Empirical modeling potential transfer of land cover change pa city with neural network algorithms
Land-use change is one of the most important challenges of land-use planning that lies with planners, decision-makers and policymakers and has a direct impact on many issues, such as economic growth and the quality of the environment. The present study examines the land use change trends in Behbahan...
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Kharazmi University
2018-03-01
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| Series: | تحقیقات کاربردی علوم جغرافیایی |
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| Online Access: | http://jgs.khu.ac.ir/article-1-2580-en.pdf |
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| author | fatemeh mohammadyary hamidreza pourkhabbaz hossin aghdar morteza Tavakoly |
| author_facet | fatemeh mohammadyary hamidreza pourkhabbaz hossin aghdar morteza Tavakoly |
| author_sort | fatemeh mohammadyary |
| collection | DOAJ |
| description | Land-use change is one of the most important challenges of land-use planning that lies with planners, decision-makers and policymakers and has a direct impact on many issues, such as economic growth and the quality of the environment. The present study examines the land use change trends in Behbahan city for 2014 and 2028 using LCM in the GIS environment. Analysis and visibility of user variations, carried out in two periods of Landsat satellite images of 2000 (ETM + sensor) and 2014 (OLI sensors), and land cover maps for each year. The transmission potential modeling was performed by using the multi-layer perceptron artificial neural network algorithm using six independent variables and the distribution of changes in user usage were calculated by Markov chain method. The results of the prediction showed that the most reduction in the changes is the degradation of the rangelands and the greatest increase in the area of agricultural use. According to the horizontal tabulation results of the 2028 map, it can be stated that from the total area of the area 28336.22 hectares of land were unchanged and 33223.78 hectares of land use change. Also Rangeland and forest degradation during this time period can be a danger to urban planners and natural resources.
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| format | Article |
| id | doaj-art-6c30e365bd4b4bb0be5e70c76977f70a |
| institution | Kabale University |
| issn | 2228-7736 2588-5138 |
| language | fas |
| publishDate | 2018-03-01 |
| publisher | Kharazmi University |
| record_format | Article |
| series | تحقیقات کاربردی علوم جغرافیایی |
| spelling | doaj-art-6c30e365bd4b4bb0be5e70c76977f70a2025-01-31T17:24:38ZfasKharazmi Universityتحقیقات کاربردی علوم جغرافیایی2228-77362588-51382018-03-011850219234Empirical modeling potential transfer of land cover change pa city with neural network algorithmsfatemeh mohammadyary0hamidreza pourkhabbaz1hossin aghdar2morteza Tavakoly3 Behbahan Khatam Alanbia University of Technology Behbahan Khatam Alanbia University of Technology Shahid Chamran University of Ahvaz Associ profe of Geography Tarbiat Modares University of Technology Land-use change is one of the most important challenges of land-use planning that lies with planners, decision-makers and policymakers and has a direct impact on many issues, such as economic growth and the quality of the environment. The present study examines the land use change trends in Behbahan city for 2014 and 2028 using LCM in the GIS environment. Analysis and visibility of user variations, carried out in two periods of Landsat satellite images of 2000 (ETM + sensor) and 2014 (OLI sensors), and land cover maps for each year. The transmission potential modeling was performed by using the multi-layer perceptron artificial neural network algorithm using six independent variables and the distribution of changes in user usage were calculated by Markov chain method. The results of the prediction showed that the most reduction in the changes is the degradation of the rangelands and the greatest increase in the area of agricultural use. According to the horizontal tabulation results of the 2028 map, it can be stated that from the total area of the area 28336.22 hectares of land were unchanged and 33223.78 hectares of land use change. Also Rangeland and forest degradation during this time period can be a danger to urban planners and natural resources. <link href="moz-extension://8b922523-7922-435a-ac74-8ddb59e9beaf/skin/s3gt_tooltip_mini.css" rel="stylesheet" type="text/css" > #s3gt_translate_tooltip_mini { display: none !important; }http://jgs.khu.ac.ir/article-1-2580-en.pdftrend of changemarkov chainneural networkland change modelar |
| spellingShingle | fatemeh mohammadyary hamidreza pourkhabbaz hossin aghdar morteza Tavakoly Empirical modeling potential transfer of land cover change pa city with neural network algorithms تحقیقات کاربردی علوم جغرافیایی trend of change markov chain neural network land change modelar |
| title | Empirical modeling potential transfer of land cover change pa city with neural network algorithms |
| title_full | Empirical modeling potential transfer of land cover change pa city with neural network algorithms |
| title_fullStr | Empirical modeling potential transfer of land cover change pa city with neural network algorithms |
| title_full_unstemmed | Empirical modeling potential transfer of land cover change pa city with neural network algorithms |
| title_short | Empirical modeling potential transfer of land cover change pa city with neural network algorithms |
| title_sort | empirical modeling potential transfer of land cover change pa city with neural network algorithms |
| topic | trend of change markov chain neural network land change modelar |
| url | http://jgs.khu.ac.ir/article-1-2580-en.pdf |
| work_keys_str_mv | AT fatemehmohammadyary empiricalmodelingpotentialtransferoflandcoverchangepacitywithneuralnetworkalgorithms AT hamidrezapourkhabbaz empiricalmodelingpotentialtransferoflandcoverchangepacitywithneuralnetworkalgorithms AT hossinaghdar empiricalmodelingpotentialtransferoflandcoverchangepacitywithneuralnetworkalgorithms AT mortezatavakoly empiricalmodelingpotentialtransferoflandcoverchangepacitywithneuralnetworkalgorithms |