USING CA-MARKOV MODEL TO MODEL THE SPATIOTEMPORAL CHANGE OF LAND USE/COVER IN FUXIAN LAKE FOR DECISION SUPPORT

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3. Individual and combined impacts of future land-use and climate conditions on extreme hydrological events in a representative basin of the Yangtze River Delta, China Q. Wang et al. 10.1016/j.atmosres.2019.104805
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19. Uncertainty in forecasting land cover land use at a watershed scale: Towards enhanced sustainable land management G. Harik et al. 10.1016/j.ecolmodel.2023.110515
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