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Spatial and temporal dimensions of land use change in cross border region of Luxembourg. Development of a hybrid approach integrating GIS, cellular automata and decision learning tree models

机译:卢森堡跨境地区土地利用的时空变化。结合GIS,元胞自动机和决策学习树模型的混合方法的开发

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This paper presents a geographical and computational modelling approach to explore the nonlinear relationship between land use types and geospatial driving factors. It focuses on the dynamism of land use characteristics in a cross-border region. The developed model is based on fully integrated Cellular Automata (CA), Geographic Information System (GIS) and Decision Learning Tree (DLT) model, which is used to define the CA transition rules. Existing literature considers CA as one of the most relevant tools for modelling spatial changes over time, particularly when complex systems such as land use are involved. The literature also highlights that, when CA is combined with other tools, results lead to a better spatial prospect of land use dynamics. Our results reveal how land use is structured around both the transportation system and the border, and how measuring accessibility from different angles using GIS platform permits analysis of the temporal and spatial discontinuity of land use itself, thereby identifying the discontinuity components of land use patterns determined by land use boundaries. (C) 2015 Elsevier Ltd. All rights reserved.
机译:本文提出了一种地理和计算建模方法,以探索土地利用类型与地理空间驱动因素之间的非线性关系。它着重于跨境区域土地利用特征的动态性。开发的模型基于完全集成的蜂窝自动机(CA),地理信息系统(GIS)和决策学习树(DLT)模型,用于定义CA转换规则。现有文献将CA视为建模随时间变化的空间的最相关工具之一,尤其是在涉及诸如土地利用等复杂系统时。文献还强调,当将CA与其他工具结合使用时,结果会导致土地利用动态的空间前景更好。我们的结果揭示了土地利用如何围绕交通系统和边界构造,以及如何使用GIS平台从不同角度测量可及性,从而可以分析土地利用本身的时空不连续性,从而确定确定的土地利用方式的不连续性成分土地利用边界。 (C)2015 Elsevier Ltd.保留所有权利。

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