News
Read a blog that summarizes resources derived from the Wildfires Challenge
Apr 21, 2021
https://dev.to/ibmdeveloper/a-summary-of-resources-for-wildfires-for-call-for-code-2h93
Hear a Comparison of Model Approaches
Apr 5, 2021
https://www.crowdcast.io/e/predicting-australian
Crowdcast-Wildfires-2021-04-05-f-Susan-Assembled-Slides.pdf
The Final Results Posted on the Leaderboard
Mar 2 , 2021
The Finale - and Next Steps
Hear from IBMers building models for the wildfires challenge
Feb 22, 2021 -
A Summary of Self Study Materials is Available
The Evaluation Script is Now Public
Register for Office Hours - Tuesdays 8am US Eastern
From Dec 15, 2020 - Jan 26, 2021 -
Summary
Nearly 3 billion animals were affected by Australia's worst wildfire season that burned from July 2019 through March 2020 estimates Chris Dickman, a professor of ecology at the University of Sydney. The human cost to Aboriginal and Torres Island Australians, who lost their homes and their sacred sites, is devastating.
Join data scientists to develop models focused on forecasting wildfires in Australia for the upcoming wildfire season and enter the chance to win 5K US Dollars. To get you started we're releasing historical data sets extracted from Weather Operations Center Geospatial Analytics component (PAIRS Geoscope) Our goal is to better understand the application of machine learning techniques in this domain.
Useful Links
You can watch prior Crowdcasts
Overview of Challenge
Wildfires are among the most common forms of natural disaster in some regions, including Siberia, California, and Australia. It is important to improve forecasting for wildfires for a number of reasons:
- To prepare and respond
- To understand the root causes
- To help to mitigate wildfires in the future
At the Digital Developer Conference Data & AI, you'll hear about the Call for Code Spot Challenge on Wildfires. The objective will be to forecast wildfires in Australia during the month of February 2021 in order to better understand the application of machine learning techniques in this domain. We are excited to share an extract from Weather Operations Center Geospatial Analytics component (PAIRS Geoscope) with some of the data going back to 2005, and sessions to help you get started. Do join us. You can see a list of the sessions that were presented at the end of this blog.
The Datasets
Predict the size of the fire area in km squared by region in Australia for each day in February 2021.
The regions are:
- NSW=New South Wales
- NT=Northern Territory
- QL=Queensland
- SA=Australia
- TA=Tasmania
- VI=Victoria
- WA=Western Australia
To forecast the wildfires, you will be given 5 datasets, extracted from Weather Operations Center Geospatial Analytics component (PAIRS Geoscope), which you can augment with other open datasets. You will also be given opportunities to try out your predictions before February in earlier stages of the contest.
Note that there is no hidden data in this contest. You will be predicting wildfires in February 2021 during January 2021. The leaderboard will check how closely your prediction matches with reality.
The datasets and accompanying readme and slides are available via GitHub https://github.com/Call-for-Code/Spot-Challenge-Wildfires together with a starter notebook.
- Landclasses Australia by region (static throughout the contest)
- Normalized Vegetation index Australia by region
- Weather
- Weather forecasts
- Wildfires
The datasets will be refreshed through the contest at particular times (see the timeline table below). Contestants can incorporate other open datasets into their model preparation.
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