding of the key human uses and drivers of change in the inshore Great Barrier Reef (GBR), and to inform GBR stakeholders of the likely consequences, costs and benefits of particular management decisions that aim to minimise the impacts on biodiversity, particularly from inshore multi-species fisheries. The MSE approach involves developing models  that capture the key attributes of the management problem, including processes of biophysical systems, human uses of ecosystems and their socio-economic drivers, and the three major components of an adaptive management strategy – monitoring, assessment and management decision processes.

A staged approach to the MSE is proposed. It will include:





Scoping of the project, data and information gathering, stakeholder elicitation of objectives and understanding key processes. 




Assessment of management strategies using a qualitative MSE in the GBR region. This will consist of a) developing management strategies, b) assessing the relative impact of the management strategies against the objectives and c) steps required for implementation.



This project is now complete.

Tags: National Environmental Research Program Tropical Ecosystems Hub, marine
Organization: Australian Ocean Data Network
DTET—Digital Projects Dashboard contribution

Data published by the Department of Trade, Employment and Training (DTET) that supports the Digital Projects Dashboard. Data resources include the list of digital and information and communication technology (ICT) enabled initiatives and their reported status.
For further information, visit the Queensland Government Digital Projects Dashboard website. Please refer to the pages: About the dashboard, FAQs and Glossary.

Tags: dashboard, digital-projects-dashboard, ict, ict-dashboard, initiatives, projects
Organization: Trade, Employment and Training
Wilson Inlet Seagrass Survey - Extent (DWER-115)

Wilson Inlet was surveyed in December 2017, April 2018, December 2019, December 
2020, December 2021 and December 2022 by underwater drop camera observations 
and/or observations through a viewing cone. Seagrass distribution and cover 
(as percentage cover in categories: 0, 0-10%, 10-25%, 25-50%, 50-75%, 75-90%, 
90-100%) were recorded. The canopy height (in 10 cm intevals) and epiphytic 
cover (as low, medium, high) was also estimated. Macroalgae distribution and 
cover (as percentage cover in categories: 0, 0-10%, 10-25%, 25-50%, 50-75%, 
75-90%, 90-100%) were recorded. At approximately a third of the sites, physical 
water profiles, photosynthetically active radiation (euphotic depth), and 
secchi depth were recorded. 

The datasets making up the seagrass survey data are:

Wilson_Seagrass - point dataset
Wilson_Seagrass_Extent - polygon showing presence/absence derived from points
Wilson_Seagrass_Cover - polygon showing percentage cover derived from points

Layers:

Wilson_Seagrass_Dec_2017 
    Wilson_Seagrass where Year = '2017'
Wilson_Seagrass_Apr_2018
    Wilson_Seagrass where Year = '2018'
Wilson_Seagrass_Dec_2019
    Wilson_Seagrass where Year = '2019'
Wilson_Seagrass_Dec_2020
    Wilson_Seagrass where Year = '2020'
Wilson_Seagrass_Dec_2021
    Wilson_Seagrass where Year = '2021'
Wilson_Seagrass_Dec_2022
    Wilson_Seagrass where Year = '2022'

Wilson_Seagrass_Extent_Dec_2017 
    Wilson_Seagrass_Extent where Year = '2017'
Wilson_Seagrass_Extent_Apr_2018
    Wilson_Seagrass_Extent where Year = '2018'
Wilson_Seagrass_Extent_Dec_2019
    Wilson_Seagrass_Extent where Year = '2019'
Wilson_Seagrass_Extent_Dec_2020
    Wilson_Seagrass_Extent where Year = '2020'
Wilson_Seagrass_Extent_Dec_2021
    Wilson_Seagrass_Extent where Year = '2021'
Wilson_Seagrass_Extent_Dec_2022
    Wilson_Seagrass_Extent where Year = '2022'

Wilson_Seagrass_Cover_Dec_2017 
    Wilson_Seagrass_Cover where Year = '2017'
Wilson_Seagrass_Cover_Apr_2018
    Wilson_Seagrass_Cover where Year = '2018'
Wilson_Seagrass_Cover_Dec_2019
    Wilson_Seagrass_Cover where Year = '2019'
Wilson_Seagrass_Cover_Dec_2020
    Wilson_Seagrass_Cover where Year = '2020'
Wilson_Seagrass_Cover_Dec_2021
    Wilson_Seagrass_Cover where Year = '2021'
Wilson_Seagrass_Cover_Dec_2022
    Wilson_Seagrass_Cover where Year = '2022'


