The Challenge
Background:
In recent years, wildfire frequency, intensity, and extent, as well as economic and human health impacts, have significantly increased worldwide. Thousands of acres of land have burned, and homes, buildings, and other important community infrastructure have been destroyed by wildfires. The overall economic impacts have cost communities billions of dollars in direct damage and loss of economic productivity.
To mitigate future losses and the overall impacts on communities, early and effective fire detection, fire prediction, risk analysis, and economic impact analysis that can provide actionable information is highly desirable. New opportunities exist for researchers and citizen scientists to convey easily consumable critical information to communities through the use of a new generation of geostationary satellites, existing polar orbiters, and many government and private sector open data initiatives. As an example, new beta geostationary satellite-based fire detection data products from NOAA are now produced and made widely available in ten minutes or less (See GOES in resources).
In the 2018 and 2019 NASA Space Apps Challenges, the challenges called Spot That Fire versions 1.0 and 2.0 received many stimulating ideas and applications that addressed the presentation of fire detection to a general user audience. For Spot That Fire 1.0 and 2.0, geostationary data were not readily available to the public. Now they are! For Spot That Fire Version 3.0, your challenge is to propose, prototype, and present innovative ideas that use novel machine learning, data science, and data fusion for the prediction, detection and impact analysis of wildfires.
Any processes and presentation methods that fulfill the overall challenge aim should have the potential to be rapidly deployed and executed, with the results presented to the target community in near realtime. Participants are encouraged to utilize technologies and methods including, but not limited to, open source web-based visualization and notebook packages for the execution of wildfire prediction and detection methods and processes. Participants are also encouraged to fuse appropriate open-data sources, such as county, state, or national Geographic Information Systems (GIS) parcels or boundaries, economic databases, or datasets that may aid in any impact analysis and assessments.
Potential Considerations:
- Prediction, detection, and/or impact assessments should be presented in a clear, intuitive, and easy-to-consume way, providing actionable information to communities, decision-makers, and/or firefighting groups. Who is your target audience
- Teams are invited (but not required to) develop or augment applications, processes, or methodologies that focus on one or more of the following suggested topics:
- Build prototype mashups that visualize fire tracks, track predictions, or economic impacts: e.g., show fire locations, tracks and trajectories on maps, embed animations, display detailed fire data, and/or present potential impacts on infrastructure, neighborhoods, and communities, such as economic losses, costs, and overall impacts. Prototype and/or improve real-time fire detection, prediction, status monitoring, and impact analysis using novel techniques, methodologies and algorithms: i.e., using novel machine learning and data science with common open source software packages and/or web-based visualization packages.
- Develop machine-learning training datasets for fire prediction and fire impact assessments, and provide a readily accessible and scalable application programming interface (“API”), with concise documentation, to the training dataset(s) so that other researchers within the data science or machine-learning communities can easily incorporate your training data into their own processes.
- Build a prototype to identify major concerns: i.e., apply analytics to identify core areas or concerns with a fire and provide a mechanism to notify relevant stakeholders, e.g. using push notification, etc.
- In order to make your efforts sustainable after the Space Apps[?] event and allow the community to continue with your innovative ideas, your solution should:
- Provide a brief description of the solution goal and design – what does it do and how?
- Provide a description (a story) of why this solution is important and what insights or future capabilities it may provide with regard to fighting wildfires or assessing their impacts.
- Leverage or deploy existing or novel technologies as noted in the challenge background.
- Be an open-source project (like all Space Apps solutions).
- Provide descriptions and links to other open-source tools used in the development (if you are building on previous Space Apps work, make sure you credit the projects).
- Create a code repository for your project so that other people can review and/or leverage your efforts.
For data and resources related to this challenge, refer to the Resources tab at the top of the page.
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