%0 Journal Article %1 karami2017investigation %A Karami, Omid %A Fallah, Asghar %A Shataee, Shaban %A Latifi, Hooman %D 2017 %J Iranian Journal of Forest and Poplar Research %K article Latifi LSFE %N 3 %P 452-462 %R 10.22092/ijfpr.2017.112879 %T Investigation on the feasibility of mapping of oak forest dieback severity using Worldview-2 satellite data (Case study: Ilam forests) %U http://ijfpr.areeo.ac.ir/article_112879.html %V 25 %X In recent years, oak decline phenomenon has caused severe damages in Zagros forests. To deal with and managed this crisis, prior to any action, having accurate information about the status and distribution area of this phenomena is necessary. Using satellite data is one of methods to achieve information on the extent and severity of die back. For this purpose, map of oak decline severity was prepared in four levels for some parts of Ilam forests using Worldview-2 satellite data. Maximum likelihood, naive bayes, Knearest neighbors and artificial neural network classification algorithm were used. The results showed that among different classification methods, the results of artificial neural network classification algorithm had most overall accuracy with 72.83%. Moreover, our results confirmed that the Worldview-2 satellite data can illustrate the severity of oak decline.

@article{karami2017investigation, abstract = {In recent years, oak decline phenomenon has caused severe damages in Zagros forests. To deal with and managed this crisis, prior to any action, having accurate information about the status and distribution area of this phenomena is necessary. Using satellite data is one of methods to achieve information on the extent and severity of die back. For this purpose, map of oak decline severity was prepared in four levels for some parts of Ilam forests using Worldview-2 satellite data. Maximum likelihood, naive bayes, Knearest neighbors and artificial neural network classification algorithm were used. The results showed that among different classification methods, the results of artificial neural network classification algorithm had most overall accuracy with 72.83%. Moreover, our results confirmed that the Worldview-2 satellite data can illustrate the severity of oak decline.}, added-at = {2020-09-11T12:04:50.000+0200}, author = {Karami, Omid and Fallah, Asghar and Shataee, Shaban and Latifi, Hooman}, biburl = {https://www.bibsonomy.org/bibtex/2cef6faf28edd37e1f1b9419c485c0a23/earthobs_uniwue}, doi = {10.22092/ijfpr.2017.112879}, interhash = {87546df2fce3ce1d2dc61a1e6eeed5d9}, intrahash = {cef6faf28edd37e1f1b9419c485c0a23}, journal = {Iranian Journal of Forest and Poplar Research}, keywords = {article Latifi LSFE}, number = 3, pages = {452-462}, timestamp = {2020-11-18T22:08:33.000+0100}, title = {Investigation on the feasibility of mapping of oak forest dieback severity using Worldview-2 satellite data (Case study: Ilam forests)}, url = {http://ijfpr.areeo.ac.ir/article_112879.html}, volume = 25, year = 2017 }