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DOI10.1007/s11069-020-04395-w
A novel approach for predicting burned forest area
Oncel Cekim H.; Güney C.O.; Şentürk Ö.; Özel G.; Özkan K.
发表日期2021
ISSN0921030X
起始页码2187
结束页码2201
卷号105期号:2
英文摘要Forest fire hazard is a major problem in the Mediterranean region of Turkey and has a significant effect on both the climate system and ecosystems. During the last century, many forest fires accounted for the majority of the Mediterranean region in Turkey. Vector singular spectrum analysis (V-SSA) and vector multivariate singular spectrum analysis (V-MSSA) are relatively novel but powerful time series analysis techniques. The present study addresses how to forecast burned forest area (BFA) by V-SSA. One of the most important factors affecting forest fires is weather conditions. The prediction of BFA is therefore also obtained by V-MSSA using meteorological covariates (i.e., relative humidity (RH), temperature (T) and wind speed (WS). In the study, forest fire data records covering the years 2005–2019 were collected and analyzed. To gain forecast accuracy, the years 2017–2019 were used as testing data, and forecast values for 1, 3, 6, 12, 24 and 36 months were obtained. Then, V-SSA and V-MSSA models were compared via the root mean square errors (RMSEs) to reach the best model explaining BFA. Our results indicated that the RMSEs of the eight models were low and close to each other. Further, forecasts for the months of the years 2020–2022 were obtained and compared with actual BFA values by means of the RMSEs. According to RMSEs, the best forecasts are obtained using the V-MSSA model with meteorological covariates BFA, WS and T. © 2020, Springer Nature B.V.
关键词Forest fireMediterraneanSingular spectrum analysisVector SSA
英文关键词forest dynamics; forest fire; hazard assessment; natural hazard; spectral analysis; vector autoregression; Turkey; Meleagris gallopavo
语种英语
来源期刊Natural Hazards
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/206473
作者单位Department of Statistics, Hacettepe University, Ankara, Turkey; Department of Forest Fire, Southwest Anatolia Forest Research Institute, Antalya, Turkey; Department of Forestry, Mehmet Akif Ersoy University, Burdur, Turkey; Department of Soil Science and Ecology, Isparta University of Applied Science, Isparta, Turkey
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GB/T 7714
Oncel Cekim H.,Güney C.O.,Şentürk Ö.,et al. A novel approach for predicting burned forest area[J],2021,105(2).
APA Oncel Cekim H.,Güney C.O.,Şentürk Ö.,Özel G.,&Özkan K..(2021).A novel approach for predicting burned forest area.Natural Hazards,105(2).
MLA Oncel Cekim H.,et al."A novel approach for predicting burned forest area".Natural Hazards 105.2(2021).
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