ENVIRONMENTAL IMPACT PREDICTION USING REMOTE SENSING IMAGES AND TECHNIQUES

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ROUDGARMI PEJHMAN; KHORASANI NEMATOLLAH; MONAVARI MASOUD; NOURI JAFAR

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Paper Information

Journal: JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY Year:2009 | Volume:11 | Issue:1 (SPECIAL ISSUE 40) Page(s): 161-172

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Information Journal Paper

Title

ENVIRONMENTAL IMPACT PREDICTION USING REMOTE SENSING IMAGES AND TECHNIQUES

Author(s)

ROUDGARMI PEJHMAN | KHORASANI NEMATOLLAH | MONAVARI MASOUD | NOURI JAFAR | Issue Writer Certificate

Keywords

ENVIRONMENTAL IMPACTQ2

REMOTE SENSINGQ2

PREDICTIONQ1

VEGETATIONQ2

BIOMASSQ2

Abstract

ENVIRONMENTAL IMPACT PREDICTION is an important step in many environmental studies. A wide variety of methods have already been developed in this area. 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 SAVI and NDVI indices based on satellite images. The resulted BIOMASS estimates were tested by the paired samplest -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.

Cites

DEVELOPMENT OF LAND USE DEVELOPMENT OF THE CITY OF MALAYER USING REMOTE SENSING

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APA: Copy

ROUDGARMI, PEJHMAN, KHORASANI, NEMATOLLAH, MONAVARI, MASOUD, & NOURI, JAFAR. (2009). ENVIRONMENTAL IMPACT PREDICTION USING REMOTE SENSING IMAGES AND TECHNIQUES. JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY, 11(1 (SPECIAL ISSUE 40)), 161-172. SID. https://sid.ir/paper/87126/en

Vancouver: Copy

ROUDGARMI PEJHMAN, KHORASANI NEMATOLLAH, MONAVARI MASOUD, NOURI JAFAR. ENVIRONMENTAL IMPACT PREDICTION USING REMOTE SENSING IMAGES AND TECHNIQUES. JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY[Internet]. 2009;11(1 (SPECIAL ISSUE 40)):161-172. Available from: https://sid.ir/paper/87126/en

IEEE: Copy

PEJHMAN ROUDGARMI, NEMATOLLAH KHORASANI, MASOUD MONAVARI, and JAFAR NOURI, “ENVIRONMENTAL IMPACT PREDICTION USING REMOTE SENSING IMAGES AND TECHNIQUES,” JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY, vol. 11, no. 1 (SPECIAL ISSUE 40), pp. 161–172, 2009, [Online]. Available: https://sid.ir/paper/87126/en

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