Araştırma Makalesi

Evaluating spectral indices for estimating burned areas in the case of Izmir / Turkey

Cilt: 8 Sayı: 1 6 Mart 2020
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Evaluating spectral indices for estimating burned areas in the case of Izmir / Turkey

Öz

Mapping and determination of fire damaged areas in an accurate and prompt way is essential for identifying environmental losses caused by fires, post-fire management activities and planning strategies. In this context, this study aims to evaluate the performance spectral indices for discriminating burned and unburned areas in the immediate post-fire environment in the case of Gaziemir, Buca and Karabağlar districts of Izmir metropolitan city where one of the forest fires occurred in the 18rd August 2019. For this, whilst a Sentinel 2A (26th August 2019) was used to map burned / unburned areas as the reference dataset, two Landsat 8 satellite images (7th and 28th August 2019) were used for the calculation of spectral indices. The spectral indices of normalised difference vegetation index (NDVI), atmospherically resistant vegetation index (ARVI), two versions of normalised burn ratio (NBR and NBR2) and burnt area index (BAI) were calculated for the selected two dates as well as pre-fire and post-fire temporal differences in those indices. For the performance comparison of spectral indices, binary maps of burned and unburned areas were created and separability index (SI) was calculated for pre/post-fire differenced spectral indices. Our results suggest that NBR2, NDVI and ARVI had the highest potential for discriminating burned areas, respectively. Even though the value of separability indices was different from each other where NBR and BAI had the lowest values, that doesn’t necessarily mean these indices cannot discriminate burned areas, since the separation of burned and unburned areas highly depend on spatio-temporal circumstances like vegetation types and time lags between image acquisition dates.

Anahtar Kelimeler

Kaynakça

  1. Boschetti, M., Stroppiana, D., Brivio, P. A. (2010). Mapping burned areas in a Mediterranean environment using soft integration of spectral indices from high-resolution satellite images. Earth Interactions, 14(17), 1-20.
  2. Chander, G., Markham, B. (2003). Revised Landsat-5 TM radiometric calibration procedures and postcalibration dynamic ranges. IEEE Transactions on geoscience and remote sensing, 41(11), 2674-2677.
  3. Chen, W., Cao, C., He, Q., Guo, H., Zhang, H., Li, R., Zheng, S., Xu, M., Gao, M., Zhao, J. and Li, S. (2010). Quantitative estimation of the shrub canopy LAI from atmosphere-corrected HJ-1 CCD data in Mu Us Sandland. Science China Earth Sciences, 53(1), 26-33.
  4. Chen, X., Vogelmann, J.E., Rollins, M., Ohlen, D., Key, C.H., Yang, L., Huang, C. and Shi, H. (2011). Detecting post-fire burn severity and vegetation recovery using multitemporal remote sensing spectral indices and field-collected composite burn index data in a ponderosa pine forest. International Journal of Remote Sensing, 32(23), 7905-7927.
  5. Chuvieco, E., Congalton, R. G. (1988). Mapping and inventory of forest fires from digital processing of TM data. Geocarto International, 3(4), 41-53.
  6. Chuvieco, E., Martin, M. P., Palacios, A. (2002). Assessment of different spectral indices in the red-near-infrared spectral domain for burned land discrimination. International Journal of Remote Sensing, 23(23), 5103-5110.
  7. Chuvieco, E., Riaño, D., Danson, F. M., Martin, P. (2006). Use of a radiative transfer model to simulate the postfire spectral response to burn severity. Journal of Geophysical Research: Biogeosciences, 111(G4).
  8. Curtis, P. S., Gough, C. M. (2018). Forest aging, disturbance and the carbon cycle. New Phytologist, 219(4), 1188-1193.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Orman Endüstri Mühendisliği

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

6 Mart 2020

Gönderilme Tarihi

9 Aralık 2019

Kabul Tarihi

9 Ocak 2020

Yayımlandığı Sayı

Yıl 2020 Cilt: 8 Sayı: 1

Kaynak Göster

APA
Kesgin Atak, B., & Ersoy Tonyaloğlu, E. (2020). Evaluating spectral indices for estimating burned areas in the case of Izmir / Turkey. Eurasian Journal of Forest Science, 8(1), 49-59. https://doi.org/10.31195/ejejfs.657253
AMA
1.Kesgin Atak B, Ersoy Tonyaloğlu E. Evaluating spectral indices for estimating burned areas in the case of Izmir / Turkey. Eurasian Journal of Forest Science. 2020;8(1):49-59. doi:10.31195/ejejfs.657253
Chicago
Kesgin Atak, Birsen, ve Ebru Ersoy Tonyaloğlu. 2020. “Evaluating spectral indices for estimating burned areas in the case of Izmir / Turkey”. Eurasian Journal of Forest Science 8 (1): 49-59. https://doi.org/10.31195/ejejfs.657253.
EndNote
Kesgin Atak B, Ersoy Tonyaloğlu E (01 Mart 2020) Evaluating spectral indices for estimating burned areas in the case of Izmir / Turkey. Eurasian Journal of Forest Science 8 1 49–59.
IEEE
[1]B. Kesgin Atak ve E. Ersoy Tonyaloğlu, “Evaluating spectral indices for estimating burned areas in the case of Izmir / Turkey”, Eurasian Journal of Forest Science, c. 8, sy 1, ss. 49–59, Mar. 2020, doi: 10.31195/ejejfs.657253.
ISNAD
Kesgin Atak, Birsen - Ersoy Tonyaloğlu, Ebru. “Evaluating spectral indices for estimating burned areas in the case of Izmir / Turkey”. Eurasian Journal of Forest Science 8/1 (01 Mart 2020): 49-59. https://doi.org/10.31195/ejejfs.657253.
JAMA
1.Kesgin Atak B, Ersoy Tonyaloğlu E. Evaluating spectral indices for estimating burned areas in the case of Izmir / Turkey. Eurasian Journal of Forest Science. 2020;8:49–59.
MLA
Kesgin Atak, Birsen, ve Ebru Ersoy Tonyaloğlu. “Evaluating spectral indices for estimating burned areas in the case of Izmir / Turkey”. Eurasian Journal of Forest Science, c. 8, sy 1, Mart 2020, ss. 49-59, doi:10.31195/ejejfs.657253.
Vancouver
1.Birsen Kesgin Atak, Ebru Ersoy Tonyaloğlu. Evaluating spectral indices for estimating burned areas in the case of Izmir / Turkey. Eurasian Journal of Forest Science. 01 Mart 2020;8(1):49-5. doi:10.31195/ejejfs.657253

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