Araştırma Makalesi

PREDICTION OF TÜRKİYE'S BURNED FOREST AREAS USING ARIMA MODEL

Cilt: 33 Sayı: 1 19 Ocak 2023
PDF İndir
EN TR

PREDICTION OF TÜRKİYE'S BURNED FOREST AREAS USING ARIMA MODEL

Öz

Abstract: Large-scale forest fires can cause significant ecological losses. Additionally, preserving forest areas may help to slow down climate change. Statistical models are one of the tools used in planning fire management strategies. In this study, the burned forest area of Türkiye is modeled using the Autoregressive Integrated Moving Average (ARIMA) method following the identification, estimation, validation, and forecasting steps. As is known the ARIMA analysis is one of the popular techniques used in time series analysis. Annual total burned forest areas in Türkiye over the period 1940-2021 are considered in the analysis. Three preliminary models are considered for evaluation of their modeling and prediction performances. The models' validities are investigated with Ljung–Box statistics, residual analysis, and cross-validation. According to the results, the ARIMA (3,1,0) model is found to be the most suitable model for predicting the future values of the burned forest area time series in Türkiye. Forecasts for Türkiye’s burned forest areas series are obtained for the next 3 years accordingly.

Anahtar Kelimeler

Kaynakça

  1. Amatulli, G., Camia, A., & San-Miguel-Ayanz, J. (2013). Estimating future burned areas under changing climate in the EU-Mediterranean countries. Science of The Total Environment, 450–451, 209–222. Elsevier.
  2. Baş, R. (2014). Türkiye’de orman yangınları nedenleri, zararları ve yangınlara karşı alınacak önlemler. Journal of the Faculty of Forestry Istanbul University, 27(2), 52–73.
  3. Boubeta, M., Lombardía, M. J., González-Manteiga, W., & Marey-Pérez, M. F. (2016). Burned area prediction with semiparametric models. International Journal of Wildland Fire, 25(6), 669–678. CSIRO Publishing.
  4. Boubeta, M., Lombardía, M. J., Marey-Pérez, M. F., & Morales, D. (2015). Prediction of forest fires occurrences with area-level Poisson mixed models. Journal of Environmental Management, 154, 151–158. Academic Press.
  5. Çekim, H. Ö., Kadilar, C., & Özel, G. (2013). Characterizing forest fire activity in Turkey by compound Poisson and time series models. AIP Conference Proceedings, 1558(1), 1442. American Institute of PhysicsAIP. Retrieved January 30, 2022, from https://aip.scitation.org/doi/abs/10.1063/1.4825789
  6. Chen, W., Moriya, K., Sakai, T., Koyama, L., & Cao, C. X. (2016). Mapping a burned forest area from Landsat TM data by multiple methods. Geomatics, Natural Hazards and Risk, 7(1), 384–402. Taylor & Francis. Retrieved from https://doi.org/10.1080/19475705.2014.925982
  7. Çolak, E., & Sunar, F. (2020). Evaluation of forest fire risk in the Mediterranean Turkish forests: A case study of Menderes region, Izmir. International Journal of Disaster Risk Reduction, 45, 101479. Elsevier.
  8. EAA. (n.d.). EAA. 2021. Date of access: 03.05.2022. https://www.eea.europa.eu/ims/forest-fires-in-europe

Ayrıntılar

Birincil Dil

İngilizce

Konular

-

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

19 Ocak 2023

Gönderilme Tarihi

18 Eylül 2022

Kabul Tarihi

10 Kasım 2022

Yayımlandığı Sayı

Yıl 2023 Cilt: 33 Sayı: 1

Kaynak Göster

APA
Bağcı, K. (2023). PREDICTION OF TÜRKİYE’S BURNED FOREST AREAS USING ARIMA MODEL. Firat University Journal of Social Sciences, 33(1), 347-355. https://doi.org/10.18069/firatsbed.1176961
AMA
1.Bağcı K. PREDICTION OF TÜRKİYE’S BURNED FOREST AREAS USING ARIMA MODEL. Firat University Journal of Social Sciences. 2023;33(1):347-355. doi:10.18069/firatsbed.1176961
Chicago
Bağcı, Kübra. 2023. “PREDICTION OF TÜRKİYE’S BURNED FOREST AREAS USING ARIMA MODEL”. Firat University Journal of Social Sciences 33 (1): 347-55. https://doi.org/10.18069/firatsbed.1176961.
EndNote
Bağcı K (01 Ocak 2023) PREDICTION OF TÜRKİYE’S BURNED FOREST AREAS USING ARIMA MODEL. Firat University Journal of Social Sciences 33 1 347–355.
IEEE
[1]K. Bağcı, “PREDICTION OF TÜRKİYE’S BURNED FOREST AREAS USING ARIMA MODEL”, Firat University Journal of Social Sciences, c. 33, sy 1, ss. 347–355, Oca. 2023, doi: 10.18069/firatsbed.1176961.
ISNAD
Bağcı, Kübra. “PREDICTION OF TÜRKİYE’S BURNED FOREST AREAS USING ARIMA MODEL”. Firat University Journal of Social Sciences 33/1 (01 Ocak 2023): 347-355. https://doi.org/10.18069/firatsbed.1176961.
JAMA
1.Bağcı K. PREDICTION OF TÜRKİYE’S BURNED FOREST AREAS USING ARIMA MODEL. Firat University Journal of Social Sciences. 2023;33:347–355.
MLA
Bağcı, Kübra. “PREDICTION OF TÜRKİYE’S BURNED FOREST AREAS USING ARIMA MODEL”. Firat University Journal of Social Sciences, c. 33, sy 1, Ocak 2023, ss. 347-55, doi:10.18069/firatsbed.1176961.
Vancouver
1.Kübra Bağcı. PREDICTION OF TÜRKİYE’S BURNED FOREST AREAS USING ARIMA MODEL. Firat University Journal of Social Sciences. 01 Ocak 2023;33(1):347-55. doi:10.18069/firatsbed.1176961