Sydney Informatics Hub presents:
AgReFed Data-Harvester Workshop for Python users
The AgReFed Data-Harvester enables reusable workflows for data downloads, feature extraction and spatial-temporal processing of ecological and environmental data into ready-made datasets for machine learning and geospatial insight.
In this hands-on workshop, we will showcase:
1. Automatic download and extraction of:
- Landsat/Sentinel data via Google Earth Engine (e.g., seasonal NDVI)
- National calibrated Landsat/Sentinel data via Digital Earth Australia (DEA) Geoscience Earth Observations
- Soil and Landscape Grid of Australia (SLGA)
- SILO Climate Database (e.g., temperature, rainfall)
- National Digital Elevation Model (DEM) 1 arcsec
- Radiometric Data
2. Spatial and temporal extraction and processing from obtained datasets
3. Visualisation of data layers and satellite images from Google Earth Engine
4. Cloud-coverage masking for satellite image processing
5. Wrangling points of interest into a machine learning-friendly format
Target audience:
This workshop will be of interest to researchers and students in Agriculture, Environmental Science, Geosciences, as well as others interested in working with geo-spatial datasets, especially via spatio-temporal processing of open environmental and satellite-derived data. Additionally, anyone interested in joining an early-phase open-source project are encouraged to come and help develop!
Workshop format:
3 hours online (with breaks). Registered attendees will receive a Zoom link closer to the date.
Pre-requisites:
A small amount of Python knowledge used within a Jupyter environment will be useful. An interactive online environment will be provided for users for the workshop (with installation instructions provided for those wishing to run things locally).
For more information:
sih.training@sydney.edu.au
