- Data Source: [Cortez and Morais, 2007] P. Cortez and A. Morais. A Data Mining Approach to Predict Forest Fires using Meteorological Data. In J. Neves, M. F. Santos and J. Machado Eds., New Trends in Artificial Intelligence, Proceedings of the 13th EPIA 2007 - Portuguese Conference on Artificial Intelligence, December, Guimarães, Portugal, pp. 512-523, 2007. APPIA, ISBN-13 978-989-95618-0-9.
- Data source webpage link: http://archive.ics.uci.edu/ml/datasets/Forest+Fires
- Github repository: https://github.com/janehyc/BST260_group_project.git
- R shiny app is in visualization folder
- website link: https://sites.google.com/view/bst260forestfire/home
- youtube link: https://youtu.be/CUsBywB29hQ
- Spatial information
- X - x-axis spatial coordinate within the Montesinho park map: 1 to 9
- Y - y-axis spatial coordinate within the Montesinho park map: 2 to 9
- Temporal information
- month - month of the year: 'jan' to 'dec'
- day - day of the week: 'mon' to 'sun'
- FWI: The forest Fire Weather Index (FWI). Which is the Canadian system for rating fire danger.
- FFMC - FFMC index from the FWI system: 18.7 to 96.20
- DMC - DMC index from the FWI system: 1.1 to 291.3
- DC - DC index from the FWI system: 7.9 to 860.6
- ISI - ISI index from the FWI system: 0.0 to 56.10
- Methorological information
- temp - temperature in Celsius degrees: 2.2 to 33.30
- RH - relative humidity in %: 15.0 to 100
- wind - wind speed in km/h: 0.40 to 9.40
- rain - outside rain in mm/m2 : 0.0 to 6.4
- area - the burned area of the forest (in ha): 0.00 to 1090.84