عنوان مقاله [English]
Modeling Land Use Pattern, City Behbahan City in the
Period 2000 - 2028 Using Remote Sensing and GIS
Mohammadyari, F*1; Pourkhabbaz, H.R2;Aghdar, H3.; Tavakoly, M4
1 MSc of Evaluation and land use planning, Faculty of Natural Resources,
Behbahan Khatam Alanbia University of Technology, Iran
2 Assist. Profe. of Environment Department, Faculty of Natural Resources,
Behbahan Khatam Alanbia University of Technology, Iran
3 MSc. of Remote Sensing and GIS, Faculty of Science, Shahid Chamran University of Ahvaz, Iran
4 Associ. Profe. of Geography Tarbit Modaress University of Technology, Iran
(Received: 2017/05/09; Accepted: 2018/10/02)
Natural habitats such as rangelands and forests as one of the most sensitive elements of the environment and an important role in living organisms, including humans. In the decades before the present era of urban development has been such that an imbalance in the use of urban land led and pristine converted to urban land in others. In the present study to understand the changes in urban land, pasture and forest in Behbahan, images Landsat ETM + sensor OLI 2000 and 2014 were analyzed. CROSSTAB was used to assess the changes occurred. As well as to predict the trends of the year 2028 from the transmission potential maps logistic regression and Markov chain method was used. Results of the survey area in the first period (2000-2014) shows that urban land area of 1605 hectares in 2000 to 3157 ha in 2014 has increased. The most degradation of rangelands (6233 ha) and forests has occurred. The second period (2014-2028) compared to the 2014forest area remains unchanged, but increased urban development and reducing the area of pastures in Outlook 2028 will continue. In the period studied, the destruction of agricultural land for conversion into residential areas has increased significantly so that during 2000 to 2014, 291 hectares and in 2028, 626 hectares of agricultural land for construction purposes have been demolished.
Keywords: Urban development, Grasslands, Forests, Logistic regression, Markov chain
*Corresponding author: Email: email@example.com
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