Tags: Biota, Estuary, Flora, Seagrass
Organization: Department of Water and Environmental Regulation
Lower Swan Canning Estuary to Upper Swan Estuary Water Quality Monitoring 2016-17

The Department of Biodiversity, Conservation and Attractions (DBCA) conducts routine monitoring of water quality in the Swan Canning Estuary. Data collected through the monitoring program is used to inform management of the river system by DBCA.

Data produced through the monitoring program provides essential information to assess system response to management actions and to report against estuary water quality targets, and phytoplankton trigger levels. Data produced have also been utilised in numerous investigations conducted by both government agencies and tertiary institutions, including modelling, that contribute to our understanding of estuary condition and response and that evaluate potential impacts on the system into the future.

Data collected is stored in the Water Information Network (WIN) database maintained by the Department of Water and Environmental Regulation (DWER) and is made publicly available via the Water Information Reporting (WIR) portal.

Note: to access the data, select the data source link located on the right-hand side.

Tags: Swan Canning, asset_water_quality
Organization: Department of Biodiversity, Conservation and Attractions
Thermal image 2012

PLEASE NOTE: The raw files (GEOTiff and Esri database files) are available for download within the attachments of the About section,  please select the 'About' button and scroll down to see the attachments. Captured on 24th February 2012 this thermal image shows temperature differences between different surfaces in the municipality.

Preview







Tags: changemaker, forest, heat, parks, researcher, thermal, trees, urban-forest, urbanforest
Organization: City of Melbourne Open Data
Key Localities Gully Remediation (NESP TWQ 2.1.4, CSIRO)

An updated version of this dataset is available at https://eatlas.org.au/data/uuid/38b496a3-3fba-42e7-b904-902f68040c85

Key Gully monitoring localities (headcuts and monitoring instrumentation) and outlines of the properties within which they are located. The data in presented in this metadata are part of a larger collection and are intended to be viewed in the context of the project. For further information on the project, view the parent metadata record: Demonstration and evaluation of gully remediation on downstream water quality and agricultural production in GBR rangelands (NESP TWQ 2.1.4, CSIRO)

Methods:

Key Gully Localities were extracted from the 2017 or 2018 RTK GPS surveys for each gully site (see Site_Configuration_and_Survey). 

Property Boundaries were generated by extracting polygons from the 2016 Digital Cadastre Database (DCDB) and simplifying to a single polygon. Area in hectares was calculated and appended to polygon attributes.

KMZ’s are exported version of the original ArcGIS shapefiles

Format:

This data collection consists of two shapefiles (zipped) and two equivalent KMZ files with the following names:

NESP_Gully_Key_localities
Key gully localities include the RTK GP location of the instrumentation and the RTK GPS location of the nickpoint in the gully headcut rim.

NESP_Gully_Property_Boundaries
Boundaries for the properties on which the paired control/treatment gullies are located.

Data Dictionary:

Attributes for Property_Boundaries.shp include property NAME and the area in hectares (AREA_HA).

Attributes for Key Locations include 
X,Y (MGA94 Z55) and Z (AHD)
Timestamp associated when RTK surveyed
Type- HEADCUT, INSTR
Survey – type of survey and year, APPROX is best guess from Lidar or GoogleEarth
Site_Code – short form code for sites where
MIV = Minnievale
MV = Meadowvale
MW = Mount Wickham
SB = Strathbogie
VP = Virginia Park
 - Treatment/Control

Property – Full name of property
Treat_type – Treatment or control

References:

Bartley, Rebecca; Hawdon, Aaron; Henderson, Anne; Wilkinson, Scott; Goodwin, Nicholas; Abbott, Brett; Baker, Brett; Matthews, Mel; Boadle, David; Jarihani, Ben (Abdollah). (2018) Quantifying the effectiveness of gully remediation on off-site water quality: preliminary results from demonstration sites in the Burdekin catchment (second wet season). RRRC: NESP and CSIRO. csiro:EP184204.

