RESEARCH ARTICLE

USING PRINCIPLE COMPONENT ALGORITHMS TO EVALUATE SHRINKING OF THE BIGGEST SALINE LAKE UNDER CLIMATE CHANGE IN MIDDLE EAST

Abstract

Lakes cover only small part of Earth’s surface water and they effect directly on environment and economic of that region. However, increasing temperature and evaporation, decreasing rainfall cause that most of waters decreased over the past years. Lake Urmia is located between East and West Azerbaijan Provinces in northwest of Iran and is the largest lake in the Middle East and the sixth-largest salt water lake in the world. Urmia Lake has important role in environment and economics of North West of Iran. Our focus in this research is to evaluate spatial and temporal changes of Urmia Lake, which is one of the most important water resources in Iran, using landsat ETM+ and OLI images during the period of 2010 to 2017. Remote sensing can help to monitoring the ecosystem changes such as lakes. The integration of remote sensing technologies and GIS is producing new insights into the water management systems. In this study potential of the supervised classification with classification work flow algorithm for shrinking map with Landsat imagery was evaluated in Urmia Lake. Also relative water depth based on Principle Component algorithm is generated to produce relative depth changes map during 8 years. The results indicate that high temperature and less rainfall effect directly on lake in 2014 and it decrease to the smallest part during 8 years. Human activities have surged in this year and satellite data demonstrate that lake area decline sharply. As a conclusion, human activities and climate change are the most important roles in shrinking of Urmia Lake.

Keywords: Lake Urmia, landsat, water management, classification, remote sensing

How to Cite: Judy,F,Bolatova,Z,Saadatfar,E, (2018). USING PRINCIPLE COMPONENT ALGORITHMS TO EVALUATE SHRINKING OF THE BIGGEST SALINE LAKE UNDER CLIMATE CHANGE IN MIDDLE EAST.WILDLANKA, 6(3):Pages 126-132

Published On:2018-09-30

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