Algerian forest fires dataset
- Citation Author(s):
-
Faroudja ABID
- Submitted by:
- Faroudja ABID
- Last updated:
- DOI:
- 10.21227/31na-kz23
- Data Format:
- Research Article Link:
- Links:
1147 views
- Categories:
- Keywords:
Abstract
The first Algerian forest fires dataset consist of data on forest fires occurrence in Algeria related to meteorological observations and the fire weather indices. Our dataset includes mainly the daily meteorological observations and the Fire Weather Index (FWI) system components. Given the lack of publically available datasets on data on forest fires occurrence in Algeria we have created this one to study the feasibility of the appliance of machine learning algorithms as models for forest fires prediction in the context of Algeria. This dataset is valuable for researchers working on forest fires forecasting and monitoring systems in Algeria and also over the word, in particular the Mediterranean countries that have similar climate. This dataset is publically available in several repositories for research. It was elaborated in 2018 and first donated to the UCI online repository on October 2019.
Instructions:
Subject: Environmental Science, Ecology
Specific subject area : This dataset involves the area of forest fires data related to meteorological observations and the fire danger rating system indices.
Brief description : This data article presents the first Algerian forest fires dataset that consists of 244 instances, which includes 12 variables (attributes), namely the meteorological observations (four weather parameters), the six components of the FWI Canadian system , the fire classes (“fire” and “not fire”) and the date variable ((DD/MM/YYYY): Day/month ('June' to 'September')/ year (2012)).
Table : Algerian forest fires dataset features description
Data Type | Attributes/variablesname | Description | Values interval Sidi-Bel-Abbes region | Values interval Bejaia region | Values intervals The two regions | |
Meteorological observations | Temperature | temperature in Celsius degrees | 24 to 42 | 22 to 37 | 22 to 42 | |
RH | relative humidity in % | 21 to 90 | 45 to 89 | 21 to 90 | ||
WS | wind speed in km/h | 6 to 29 | 11 to 26 | 6 to 29 | ||
Rain | outside rain in mm/m2 | 0 to 16.8 | 0 to 8.7 | 0 to 16.8 | ||
FWI components | FFMC | Fine Fuel Moisture Code | 41.1 to 94.3 | 28.6 to 90.3 | 28.6 to 94.3 | |
DMC | Duff Moisture Code | 0.9 to 65.9 | 0.7 to 54.2 | 1.1 to 65.9 | ||
DC | Drought Code | 7.3 to 177.3 | 7.4 to 220.4 | 7 to 220.4 | ||
ISI | Initial Spread Index | 0.1 to 18.5 | 0.1 to 19 | 0.1 to 19 | ||
BUI | Buildup Index | 1.4 to 68 | 3.3 to 67.4 | 1.1 to 68 | ||
FWI | Fire Weather Index | 0 to 31.1 | 0 to 30.2 | 0 to 31.1 | ||
This dataset was first donated to the UC Irvine Machine Learning Repository : https://archive.ics.uci.edu/dataset/547/algerian+forest+fires+dataset
