An integrated object-based image analysis and CA-Markov model approach for modeling land use/land cover trends in the Sa
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ORIGINAL PAPER
An integrated object-based image analysis and CA-Markov model approach for modeling land use/land cover trends in the Sarab plain Amin Naboureh 1 & Mohammad Hossein Rezaei Moghaddam 1 & Bakhtiar Feizizadeh 1 & Thomas Blaschke 2
Received: 2 July 2016 / Accepted: 27 April 2017 # Saudi Society for Geosciences 2017
Abstract The present paper is an attempt to integrate a semiautomated object-based image analysis (OBIA) classification framework and a cellular automata-Markov model to study land use/land cover (LULC) changes. Land use maps for the Sarab plain in Iran for the years 2000, 2006, and 2014 were created from Landsat satellite data, by applying an OBIA classification using the normalized difference vegetation index, salinity index, moisture stress index, soil-adjusted vegetation index, and elevation and slope indicators. The classifications yielded overall accuracies of 91, 93, and 94% for 2000, 2006, and 2014, respectively. Finally, using the transition matrix, the spatial distribution of land use was simulated for 2020. The results of the study revealed that the number of orchards with irrigated agriculture and dry-farm agriculture in the Sarab plain is increasing, while the amount of bare land is decreasing. The results of this research are of great importance for regional authorities and decision makers in strategic land use planning.
* Amin Naboureh [email protected] Mohammad Hossein Rezaei Moghaddam [email protected] Bakhtiar Feizizadeh [email protected] Thomas Blaschke [email protected] 1
Department of Physical Geography, Center for Remote Sensing and GIS, University of Tabriz, Tabriz, Iran
2
Department of Geoinformatics, University of Salzburg, Salzburg, Austria
Keywords Land use/cover . Object-based approach . CA-Markov . Spatial modeling . Sarab plain
Introduction Decision making in each country or region needs adequate information on many complex interrelated aspects of its activities (Memarian et al. 2013). Land use/cover change (LUCC) has been identified as a major driver of global and regional environmental changes and is increasingly recognized in today’s assessment of anthropogenic impacts on the environment on a global scale (Foley et al. 2005; Brovkin et al. 2013; Verburg et al. 2015). Technically speaking, population growth increases the pressure on both agricultural and natural resources, especially in developing countries. A greater food supply is required to satisfy the nutritional demand of the growing world population. Both the increasing population and the process of urbanization have augmented the pressure on agricultural resources (Dengiz et al. 2003). In many cases, the restricted availability of agricultural land is a serious factor, particularly in semiarid regions. This increased pressure on the available land resources may lead to land degradation (Elaalem et al. 2011). Reliable and precise land assessment is therefore crucial to the decision-making processes involved in developing land use/land cover (LULC) policies that will
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