To date, the efficiency and effectiveness of early warning systems of satellite imagery for preventing and mitigating wildfire remain a challenging issue. The heat of pre-ignition (\(Q_{{{\text{ig}}}}\)) can be an index of fire likelihood, which is further enhanced with remotely sensed data, active fire data, and fuels information for operational application of satellite imagery in fire early warning systems. \(Q_{{{\text{ig}}}}\) is a prerequisite for forest fires by the side of ignition sources and weather. This study analyzed the effect of \(Q_{{{\text{ig}}}}\) variation on fire occurrences to develop a remote sensing-based initial fire likelihood index for identifying areas that have a high probability of fire. In this study, \(Q_{{{\text{ig}}}}\) of Rothermel’s fire spread model daily data is retrieved at 1 km pixels from MODIS data. MODIS active fire products were used to interpret the \(Q_{{{\text{ig}}}}\) of fuels for 10 days before the days of fire occurrences in November 2010 to determine the pre-fire conditions. A formula for converting \(Q_{{{\text{ig}}}}\) into an initial fire likelihood index (IFLI) was then used by binary logistic regression method. Analyses show that there was a positive association between suggested IFLI and fire occurrences during the study period with a fair diagnostic accuracy of 92%, and 80% for dead and live fuels, respectively. Mann–kendall test suggested that there are significant trends in the fuel moisture content time-series for both live and dead fuels. Further analysis using the Hosmer–Lemeshow test represents that the models showed an acceptable fit. The suggested IFLI is an effective tool for fire management decision-making whenever a near real-time fire likelihood is required.

迄今为止，用于预防和减轻野火的卫星图像预警系统的效率和有效性仍然是一个具有挑战性的问题。预点火的热量（\（Q _ {{{\ text {ig}}}} \））可以作为火灾可能性的指标，并通过遥感数据，有效火灾数据以及为运行提供燃料信息进一步增强了火灾可能性卫星图像在火灾预警系统中的应用。\（Q _ {{{{\ text {ig}}}} \\）是点火源和天气影响的森林大火的先决条件。这项研究分析了\（Q _ {{{\ text {ig}}}} \）变化对火灾的影响，从而开发了基于遥感的初始火灾可能性指数，用于识别火灾可能性高的区域。在这项研究中，Rothermel的火灾传播模型每日数据的\（Q _ {{{\ text {ig}}}} \\）距MODIS数据1公里像素处得到。在2010年11月发生火灾之前的10天内，使用MODIS主动式灭火产品来解释\（Q _ {{{{text {ig}}}} \）燃料，以确定着火前的状况。用于转换\（Q _ {{{\ text {ig}}}} \）的公式然后通过二元logistic回归方法使用初始火灾似然指数（IFLI）。分析表明，在研究期间，建议的IFLI与火灾之间存在正相关关系，对死燃料和活燃料的合理诊断准确度分别为92％和80％。Mann–kendall测试表明，无论是活燃料还是废燃料，燃油含水量时间序列都存在明显的趋势。使用Hosmer–Lemeshow检验的进一步分析表明，这些模型显示出可接受的拟合度。无论何时需要近乎实时的火灾可能性，建议的IFLI都是进行消防管理决策的有效工具。