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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Simulating the Range Expansion ofSpartina alterniflorain Ecological Engineering through Constrained Cellular Automata Model and GIS
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Simulating the Range Expansion ofSpartina alterniflorain Ecological Engineering through Constrained Cellular Automata Model and GIS

机译:通过约束元胞自动机模型和GIS模拟互花米草生态工程的范围扩展

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摘要

Environmental factors play an important role in the range expansion ofSpartina alterniflorain estuarine salt marshes. CA models focusing on neighbor effect often failed to account for the influence of environmental factors. This paper proposed a CCA model that enhanced CA model by integrating constrain factors of tidal elevation, vegetation density, vegetation classification, and tidal channels in Chongming Dongtan wetland, China. Meanwhile, a positive feedback loop between vegetation and sedimentation was also considered in CCA model through altering the tidal accretion rate in different vegetation communities. After being validated and calibrated, the CCA model is more accurate than the CA model only taking account of neighbor effect. By overlaying remote sensing classification and the simulation results, the average accuracy increases to 80.75% comparing with the previous CA model. Through the scenarios simulation, the future ofSpartina alternifloraexpansion was analyzed. CCA model provides a new technical idea and method for salt marsh species expansion and control strategies research.
机译:环境因素在互花米草河口盐沼的范围扩展中起重要作用。专注于邻居效应的CA模型通常无法解释环境因素的影响。本文提出了一种CCA模型,该模型结合了崇明东滩湿地的潮汐高程,植被密度,植被分类和潮汐通道等约束因素,从而增强了CA模型。同时,在CCA模型中,通过改变不同植被群落的潮汐增生速率,还考虑了植被与沉积物之间的正反馈回路。经过验证和校准后,CCA模型比仅考虑邻居效应的CA模型更为准确。通过叠加遥感分类和仿真结果,与以前的CA模型相比,平均精度提高到80.75%。通过情景模拟,分析了互花米草的扩展前景。 CCA模型为盐沼物种扩展和控制策略研究提供了新的技术思路和方法。

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