Search results for learning models
FiltersWMS
31 datasets for “learning models”
- data.gov.au
Machine Learning Models WMS
Geoscience Australia DataUpdated 8 Jan 2026
This web service contains map layers and coverages for machine learning models, using raster datasets which include radiometric …
- WMS
- GovData Germany
Forest Structure - Sentinel-1/2, GEDI - Germany, Yearly
open.bydataUpdated 11 Nov 2026
… The products were generated using a machine learning modelling approach that combines complementary spaceborne remote sensing sensors, namely …
- WMS
- DOWNLOAD
- data.gov.au
High resolution conductivity mapping using regional AEM survey and machine learning.
Geoscience Australia DataUpdated 16 Oct 2025
… We have used a machine learning modelling approach that establishes predictive relationships between the inverted flight-line modelled …
- ZIP
- WMS
- WCS
- Open Government Canada
Predictive model of Li-Cs-Ta pegmatite deposits
Natural Resources Canada | Ressources naturelles CanadaUpdated 2 Jul 2025
This model is derived from geological and geophysical data, which is processed using deep learning and natural language …
- HTML
- ESRI REST
- WMS
- GPKG
- data.gov.au
Soil and Landscape Grid National Soil Attribute Maps - Rock outcrop occurrence (3" resolution) - Release 1
Terrestrial Ecosystem Research Network's Data DiscoveryUpdated 10 Jun 2026
… A machine learning model was used to find relationships between observed data and associated environmental covariate data to …
- HTML
- WMS
- PNG
- data.gov.au
Unearthing Australia’s subsurface secrets - An integrated FAIR modelling approach
Geoscience Australia DataUpdated 16 Oct 2025
… A national coordination of data compilation with common standards, along with development of open-source modelling tools in …
- WMS
- WCS
- WMTS
- Open Government Canada
Predictive model of graphite
Natural Resources Canada | Ressources naturelles CanadaUpdated 2 Jul 2025
This model is derived from geological, geophysical and other forms of geodata. Feature extraction used deep learning. Predictive …
- HTML
- ESRI REST
- WMS
- GPKG
- data.gov.au
Data–driven prospectivity modelling of sediment–hosted Zn–Pb mineral systems and their critical raw materials
Geoscience Australia DataUpdated 16 Oct 2025
… Herein we integrate public geoscience datasets using a discrete global grid to system to model the mineral potential …
- HTML
- WFS
- WMS
- data.gov.au
Complete Radiometric Grid of Australia (Radmap) v4 2019 with modelled infill
Geoscience Australia DataUpdated 16 Oct 2025
… used as a seamless dataset for predictive modelling using machine learning. The product can be seen as an …
- ZIP
- WMS
- WCS
- data.gov.au
National surface and near-surface conductivity grids
Geoscience Australia DataUpdated 16 Oct 2025
… The GB model is a machine learning (ML) ensemble technique used for both regression and classification tasks (https …
- ZIP
- WMS
- WCS
- Open Government Canada
Pan-Canadian predictive model of Carbonatite-hosted REE and Nb deposits
Natural Resources Canada | Ressources naturelles CanadaUpdated 2 Jul 2025
A predictive model for Canadian carbonatite-hosted REE ± Nb deposits is presented herein. This model was developed by …
- HTML
- ESRI REST
- WMS
- GPKG
- Open Government Canada
Updated flake graphite national prospectivity
Natural Resources Canada | Ressources naturelles CanadaUpdated 19 Oct 2026
… Feature extraction was performed using an autoencoder (deep learning). Predictive modelling was performed using the deep ensemble method …
- HTML
- GPKG
- ESRI REST
- WMS
- Open Government Canada
Updated magmatic nickel national prospectivity
Natural Resources Canada | Ressources naturelles CanadaUpdated 19 Oct 2026
… Feature extraction was performed using an autoencoder (deep learning). Predictive modelling was performed using the deep ensemble method …
- HTML
- GPKG
- ESRI REST
- WMS
- Open Government Canada
Updated Mississippi Valley-type lead-zinc national prospectivity
Natural Resources Canada | Ressources naturelles CanadaUpdated 19 Oct 2026
… Feature extraction was performed using an autoencoder (deep learning). Predictive modelling was performed using the deep ensemble method …
- HTML
- GPKG
- ESRI REST
- WMS
- data.gov.gr
Modelled occurrence probability for Posidonia oceanica meadows across the Mediterranean Sea
Περιφέρεια ΚρήτηςUpdated 1 Nov 2026
… model P. oceanica distribution across the whole Mediterranean basin. A Random Forest (i.e. a Machine Learning technique …
- WMS
- PNG
- XML
- ZIP
- data.gov.au
EFTF cover thickness model in the Darling-Curnamona-Delamerian (DCD) region
Geoscience Australia DataUpdated 16 Oct 2025
… was used to model the depth of the Cenozoic surface. Machine learning allows to learn relationship between datasets …
- ZIP
- WMS
- WCS
- WMTS
- data.gov.au
Australia wide daily volumetric soil moisture estimates
Terrestrial Ecosystem Research Network's Data DiscoveryUpdated 10 Jun 2026
… using a machine learning approach. To help increase model accuracy, the internal SMIPS model states are adjusted or …
- HTML
- WMS
- PNG
- data.gov.au
Great Barrier Reef 10m Grid (GBR10) GBRMP Benthic
Australian Ocean Data NetworkUpdated 16 Jul 2026
… Fitting a supervised machine learning model (e.g. random forest) to known occurrences in order to classify segments …
- TIF
- WMS
- HTML
- PNG
- data.gov.au
Great Barrier Reef 10m Grid (GBR10) GBRMP Benthic
Australian Ocean Data NetworkUpdated 28 Sept 2026
… Fitting a supervised machine learning model (e.g. random forest) to known occurrences in order to classify segments …
- TIF
- WMS
- HTML
- PNG
- Open Government Canada
Future - Flood Susceptibility Mapping
Natural Resources Canada | Ressources naturelles CanadaUpdated 24 Apr 2026
This series of projected future flood susceptibility maps were generated using an XGBoost machine learning model trained on …
- HTML
- JSON
- WMS