Volume 8, Issue 3 (12-2019)                   2019, 8(3): 31-44 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Mozafari F, Karamshahi A, Heydari M, karami O. Mapping Dieback Intensity Distribution in Zagros Oak Forests Using Geo-statistics and Artificial Neural Network. Iranian Journal of Applied Ecology 2019; 8 (3) :31-44
URL: http://ijae.iut.ac.ir/article-1-952-en.html
ilam university
Abstract:   (5466 Views)
The first and most important issue in forest drought management is knowledge of the location and severity of forest decline. In this regard, we used geostatistics and artificial neural network methods to map the dieback intensity of oak forests in the  Ilam province, Iran. We used a systematic random sampling with a 250 × 200 m grid to establish 100 plots, each covering 1200 m2. The percentage of the declined trees in each plot was measured and recorded. Also, a composite soil sample was extracted from the center and the four corners of each plot in order to determine their physical and chemical properties. After examining the normality of the data, the dieback intensity map was made using interpolation methods and the artificial neural network. The results showed  that the best method for dieback intensity estimation was the artificial neural network with an accuracy of 85 %, by using the multilayer perceptron algorithm. Oak decline was found to be mainly related to the slope, soil moisture, soil organic content and soil bulk density.
Full-Text [PDF 753 kb]   (1545 Downloads)    
Type of Study: Applicable | Subject: General

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Iranian Journal of Applied Ecology

Designed & Developed by : Yektaweb