Detection and Projection of Forest Changes by Using the Markov Chain Model and Cellular Automata
| Autor: | Alfredo Pinedo-Alvarez, Raúl Solís-Moreno, Griselda Vázquez-Quintero, Federico Villarreal-Guerrero, Marín Pompa-García, Carmelo Pinedo-Alvarez |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
010504 meteorology & atmospheric sciences
landsat Geography Planning and Development lcsh:TJ807-830 lcsh:Renewable energy sources 010501 environmental sciences Management Monitoring Policy and Law 01 natural sciences Temperate climate land use changes lcsh:Environmental sciences 0105 earth and related environmental sciences lcsh:GE1-350 Land use Markov chain Renewable Energy Sustainability and the Environment Ecology simulation temperate forest lcsh:Environmental effects of industries and plants Probabilistic logic Temperate forest Multispectral Scanner lcsh:TD194-195 Thematic Mapper Environmental science Physical geography Temperate rainforest |
| Zdroj: | Sustainability, Vol 8, Iss 3, p 236 (2016) Sustainability; Volume 8; Issue 3; Pages: 236 |
| ISSN: | 2071-1050 |
| Popis: | The spatio-temporal analysis of land use changes could provide basic information for managing the protection, conservation and production of forestlands, which promotes a sustainable resource use of temperate ecosystems. In this study we modeled and analyzed the spatial and temporal dynamics of land use of a temperate forests in the region of Pueblo Nuevo, Durango, Mexico. Data from the Landsat images Multispectral Scanner (MSS) 1973, Thematic Mapper (TM) 1990, and Operational Land Imager (OLI) 2014 were used. Supervised classification methods were then applied to generate the land use for these years. To validate the land use classifications on the images, the Kappa coefficient was used. The resulting Kappa coefficients were 91%, 92% and 90% for 1973, 1990 and 2014, respectively. The analysis of the change dynamics was assessed with Markov Chains and Cellular Automata (CA), which are based on probabilistic modeling techniques. The Markov Chains and CA show constant changes in land use. The class most affected by these changes is the pine forest. Changes in the extent of temperate forest of the study area were further projected until 2028, indicating that the area of pine forest could be continuously reduced. The results of this study could provide quantitative information, which represents a base for assessing the sustainability in the management of these temperate forest ecosystems and for taking actions to mitigate their degradation. |
| Databáze: | OpenAIRE |
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