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AgReFed Data Harvester Workshop

https://www.sydney.edu.au/research/facilities/sydney-informatics-hub/workshops-and-training/training-calendar.html

Description:

Sydney Informatics Hub presents:

AgReFed Data-Harvester Workshop for R 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

  1. Spatial and temporal extraction and processing from obtained datasets

  2. Visualisation of data layers and satellite images from Google Earth Engine

  3. Cloud-coverage masking for satellite image processing

  4. 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 basic knowledge of R and RStudio is highly recommended; familiarity with tidyverse libraries will be advantageous. An interactive online RStudio environment will be provided for all users for the workshop (with installation instructions provided for those wishing to run things locally).

Note: The AgReFed Data-Harvester is accessible via both R and Python. If you would like to attend a Python workshop instead of (or in addition to) the R stream, please let us know of your interest by entering your email here: https://sydney.au1.qualtrics.com/jfe/form/SV_9TUKiEjaNEFPifk

For more information: 

sih.training@sydney.edu.au 

Start: Tuesday, 25 October 2022 @ 09:30

End: Tuesday, 25 October 2022 @ 12:30

Timezone: Sydney

City: Sydney  Country: Australia

Eligibility:
  • Host institutions

Organiser: Sydney Informatics Hub

Contact: sih.training@sydney.edu.au

Host institution: University of Sydney

AgReFed Data Harvester Workshop https://dresa.org.au/events/agrefed-data-harvester-workshop ### Sydney Informatics Hub presents: ## AgReFed Data-Harvester Workshop for R 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 basic knowledge of R and RStudio is highly recommended; familiarity with tidyverse libraries will be advantageous. An interactive online RStudio environment will be provided for all users for the workshop (with installation instructions provided for those wishing to run things locally). **Note:** The AgReFed Data-Harvester is accessible via both _R_ and _Python_. If you would like to attend a Python workshop instead of (or in addition to) the R stream, please let us know of your interest by entering your email here: [https://sydney.au1.qualtrics.com/jfe/form/SV\_9TUKiEjaNEFPifk](https://sydney.au1.qualtrics.com/jfe/form/SV_9TUKiEjaNEFPifk) ### ### For more information:  sih.training@sydney.edu.au  2022-10-25 09:30:00 UTC 2022-10-25 12:30:00 UTC Sydney Informatics Hub Sydney, Australia Sydney Australia University of Sydney sih.training@sydney.edu.au [] [] [] host_institution []