Full Text:   <3874>

CLC number: X9

On-line Access: 2008-01-27

Received: 2007-10-20

Revision Accepted: 2007-12-10

Crosschecked: 0000-00-00

Cited: 5

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Journal of Zhejiang University SCIENCE A 2008 Vol.9 No.3 P.381~390


Environmental impact prediction using remote sensing images

Author(s):  Pezhman ROUDGARMI, Masoud MONAVARI, Jahangir FEGHHI, Jafar NOURI, Nematollah KHORASANI

Affiliation(s):  Tehran Agricultural and Natural Resources Research Center, Agricultural Research and Education Organization (AREO), Tehran, Iran; more

Corresponding email(s):   Roudgarmi@yahoo.com, monavarism@yahoo.com, jfeghhi@ut.ac.ir, jnouri@tums.ac.ir, Khorasan@chamran.ut.

Key Words:  Environmental impact, Remote sensing, Prediction, Vegetation, Biomass

Pezhman ROUDGARMI, Masoud MONAVARI, Jahangir FEGHHI, Jafar NOURI, Nematollah KHORASANI. Environmental impact prediction using remote sensing images[J]. Journal of Zhejiang University Science A, 2008, 9(3): 381~390.

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author="Pezhman ROUDGARMI, Masoud MONAVARI, Jahangir FEGHHI, Jafar NOURI, Nematollah KHORASANI",
journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

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%T Environmental impact prediction using remote sensing images
%A Jahangir FEGHHI
%A Jafar NOURI
%A Nematollah KHORASANI
%J Journal of Zhejiang University SCIENCE A
%V 9
%N 3
%P 381~390
%@ 1673-565X
%D 2008
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A072222

T1 - Environmental impact prediction using remote sensing images
A1 - Pezhman ROUDGARMI
A1 - Masoud MONAVARI
A1 - Jahangir FEGHHI
A1 - Jafar NOURI
A1 - Nematollah KHORASANI
J0 - Journal of Zhejiang University Science A
VL - 9
IS - 3
SP - 381
EP - 390
%@ 1673-565X
Y1 - 2008
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A072222

environmental impact prediction is an important step in many environmental studies. A wide variety of methods have been developed in this concern. During this study, remote sensing images were used for environmental impact prediction in Robatkarim area, Iran, during the years of 2005~2007. It was assumed that environmental impact could be predicted using time series satellite imageries. Natural vegetation cover was chosen as a main environmental element and a case study. environmental impacts of the regional development on natural vegetation of the area were investigated considering the changes occurred on the extent of natural vegetation cover and the amount of biomass. vegetation data, land use and land cover classes (as activity factors) within several years were prepared using satellite images. The amount of biomass was measured by Soil-adjusted vegetation Index (SAVI) and Normalized Difference vegetation Index (NDVI) based on satellite images. The resulted biomass estimates were tested by the paired samples t-test method. No significant difference was observed between the average biomass of estimated and control samples at the 5% significance level. Finally, regression models were used for the environmental impacts prediction. All obtained regression models for prediction of impacts on natural vegetation cover show values over 0.9 for both correlation coefficient and R-squared. According to the resulted methodology, the prediction models of projects and plans impacts can also be developed for other environmental elements which may be derived using time series remote sensing images.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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