Data Location:

This dataset is filed in the eAtlas enduring data repository at: data\NESP2\2.1.4_Gully-remediation-effectiveness

Organization: Australian Ocean Data Network
eReefs Basemap - GIS layers Reefs, Rivers, Cities, Basins, Countries (AIMS)

This dataset collection contains GIS layers for creating the AIMS eReefs visualisation maps (https://ereefs.aims.gov.au/). These datasets are useful for creating A4 printed maps of the Great Barrier Reef and the Coral Sea. It contains the following datasets:
- Countries - Australia plus surrounding countries at 1:10M scale. Crop of Natural Earth Data 1:10 Admin 0 - Countries dataset. Allows filtering out of surrounding countries.
- Cities - 21 Cities along the Queensland coastline. 
- Basins - Drainage basins adjacent to the Great Barrier Reef along the eastern Queensland coastline. Derived from Geoscience Australia River Basins 1997 dataset. It is a subset and reprojection.
- Land and Basins - This layer contains both Queensland and PNG land areas, along with the river basins along the eastern Queensland coastline. This is an integrated layer that represents both the background land area and the river basins all in one layer. This layer saves having to map the land area, then overlay the river basins. In this way each polygon only needs to be rendered once. The goal of this layer is to optmise the rendering time of the eReefs base map. This dataset is made up from the Geoscience Australia Australia's River Basins 1997 dataset for the Queensland coastline and the eastern Queensland basins. PNG is copied from Natural Earth Data 10 m countries dataset.
- Rivers - Rivers that drain along the Queensland eastern coast. This is a subset of the Geoscience Australia Geodata Topo 1:5M 2004.
- Reefs - Boundaries of reefs in GBR, Torres Strait and Coral Sea. In the Coral Sea it contains the atoll platform boundaries rather than the individual reefs. This is derived from the GBRMPA GBR features dataset, AIMS Torres Strait features dataset and the AIMS Coral Sea features dataset. These were combined and simplified to a scale of 1:1M. Note that this simplification resulted in multiple neighbouring reefs being grouped together. This dataset is intended for visual rendering of maps. 
- Clip regions - Polygons for clipping eReefs data to the GBR. Also contains approximate polygons for Coral Sea, Torres Strait, PNG and New Caledonia. This was created principally for setting the region attribute for the Reefs dataset, but was made available as it is useful for clipping eReefs data to the GBR for plotting purposes.

Methods:
Most of the base map layers are derived from a variety of data sources. The full workflow used to transform these source datasets is documented on GitHub (https://github.com/eatlas/GBR_AIMS_eReefs-basemap). 

Limitations of the data:
The datasets in this collection have been cropped and simplified for the purposes of creating low detail printed maps of the GBR. They are not intended for creating a high resolution base map. 

Format of the data:
Shapefile and GeoJSON files. The Cities dataset is provided as a CSV file.

Location of the data:
This dataset is filed in the eAtlas enduring data repository at: data\custodian\2018-2024-eReefs\GBR_AIMS_eReefs-basemap

Tags: Marine, World
Organization: Australian Ocean Data Network
The Maze 1983 (LGATE-279)

Part of a collection of WA's iconic theme parks from the 1980s. Many of these sites are still around today, but are either bigger, laying in ruins or modified versions of their former lives. Landgate has delved into the archives to extract 'wicked' aerial imagery of some of these venues for WA Heritage Week. Take a trip back in time without the need of a DeLorean!

This dataset contains vectorised boundaries for the theme park. To view the aerial photography for the sites please refer to https://catalogue.data.wa.gov.au/group/interesting-historical-photography © Western Australian Land Information Authority (Landgate). Use of Landgate data is subject to Personal Use License terms and conditions unless otherwise authorised under approved License terms and conditions. 

Tags: heritage, heritage-week, park, theme
Organization: Landgate
NESP MaC Project 4.12 - Protecting valuable shoreline mangroves of northern Australia, 2024-2026 (JCU)

This record provides an overview of the NESP Marine and Coastal Hub study - Protecting valuable shoreline mangroves of northern Australia. For specific data outputs from this project, please see child records associated with this metadata.

