Land Use Change Detection and Prediction Using Markov-CA and Publishing on the Web with Platform Map Server, Case Study: Qom Metropolis, Iran

Mojtaba Pirnazar, Nasrin Haghighi, Donya Azhand, Dr. Kaveh Ostad-Ali-Askari, Professor Saeid Eslamian, Professor Nicolas R. Dalezios, Professor Vijay P. Singh


To achieve sustainable development, detailed planning, control and management of land cover changes that occurs naturally or by human caused artificial factors, is essential. Urban managers and planners need a tool that represents them the information accurate, fast and in exact time. In this study, land use changes of 3 periods 1994-2002, 2002-2009, 2009-2015 and predictions of 2009, 2015 and 2023 were assessed. In this paper, Maximum Likelihood method was used to classify the images, so that after evaluation of accuracy, amount of overall accuracy for images of 2013 was 85.55 % and its Kappa coefficient was 80.03%. To predict land use changes, Markov-CA model was used that after assessing the accuracy, the amount of overall accuracy for 2009 was 82.57% and for 2015 was 93.865%. ThenWebGis application was designed via map server application and evoked shape files through map file and open layers to browser environment and for design of appearance of website Css, HTML and JavaScript languages were used. HTML is responsible for creating the foundation and overall structure of webpage but beautify and layout design is on Css.

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This site is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.