Open AccessDeveloping fire danger models using logistic regression analysis for mid-hills of Himachal Pradesh
Author(s) -
Divya Mehta,
Parminder Kaur Baweja,
R. K. Aggarwal
Publication year - 2021
Publication title -
journal of agrometeorology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 11
eISSN - 2583-2980
pISSN - 0972-1665
DOI - 10.54386/jam.v21i4.289
Subject(s) - wind speed , environmental science , relative humidity , logistic regression , coefficient of determination , mean squared error , maximum temperature , regression analysis , meteorology , statistics , atmospheric sciences , mathematics , geography , geology
The present study intended to develop a climatic fire danger model for mid-hills zone of Himachal Pradesh using ten years weather data in relation with forest fire occurrence (2007-2016). Logistic regression technique was used to determine the relationship between fire occurrence and weather parameters viz., maximum temperature (°C), relative humidity (%), and wind speed (ms-1). The model was validated by calculating area under curve (AUC), coefficient of determination (R2) and root mean square Error (RMSE), with estimated values of 88.90%, 0.705 and 0.247, respectively. The fire danger model was verified with actual fire incidences in the study area during the year 2017. Wald's test was carried out to quantify impact climatic parameters on forest fire. Wald's test value was highest for maximum temperature (40.07) followed by relative humidity (1.15) and wind speed (0.75), respectively. In future such model can be utilized for prevention of forest fire hazards in the study area.