The mass death (~80 km2) and dieback of shoreline mangroves around the Gulf of Carpentaria (GOC) and across northern Australia in 1982 and 2015 was a wake-up call to the vulnerability and immense importance of marine coastal ecosystems like mangroves. It is essential that we fully understand the circumstances surrounding such catastrophic events, the environmental triggers identified, and what we might do to restore the damage while also preventing future occurrences. In response to the 2015 mass dieback event (the world’s largest such recorded event), the NESP commissioned an Emerging Priority project that utilised aerial surveys to assess the extent of the dieback along the entire Gulf of Carpentaria coastline. It is proposed to resurvey GOC shorelines for their current condition whilst taking the opportunity further to devise a well-considered and fully costed rapid response plan that will include innovative preventative management outcomes for the longer-term sustainability of threatened but highly-valued coastal marine ecosystems of northern Australia. 

Planned Outputs
 • aerial survey imagery [imagery]
 • satellite imagery analysis [spatial dataset]
 • field &amp; environmental surveys [tabular dataset]
 • Final technical report with analysed data and a short summary of recommendations for policy makers of key findings [written]

Tags: National Environmental Science Program Marine and Coastal (NESP MaC) hub, marine
Organization: Australian Ocean Data Network
Woody Change 2020-2021 (LGATE-397)

Vegetation change products are produced annually identifying locations where the perennial woody vegetation from the vegetation cover datasets based on Landsat imagery (30m ground pixel) has changed between the forest, sparse woody and non woody classifications. Change classes include; no change, non-woody to sparse, non-woody to forest, sparse to non-woody, forest to non-woody and forest to sparse.

Click here for more information.

Tags: Land, LandMonitor, Monitor, class, imagery, trend
Organization: Landgate
Vegetation Trend 2012-2022 (LGATE-461)

The Vegetation Trend product is a multiband image file that contains summaries of change in reflectance of vegetation over time using the Land Monitor Landsat based vegetation index related to vegetation density (red band + short wave infrared band 1) calculated for each annual date of imagery. Two time periods are provided in the south west agricultural zone only where the Land Monitor index can be more confidently applied, these time periods are 1990-current year and the last 10 years. The summaries are statistical measures of mean, linear trend over time, quadratic trend over time, standard deviation about mean, residual standard deviation after fitting linear trend and residual standard deviation after fitting linear and quadratic trends. The statistical summaries can be displayed separately or together to summarise trends and stability of vegetation over time as measured by the Land Monitor vegetation index, and in particular to highlight areas with different patterns of change.

Click here for more information.

Tags: Land, LandMonitor, Monitor, class, imagery, trend
Organization: Landgate
Wilson Inlet Seagrass Survey - Cover (DWER-114)

Wilson Inlet was surveyed in December 2017, April 2018, December 2019, December 
2020, December 2021 and December 2022 by underwater drop camera observations 
and/or observations through a viewing cone. Seagrass distribution and cover 
(as percentage cover in categories: 0, 0-10%, 10-25%, 25-50%, 50-75%, 75-90%, 
90-100%) were recorded. The canopy height (in 10 cm intevals) and epiphytic 
cover (as low, medium, high) was also estimated. Macroalgae distribution and 
cover (as percentage cover in categories: 0, 0-10%, 10-25%, 25-50%, 50-75%, 
75-90%, 90-100%) were recorded. At approximately a third of the sites, physical 
water profiles, photosynthetically active radiation (euphotic depth), and 
secchi depth were recorded. 

The datasets making up the seagrass survey data are:

Wilson_Seagrass - point dataset
Wilson_Seagrass_Extent - polygon showing presence/absence derived from points
Wilson_Seagrass_Cover - polygon showing percentage cover derived from points

Layers:

Wilson_Seagrass_Dec_2017 
    Wilson_Seagrass where Year = '2017'
Wilson_Seagrass_Apr_2018
    Wilson_Seagrass where Year = '2018'
Wilson_Seagrass_Dec_2019
    Wilson_Seagrass where Year = '2019'
Wilson_Seagrass_Dec_2020
    Wilson_Seagrass where Year = '2020'
Wilson_Seagrass_Dec_2021
    Wilson_Seagrass where Year = '2021'
Wilson_Seagrass_Dec_2022
    Wilson_Seagrass where Year = '2022'

