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.
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)
#> Rows: 1,021
#> Columns: 60
#> $ id <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1…
#> $ lon <dbl> 141.1300, 141.3000, 141.4800, 147.1600, 148.1050, 144.18…
#> $ lat <dbl> -37.13000, -37.65000, -37.35000, -37.85000, -37.57999, -…
#> $ time <date> 2019-10-01, 2019-10-01, 2019-10-02, 2019-10-02, 2019-10…
#> $ FOR_CODE <dbl> 41, 41, 91, 44, 0, 44, 0, 102, 0, 91, 45, 41, 45, 45, 45…
#> $ FOR_TYPE <chr> "Eucalypt Medium Woodland", "Eucalypt Medium Woodland", …
#> $ FOR_CAT <chr> "Native forest", "Native forest", "Commercial plantation…
#> $ COVER <dbl> 1, 1, 4, 2, 6, 2, 6, 5, 6, 4, 2, 1, 2, 2, 2, 2, 6, 6, 6,…
#> $ HEIGHT <dbl> 2, 2, 4, 2, 6, 2, 6, 5, 6, 4, 3, 2, 3, 3, 3, 2, 6, 6, 6,…
#> $ FOREST <dbl> 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0,…
#> $ rf <dbl> 0.0, 0.0, 15.4, 4.8, 6.0, 11.6, 11.6, 0.6, 0.2, 0.6, 0.0…
#> $ arf7 <dbl> 5.0857143, 2.4000000, 2.4000000, 0.7142857, 0.8571429, 1…
#> $ arf14 <dbl> 2.8142857, 1.7428571, 1.8000000, 1.6714286, 1.5714286, 1…
#> $ arf28 <dbl> 1.9785714, 1.5357143, 1.5357143, 3.7857143, 1.9000000, 1…
#> $ arf60 <dbl> 2.3033333, 1.7966667, 1.7966667, 4.0000000, 2.5333333, 1…
#> $ arf90 <dbl> 1.2566667, 1.0150000, 1.0150000, 2.9600000, 2.1783333, 1…
#> $ arf180 <dbl> 0.9355556, 0.8444444, 0.8444444, 2.3588889, 1.7866667, 1…
#> $ arf360 <dbl> 1.3644444, 1.5255556, 1.5255556, 1.7272222, 1.4716667, 1…
#> $ arf720 <dbl> 1.3011111, 1.5213889, 1.5213889, 1.7111111, 1.5394444, 1…
#> $ se <dbl> 3.8, 4.6, 14.2, 23.7, 23.8, 16.8, 18.0, 12.9, 14.7, 12.9…
#> $ ase7 <dbl> 18.02857, 18.50000, 21.41429, 23.08571, 23.11429, 22.014…
#> $ ase14 <dbl> 17.03571, 17.44286, 18.03571, 19.17143, 18.45714, 18.628…
#> $ ase28 <dbl> 19.32857, 18.47500, 19.33929, 18.23571, 16.86071, 19.375…
#> $ ase60 <dbl> 20.38644, 19.99153, 20.39492, 19.90847, 19.26780, 20.449…
#> $ ase90 <dbl> 22.54118, 21.93193, 22.04370, 20.59328, 20.04538, 21.809…
#> $ ase180 <dbl> 20.79106, 19.93966, 19.99385, 19.11006, 18.66760, 19.810…
#> $ ase360 <dbl> 15.55153, 14.83259, 14.87883, 14.69276, 14.44318, 14.755…
#> $ ase720 <dbl> 15.52350, 14.75049, 14.77427, 14.53463, 14.32656, 14.540…
#> $ maxt <dbl> 21.3, 17.8, 15.4, 20.8, 19.8, 15.8, 19.5, 12.6, 18.8, 12…
#> $ amaxt7 <dbl> 22.38571, 20.44286, 22.21429, 24.21429, 23.14286, 21.671…
#> $ amaxt14 <dbl> 21.42857, 19.72857, 19.86429, 21.80000, 20.89286, 19.578…
#> $ amaxt28 <dbl> 20.71071, 19.10000, 19.18929, 19.75000, 19.05714, 18.885…
#> $ amaxt60 <dbl> 24.02667, 22.28000, 22.38667, 22.93167, 22.12000, 21.031…
#> $ amaxt90 <dbl> 27.07750, 25.77667, 25.89833, 24.93667, 23.93750, 23.164…
#> $ amaxt180 <dbl> 26.92000, 25.92722, 25.98500, 24.84056, 23.95389, 23.343…
#> $ amaxt360 <dbl> 21.55389, 20.79778, 20.81333, 20.21972, 19.99389, 19.505…
#> $ amaxt720 <dbl> 21.47750, 20.57222, 20.57694, 20.13153, 20.03875, 19.650…
#> $ mint <dbl> 9.6, 9.0, 7.3, 7.7, 8.3, 8.3, 6.1, 5.9, 7.4, 5.9, 6.9, 7…
#> $ amint7 <dbl> 9.042857, 7.971429, 9.171429, 10.328571, 11.200000, 10.6…
#> $ amint14 <dbl> 9.928571, 9.235714, 9.421429, 10.007143, 10.900000, 10.7…
#> $ amint28 <dbl> 8.417857, 7.560714, 7.353571, 8.671429, 9.575000, 10.060…
#> $ amint60 <dbl> 11.156667, 9.903333, 9.971667, 10.971667, 11.975000, 12.…
#> $ amint90 <dbl> 11.96667, 10.81250, 10.87833, 12.49000, 13.46167, 13.638…
#> $ amint180 <dbl> 11.96778, 11.01056, 11.02000, 12.41944, 13.42500, 13.695…
#> $ amint360 <dbl> 9.130556, 8.459722, 8.448333, 9.588611, 10.456389, 11.03…
#> $ amint720 <dbl> 8.854861, 8.266250, 8.254028, 9.674861, 10.517083, 10.96…
#> $ dist_cfa <dbl> 9442.206, 6322.438, 7957.374, 7790.785, 10692.055, 6054.…
#> $ dist_camp <dbl> 50966.485, 6592.893, 31767.235, 8816.272, 15339.702, 941…
#> $ ws <dbl> 1.263783, 1.263783, 1.456564, 5.424445, 4.219751, 4.1769…
#> $ aws_m0 <dbl> 2.644795, 2.644795, 2.644795, 5.008369, 3.947659, 5.2316…
#> $ aws_m1 <dbl> 2.559202, 2.559202, 2.559202, 5.229680, 4.027398, 4.9704…
#> $ aws_m3 <dbl> 2.446211, 2.446211, 2.446211, 5.386005, 3.708622, 5.3045…
#> $ aws_m6 <dbl> 2.144843, 2.144843, 2.144843, 5.132617, 3.389890, 5.0355…
#> $ aws_m12 <dbl> 2.545008, 2.545008, 2.548953, 5.045297, 3.698736, 5.2341…
#> $ aws_m24 <dbl> 2.580671, 2.580671, 2.584047, 5.081100, 3.745286, 5.2522…
#> $ dist_road <dbl> 498.75145, 102.22032, 1217.22446, 281.69151, 215.56176, …
#> $ log_dist_cfa <dbl> 9.152945, 8.751860, 8.981854, 8.960697, 9.277256, 8.7084…
#> $ log_dist_camp <dbl> 10.838924, 8.793748, 10.366191, 9.084354, 9.638200, 9.15…
#> $ log_dist_road <dbl> 6.212108, 4.627130, 7.104329, 5.640813, 5.373247, 5.0047…
#> $ cause <chr> "lightning", "lightning", "lightning", "lightning", "lig…