A Random Forest-Based CA-Markov Model to Examine the Dynamics of Land Use/Cover Change Aided with Remote Sensing and GIS

Understanding the land use/cover change (LUCC) in watersheds is essential for sustainable development. The CA-Markov model has been proven to be an effective method for land use modeling because of its simplicity and potential for evolution. However, it is difficult to apply this method to meet the...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2023-04, Vol.15 (8), p.2128
Main Authors: Zhang, Zhenyu, Hörmann, Georg, Huang, Jinliang, Fohrer, Nicola
Format: Article
Language:English
Subjects:
Accuracy
Agricultural land
Algorithms
Artificial intelligence
CA-Markov
China
Classification
Coastal waters
Comparative analysis
Distribution
Economic growth
Environmental changes
Evolution
GDP
GIS
Gross Domestic Product
Identification and classification
Land cover
Land use
Land use management
Land use planning
land use/cover change
Machine learning
Markov chains
Minjiang River Watershed
Observations
people
Population growth
random forest
Regression analysis
Remote sensing
rivers
Satellite imaging
Sustainability
Sustainable development
topography
Urban areas
Urban development
Urbanization
Watershed management
Watersheds
Woodlands
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