Algerian Forest Fires Dataset

Algerian Forest Fires Dataset

Datasets

Algerian Forest Fires Dataset

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Algerian Forest Fires Dataset

Use Case

Algerian Forest Fires Dataset

Description

Download our enriched Algerian Forest Fires Dataset featuring 300 instances and 24 detailed attributes from Bejaia and Sidi Bel-Abbes regions.

Description:

This dataset encompasses detailed information on forest fires in Algeria, focusing on two prominent regions: Bejaia in the northeast and Sidi Bel-Abbes in the northwest. The data spans from June 2012 to September 2013, covering two consecutive fire seasons to provide a richer temporal perspective.

  • Total Instances: 300 (150 instances per region)
  • Time Period: June 2012 – September 2013
  • Regions Covered: Bejaia and Sidi Bel-Abbes
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Attributes

  1. Date: The specific date of the record.
  2. Region: The region where the data was collected (Bejaia or Sidi Bel-Abbes).
  3. Temperature (°C): Average daily temperature.
  4. Relative Humidity (%): Average daily relative humidity.
  5. Wind Speed (km/h): Average daily wind speed.
  6. Rainfall (mm): Total daily rainfall.
  7. Solar Radiation (MJ/m²): Amount of solar energy received per square meter.
  8. Soil Moisture (%): Percentage of moisture in the soil.
  9. Vegetation Density (%): Percentage representing the density of vegetation cover.
  10. Fire Weather Index (FWI): An index calculating fire risk based on weather conditions.
  11. Drought Code (DC): Indicates the potential for deep, smoldering combustion.
  12. Fine Fuel Moisture Code (FFMC): Reflects the moisture content of litter and fine fuels.
  13. Human Activity Level: Categorical variable indicating human presence (Low, Medium, High).
  14. Fire Occurrence: Binary variable indicating whether a fire occurred (Yes=1, No=0).

Dataset Description

This enriched dataset is designed to facilitate advanced analysis of forest fire occurrences in Algeria. By incorporating both meteorological data and geographical attributes, the dataset allows for multifaceted studies into the causes and patterns of forest fires.

Key Enhancements:

  • Temporal Expansion: Data now includes two fire seasons for trend analysis.
  • Spatial Details: Added geographical features like elevation, slope, and aspect.
  • Human Factors: Included distance to roadways and human activity levels to assess human impact.
  • Environmental Indicators: Introduced variables like soil moisture, vegetation density, and fuel type.

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