A forest fire warning model: using time decay model to calculate comprehensive precipitation index

Jiajun Chen; Xiaoqing Wang; Haifeng Huang

doi:10.1117/12.2625573

9 December 2021 A forest fire warning model: using time decay model to calculate comprehensive precipitation index

Jiajun Chen, Xiaoqing Wang, Haifeng Huang

Proceedings Volume 12129, International Conference on Environmental Remote Sensing and Big Data (ERSBD 2021); 121290E (2021) https://doi.org/10.1117/12.2625573
Event: 2021 International Conference on Environmental Remote Sensing and Big Data, 2021, Wuhan, China

Abstract

Precipitation is an important factor that predicts the occurrence of forest fires in the future. This study uses a time decay model to calculate the comprehensive precipitation index, which is an exponential weight decay model. This method can better represent the effect of precipitation in predicting the occurrence of forest fires. Besides, this study used the Support Vector Machine (SVM) regression model to construct a forest fire warning model. In the same area, using the comprehensive precipitation index compared with the average precipitation, the accuracy of the three forest areas in the test set has been improved by approximately 5%.

Citation Download Citation

Jiajun Chen, Xiaoqing Wang, and Haifeng Huang "A forest fire warning model: using time decay model to calculate comprehensive precipitation index", Proc. SPIE 12129, International Conference on Environmental Remote Sensing and Big Data (ERSBD 2021), 121290E (9 December 2021); https://doi.org/10.1117/12.2625573

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