A LOGIT MODEL FOR PREDICTING THE DAILY OCCURRENCE OF HUMAN CAUSED FOREST-FIRES

被引:161
|
作者
VEGA GARCIA, C [1 ]
WOODARD, PM [1 ]
TITUS, SJ [1 ]
ADAMOWICZ, WL [1 ]
LEE, BS [1 ]
机构
[1] UNIV ALBERTA, DEPT FOREST SCI, EDMONTON, AB T6G 2H, CANADA
关键词
PREDICTION; LOGIT MODEL; ALBERTA; CANADA; FIRE OCCURRENCE; HUMAN-CAUSED;
D O I
10.1071/WF9950101
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
The logit model was used to predict the number of fire-days in the Whitecourt Forest of Alberta. The database used included fire (1) and no-fire (0) observations for fire season days between April and October for the 1986 through 1990 period. There were 8,009 observations during this period of which 157 were fire observations. Using four variables, we were able to predict 79.0% of the fire-days and 81.5% of the no-fire-days. The model, Z(i)=-8.5171+7.6590xAREA(i)+0.7367xDISTRICT(i)+2.0478xBUI(i)+3.9563xISI(i), failed to predict 37 of the fire-days and produced 29 ''false alarms''. When this model was tested on fire occurrence data from the Whitecourt Forest for 1991 and 1992 fire seasons it was correct 74.1% of the time. The management implications and limitations of this study are also discussed in this paper.
引用
收藏
页码:101 / 111
页数:11
相关论文
共 43 条
  • [31] An evaluation of spatial and temporal patterns of lightning- and human-caused forest fires in Alberta, Canada, 1980-2007
    Wang, Yonghe
    Anderson, Kerry R.
    INTERNATIONAL JOURNAL OF WILDLAND FIRE, 2010, 19 (08) : 1059 - 1072
  • [32] An insight into machine-learning algorithms to model human-caused wildfire occurrence
    Rodrigues, Marcos
    de la Riva, Juan
    ENVIRONMENTAL MODELLING & SOFTWARE, 2014, 57 : 192 - 201
  • [33] Mesoscale spatiotemporal predictive models of daily human- and lightning-caused wildland fire occurrence in British Columbia
    Nadeem, Khurram
    Taylor, S. W.
    Woolford, Douglas G.
    Dean, C. B.
    INTERNATIONAL JOURNAL OF WILDLAND FIRE, 2020, 29 (01) : 11 - 27
  • [34] Predicting the number of daily human-caused bushfires to assist suppression planning in south-west Western Australia
    Plucinski, M. P.
    McCaw, W. L.
    Gould, J. S.
    Wotton, B. M.
    INTERNATIONAL JOURNAL OF WILDLAND FIRE, 2014, 23 (04) : 520 - 531
  • [35] A nonlinear occupant-restraint system model for predicting human injuries caused by vertical impact
    Di Zhou
    Xianhui Wang
    Qichen Zheng
    Tiaoqi Fu
    Mengyang Wu
    Xiaowang Sun
    Nonlinear Dynamics, 2021, 105 : 3093 - 3115
  • [36] A nonlinear occupant-restraint system model for predicting human injuries caused by vertical impact
    Zhou, Di
    Wang, Xianhui
    Zheng, Qichen
    Fu, Tiaoqi
    Wu, Mengyang
    Sun, Xiaowang
    NONLINEAR DYNAMICS, 2021, 105 (04) : 3093 - 3115
  • [37] PredMS: a random forest model for predicting metabolic stability of drug candidates in human liver microsomes
    Ryu, Jae Yong
    Lee, Jeong Hyun
    Lee, Byung Ho
    Song, Jin Sook
    Ahn, Sunjoo
    Oh, Kwang-Seok
    BIOINFORMATICS, 2022, 38 (02) : 364 - 368
  • [38] Predicting daily heating energy consumption in residential buildings through integration of random forest model and meta-heuristic algorithms
    Xu, Weiyan
    Tu, Jielei
    Xu, Ning
    Liu, Zuming
    ENERGY, 2024, 301
  • [39] Driving Factors and Forecasting Model of Lightning-Caused Forest Fires in Daxing’ anling Mountains Based on Multi-Sources Data and Machine Learning Method
    Jiao Q.
    Han Z.
    Wang W.
    Liu D.
    Pan P.
    Li B.
    Zhang N.
    Wang P.
    Tao J.
    Fan M.
    Linye Kexue/Scientia Silvae Sinicae, 2023, 59 (06): : 74 - 87
  • [40] Comparing calibrated statistical and machine learning methods for wildland fire occurrence prediction: a case study of human-caused fires in Lac La Biche, Alberta, Canadac
    Phelps, Nathan
    Woolford, Douglas G.
    INTERNATIONAL JOURNAL OF WILDLAND FIRE, 2021, 30 (11) : 850 - 870