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• W2985305445 abstract "In this study, we used the Maxent predictive model to investigate the risk of veldt fire occurrence based on historical fire data, climatic and non-climatic drivers in the Golden Gate highland National Park (GGHNP), South Africa during the 2011–2014 periods. Results indicate that the highest fire risk occurred in the eastern and southwestern regions of the park, in particular the grass dominated region at middle altitude and along the northeast facing slopes with moderate precipitation. Rainfall contributed most to the model performance, followed by elevation, and temperature respectively. The predicted model performed well in terms of accuracy and average AUC and correlation values of 0.926 and 0.74 respectively for the validation sample. The higher contribution of climatic and topographic factors to fire occurrence suggested that wind driven fires has more effect than convective fuel related fires in the park. The results of this study can contribute to improved quantitative assessment and management of early warning and forecasting for fire risk management in the park." @default.
• W2985305445 created "2019-11-22" @default.
• W2985305445 creator A5084164098 @default.
• W2985305445 creator A5085321347 @default.
• W2985305445 date "2019-07-01" @default.
• W2985305445 modified "2023-09-26" @default.
• W2985305445 title "Assessment of Fuel and Wind Drivers of Fire Risk in Protected Mountainous Grassland of South Africa" @default.
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• W2985305445 doi "https://doi.org/10.1109/igarss.2019.8900100" @default.
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