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Investigation on the feasibility of mapping of oak forest dieback severity using Worldview-2 satellite data (Case study: Ilam forests)

Karami, Omid and Fallah, Asghar and Shataee, Shaban and Latifi, Hooman (2017) Investigation on the feasibility of mapping of oak forest dieback severity using Worldview-2 satellite data (Case study: Ilam forests). Iranian Journal of Forest and Poplar Research, 25 (3), pp. 452-462. ISSN 1735-0883.

Full text not available from this repository.

Official URL: http://ijfpr.areeo.ac.ir/article_112879.html

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."

Item URL in elib:https://elib.dlr.de/115525/
Document Type:Article
Title:Investigation on the feasibility of mapping of oak forest dieback severity using Worldview-2 satellite data (Case study: Ilam forests)
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Karami, OmidUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Fallah, Asgharsari university of agricultural sciences and natural resourcesUNSPECIFIEDUNSPECIFIED
Shataee, Shabangorgan university of agricultural sciences and natural resourcesUNSPECIFIEDUNSPECIFIED
Latifi, HoomanUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date:2017
Journal or Publication Title:Iranian Journal of Forest and Poplar Research
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Volume:25
Page Range:pp. 452-462
ISSN:1735-0883
Status:Published
Keywords:Artificial neural network, oak decline, remote sensing
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Geoscientific remote sensing and GIS methods
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center
Deposited By: Wöhrl, Monika
Deposited On:21 Nov 2017 13:35
Last Modified:19 Nov 2021 20:36

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