Climate Change Data Portal
DOI | 10.1007/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 |
ISSN | 0921030X |
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 |
推荐引用方式 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). |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。