Tonbul, H. Et Al. 2022. Pixel- and Object-Based ensemble learning for forest burn severity using USGS FIREMON and Mediterranean condition dNBRs in Aegean ecosystem (Turkey). Advances in Space Research , vol.69, no.10 , 3609-3632.

Tonbul, H., Colkesen, I., & Kavzoglu, T., (2022). Pixel- and Object-Based ensemble learning for forest burn severity using USGS FIREMON and Mediterranean condition dNBRs in Aegean ecosystem (Turkey). Advances in Space Research , vol.69, no.10, 3609-3632.

Tonbul, Hasan, Ismail Colkesen, And Taskin Kavzoglu. "Pixel- and Object-Based ensemble learning for forest burn severity using USGS FIREMON and Mediterranean condition dNBRs in Aegean ecosystem (Turkey)," Advances in Space Research , vol.69, no.10, 3609-3632, 2022

Tonbul, Hasan Et Al. "Pixel- and Object-Based ensemble learning for forest burn severity using USGS FIREMON and Mediterranean condition dNBRs in Aegean ecosystem (Turkey)." Advances in Space Research , vol.69, no.10, pp.3609-3632, 2022

Tonbul, H. Colkesen, I. And Kavzoglu, T. (2022) . "Pixel- and Object-Based ensemble learning for forest burn severity using USGS FIREMON and Mediterranean condition dNBRs in Aegean ecosystem (Turkey)." Advances in Space Research , vol.69, no.10, pp.3609-3632.

@article{article, author={Hasan Tonbul Et Al. }, title={Pixel- and Object-Based ensemble learning for forest burn severity using USGS FIREMON and Mediterranean condition dNBRs in Aegean ecosystem (Turkey)}, journal={Advances in Space Research}, year=2022, pages={3609-3632} }