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Modelling
land use/cover change in Lake Mogan and surroundings using CA-Markov Chain
Analysis
Z.O.
Durmusoglu1* and A.A. Tanriover2
1Department of
Urban and Regional Planning, Faculty of Architecture, Gazi University,
Ankara, 06570, Turkey
2Department of
Urban and Regional Planning, Faculty of Natural Sciences, Architecture and Engineering,
Bursa Technical University, Bursa, 16330, Turkey
*Corresponding
Author E-mail: azokaydurmusoglu@gmail.com
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Key
words
CA-Markov Chain Analysis,
Change detection,
Modelling,
Lake Mogan,
Land use/cover change
Publication Data
Paper received :? 21.08.2016
Revised received :?
25.06.2017????????????????????
Accepted : 28.06.2017
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Abstract
Aim: Lake Mogan, having
high ecological and cultural significance, has been under intense pressure of
urbanization and industrialization due to its location on the periphery of
the capital Ankara. In this study, we analyzed data from satellite remote
sensing, Geographic Information System and Cellular Automata Markov Chain
modelling to predict land use/cover changes in Lake Mogan and surrounding
areas.
Methodology:
Three
images recorded in 1975 and 1999 (air photos) and 2009 (Quickbird image) were
used to detect the land use/cover changes over the time. An object-based
supervised classification approach to simulate changes in the study area for
the future was performed. Land use/cover changes for the year 2029 was
modelled using Cellular Automata Markov Chain Analysis with the support of
suitability analysis.
Results:
The
results indicated that most of the agricultural areas will be converted into
settlements over the next 40 years. Modelling results for 2029 also showed
that land degradation activities are likely to continue in the future.
Interpretation: According to model
on land use changes in Lake Mogan and surrounding areas, there is an
immediate need to take long-term measures for sustainable land development
based on the regional scales, preferably on the basin level.
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Copyright
? 2017 Triveni Enterprises. All rights reserved. No part of the Journal can
be reproduced in any form without prior permission. Responsibility
regarding the authenticity of the data, and the acceptability of the
conclusions enforced or derived, rest completely with the author(s).
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