Evaluating forest based land use change trends using a cellular automata Markov model: A case study of Turkey
Yazarlar (4)
Prof. Dr. Fatih SİVRİKAYA Kastamonu Üniversitesi, Türkiye
Ergin Çağatay Çankaya
Nuri Bozali Kahramanmaraş Sütçü İmam Üniversitesi, Türkiye
Arif Okumuş Kahramanmaraş Sütçü İmam Üniversitesi, Türkiye
| Bildiri Türü | Tebliğ/Bildiri | Bildiri Dili | İngilizce |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) | ||
| Bildiri Niteliği | Alanında Hakemli Uluslararası Kongre/Sempozyum | ||
| Kongre Adı | 38th Annual Meeting of COFE Symposium, Engineering Solutions for Non-Industrial Private Forest Operations | ||
| Kongre Tarihi | 19-07-2015 / 22-07-2015 | ||
| Basıldığı Ülke | Amerika Birleşik Devletleri | Basıldığı Şehir | Lexington |
| Özet |
| Land use changes greatly impact especially forest ecosystem such as carbon sequestration, water quality, global climate, and soil conditions. Therefore, identification and simulation of land use change that occur in a given period of time is important for decision makers. Precise estimates for future land use change giving a possible change can be determined with the help of simulation models. Simulation model can help the decision makers and land use planner to sustain forest ecosystem development. A Markov chain and cellular automata (CA) models are generally used to determine transition possibilities of land use categories. In this study, we investigated the capability of Markov chain analysis and CA model to better comprehend the dynamics of forest ecosystem for case study area in south east of Turkey. Temporal land use maps derived from stand type map from 1991, 2002, and 2012 and Markov cellular automata methods (CA–Markov) were used for characterizing trends and patterns 1991–2002 and 2002–2012, and to develop predictive scenarios through 2022. With Markov chain analysis, transition matrix was calculated based on 1991 and 2002 land use map and then predicted 2012 land use map using transition matrices. Predicted and actual land use map for 2012 were validated using accuracy value. Future land use were then projected using a CA–Markov model based on the 2002 and 2012 land use map and transition matrices. Integrated with Geographical Information System (GIS) and Cellular Automata-Markov Chain approach of land use changes has proven to be an effective way to predict future land cover. With the … |
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