bushfires: Australian bushfires 2019-2020

In mulgar: Functions for Pre-Processing Data for Multivariate Data Visualisation using Tours

Australian bushfires 2019-2020

Description

This data was collated by Weihao (Patrick) Li as part of his Honours research at Monash University. It contains fire ignitions as detected from satellite hotspots, and processed using the spotoroo package, augmented with measurements on weather, vegetation, proximity to human activity. The cause variable is predicted based on historical fire ignition data collected by County Fire Authority personnel.

Format

A dataset with 1021 rows and 60 columns

Details

id, lon, lat, time

unique id, and spatiotemporal information for each fire ignition

FOR_CODE, FOR_TYPE, COVER, HEIGHT, FOREST

vegetation variables

rf, arf7-arf720

average rainfall, on that day, and over last 7, ..., 720 days

se, ase7-ase720

solar exposure, on that day, and over last 7, ..., 720 days

maxt, amaxt7-amaxt720

max temperature, on that day, and over last 7, ..., 720 days

mint, amint7-amint720

min temperature, on that day, and over last 7, ..., 720 days

ws, aws_m0-aws_m24

average wind speed, on that day, and for last 1-24 months

dist_road, log_dist_road

distance to nearest road

dist_cfa, log_dist_cfa

distance to nearest county fire authority facility

dist_camp, log_dist_camp

distance to nearest camp site

cause

predicted ignition cause, accident, arson, burning_off, lightning

Examples

require(dplyr)
data(bushfires)
glimpse(bushfires)

mulgar documentation built on April 12, 2025, 1:23 a.m.