Wilson_Seagrass_Extent_Dec_2017 
    Wilson_Seagrass_Extent where Year = '2017'
Wilson_Seagrass_Extent_Apr_2018
    Wilson_Seagrass_Extent where Year = '2018'
Wilson_Seagrass_Extent_Dec_2019
    Wilson_Seagrass_Extent where Year = '2019'
Wilson_Seagrass_Extent_Dec_2020
    Wilson_Seagrass_Extent where Year = '2020'
Wilson_Seagrass_Extent_Dec_2021
    Wilson_Seagrass_Extent where Year = '2021'
Wilson_Seagrass_Extent_Dec_2022
    Wilson_Seagrass_Extent where Year = '2022'

Wilson_Seagrass_Cover_Dec_2017 
    Wilson_Seagrass_Cover where Year = '2017'
Wilson_Seagrass_Cover_Apr_2018
    Wilson_Seagrass_Cover where Year = '2018'
Wilson_Seagrass_Cover_Dec_2019
    Wilson_Seagrass_Cover where Year = '2019'
Wilson_Seagrass_Cover_Dec_2020
    Wilson_Seagrass_Cover where Year = '2020'
Wilson_Seagrass_Cover_Dec_2021
    Wilson_Seagrass_Cover where Year = '2021'
Wilson_Seagrass_Cover_Dec_2022
    Wilson_Seagrass_Cover where Year = '2022'


Tags: Biota, Estuary, Flora, Seagrass
Organization: Department of Water and Environmental Regulation
DNA Barcode Reference Library

DNA barcode information and metadata, generated from Ecosystem Science in house collections. 

Barcode information is also uploaded into Genbank and BOLD, and accession numbers are updated in the 'Sequence Information' spreadsheet. 

Note: to access the data, select the data source link located on the right-hand side.

Tags: DNA, Invertebrates, barcodes
Organization: Department of Biodiversity, Conservation and Attractions
Vegetation History 90 05 21 (LGATE-366)

The Vegetation History product is a visual display produced from a Land Monitor developed Landsat imagery vegetation index related to vegetation density (red band + short wave infrared band 1) over three dates. It provides visual displays that highlight areas of change in vegetation density over time. The product is suitable for visual interpretation of changes over the period only. Other data products provide information that are more suitable for numerical summary and analysis.

Click here for more information.

Tags: Land, LandMonitor, Monitor, class, imagery, trend
Organization: Landgate
GBR - Basic water quality of Cockle Bay, Magnetic Island 2008-2011 (MTSRF 4.8.4s, JCU)

This is data associated with MTSRF Task 4.8.4s, a MTSRF supported PhD project titled /Biology and ecology of the blacktip reef shark/. As part of this project, basic water quality data were collected during shark tagging trips at the study site - Cockle Bay Reef at Magnetic Island. The meta data regarding these shark catch and tagging trips are recorded in a separate data file.

Basic water quality of Cockle Bay was measured at weekly to monthly intervals with handheld instruments - a YSI water quality meter (temp, salinity, condutivity, dissolved oxygen), and secchi disk depth.

Data units:
* Temperature - Degrees celcuis
* Salinity - ppt
* Conductivity - ms
* Dissolved oxygen - mg/l and % saturation
* Secchi depth - cm

Tags: marine
Organization: Australian Ocean Data Network
Australia's River Basins 1997 (GA)

Australia's River Basins 1997 is the result of a joint State, Territory and Commonwealth Government project to create a national spatial database of major hydrological basins. It shows the boundaries of Australia's basins as defined by the Australian Water Resources Management Committee (WRMC).

Australia is divided into drainage divisions which are sub-divided into water regions which are in-turn sub-divided into river basins. The data includes the name and number of each of the 245 drainage basins, 77 regions, and 12 divisions.

This metadata was prepared for the eAtlas and is not authoritative. Please contact the custodian for an authoritative record.

Data Location:

A copy of this dataset is filed in the eAtlas enduring data repository at: data\other\AU_GA_River-basins-1997

Tags: BOUNDARIES, GIS, National dataset, WATER Hydrology, catchments, environmental, hydrology, mapping
Organization: Australian Ocean Data Network