scholarly journals Correction: Changes in mangrove species assemblages and future prediction of the Bangladesh Sundarbans using Markov chain model and cellular automata

2015 ◽  
Vol 17 (11) ◽  
pp. 1990-1991
Author(s):  
Anirban Mukhopadhyay ◽  
Parimal Mondal ◽  
Jyotiskona Barik ◽  
S. M. Chowdhury ◽  
Tuhin Ghosh ◽  
...  
Keyword(s):  
Markov Chain ◽  
Cellular Automata ◽  
Markov Chain Model ◽  
Species Assemblages ◽  
Chain Model ◽  
Mangrove Species ◽  
Future Prediction

Correction for ‘Changes in mangrove species assemblages and future prediction of the Bangladesh Sundarbans using Markov chain model and cellular automata’ by Anirban Mukhopadhyay et al., Environ. Sci.: Processes Impacts, 2015, 17, 1111–1117.

Changes in mangrove species assemblages and future prediction of the Bangladesh Sundarbans using Markov chain model and cellular automata

2015 ◽  
Vol 17 (6) ◽  
pp. 1111-1117 ◽  
Author(s):  
Anirban Mukhopadhyay ◽  
Parimal Mondal ◽  
Jyotiskona Barik ◽  
S. M. Chowdhury ◽  
Tuhin Ghosh ◽  
...  
Keyword(s):  
Markov Chain ◽  
Environmental Factors ◽  
Cellular Automata ◽  
Markov Chain Model ◽  
Species Assemblages ◽  
Chain Model ◽  
Mangrove Species ◽  
Future Prediction

The composition and assemblage of mangroves in the Bangladesh Sundarbans are changing systematically in response to several environmental factors.

Application of Cellular automata and Markov-chain model in geospatial environmental modeling- A review

2017 ◽  
Vol 5 ◽  
pp. 64-77 ◽  
Author(s):  
Pramit Ghosh ◽  
Anirban Mukhopadhyay ◽  
Abhra Chanda ◽  
Parimal Mondal ◽  
Anirban Akhand ◽  
...  
Keyword(s):  
Markov Chain ◽  
Cellular Automata ◽  
Markov Chain Model ◽  
Environmental Modeling ◽  
Chain Model

scholarly journals Monitoring and Predicting Spatio-Temporal Land Use/Land Cover Changes in Zaria City, Nigeria, through an Integrated Cellular Automata and Markov Chain Model (CA-Markov)

2020 ◽  
Vol 12 (24) ◽  
pp. 10452
Author(s):  
Auwalu Faisal Koko ◽  
Wu Yue ◽  
Ghali Abdullahi Abubakar ◽  
Roknisadeh Hamed ◽  
Akram Ahmed Noman Alabsi
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Cellular Automata ◽  
Land Cover ◽  
Markov Chain Model ◽  
Chain Model ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Barren Land ◽  
Spatio Temporal

Monitoring land use/land cover (LULC) change dynamics plays a crucial role in formulating strategies and policies for the effective planning and sustainable development of rapidly growing cities. Therefore, this study sought to integrate the cellular automata and Markov chain model using remotely sensed data and geographical information system (GIS) techniques to monitor, map, and detect the spatio-temporal LULC change in Zaria city, Nigeria. Multi-temporal satellite images of 1990, 2005, and 2020 were pre-processed, geo-referenced, and mapped using the supervised maximum likelihood classification to examine the city’s historical land cover (1990–2020). Subsequently, an integrated cellular automata (CA)–Markov model was utilized to model, validate, and simulate the future LULC scenario using the land change modeler (LCM) of IDRISI-TerrSet software. The change detection results revealed an expansion in built-up areas and vegetation of 65.88% and 28.95%, respectively, resulting in barren land losing 63.06% over the last three decades. The predicted LULC maps of 2035 and 2050 indicate that these patterns of barren land changing into built-up areas and vegetation will continue over the next 30 years due to urban growth, reforestation, and development of agricultural activities. These results establish past and future LULC trends and provide crucial data useful for planning and sustainable land use management.

scholarly journals Improving land-use change modeling by integrating ANN with Cellular Automata-Markov Chain model

Heliyon ◽  
2020 ◽  
Vol 6 (9) ◽  
pp. e05092
Author(s):  
Anne Gharaibeh ◽  
Abdulrazzaq Shaamala ◽  
Rasha Obeidat ◽  
Salman Al-Kofahi
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Cellular Automata ◽  
Land Use Change ◽  
Markov Chain Model ◽  
Chain Model ◽  
Land Use Change Modeling

Application of modified cellular automata Markov chain model: forecasting land use pattern in Lebanon

2020 ◽  
Author(s):  
Walid Al-Shaar ◽  
Jocelyne Adjizian Gérard ◽  
Nabil Nehme ◽  
Hassan Lakiss ◽  
Liliane Buccianti Barakat
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Cellular Automata ◽  
Markov Chain Model ◽  
Chain Model ◽  
Land Use Pattern ◽  
Use Pattern
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