Residential location choice (RLC) predicts where and how people choose their residential location in the framework of land use–transport interaction models (LUTI). This paper seeks an efficient RLC model in the context of irregular zoning of location alternatives. The main current proposals in the field are discrete choice models. In RLC modeling, the alternatives are spatial units, and spatially correlated logit (SCL) is an efficient approach when the analyst cannot pre-define groups of alternatives that efficiently reflect the systematic substitution patterns among the alternatives. The SCL uses the spatial information on the contiguity of the zones to determine spatial correlation among the alternatives. Urban residential location choice usually uses administrative zoning, which is very irregular in many cities (mainly historic cities); however, SCL is not efficient in this context owing to the limitations of the binary contiguity spatial variable employed as a spatial correlation metric (SCM). This paper proposes an extension of the mixed SCL model, with an SCM based on the proportion of common border length in contiguous zones, which is more efficient in the irregular urban zoning context. The proposed model is applied to an urban case study of LUTI RLC modeling with irregular zoning, based on the administrative divisions of the city of Santander (Spain) and is shown to be empirically more efficient than the previous approaches.

中文翻译：

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不规则分区的住宅区位经济计量选择建模：公共边界空间相关度量

居住地点选择（RLC）可以在土地使用-运输互动模型（LUTI）的框架中预测人们在何处以及如何选择居住地点。本文在选址的不规则分区中寻求一种有效的RLC模型。该领域当前的主要建议是离散选择模型。在RLC建模中，替代方案是空间单位，当分析人员无法预先定义可有效反映替代方案之间系统替代模式的替代方案组时，空间相关对数（SCL）是一种有效的方法。SCL使用有关区域连续性的空间信息来确定替代方案之间的空间相关性。城市居民区位选择通常使用行政区划，这在许多城市（主要是历史悠久的城市）中非常不规则；然而，由于用作空间相关度量（SCM）的二进制连续性空间变量的局限性，SCL在这种情况下效率不高。本文提出了一种基于SCM的混合SCL模型的扩展，该模型基于连续区域中公共边界长度的比例，在不规则的城市分区环境中效率更高。基于西班牙桑坦德市（西班牙）的行政区划，拟议的模型被应用于具有不规则分区的LUTI RLC建模的城市案例研究，并在经验上比以前的方法更有效。基于连续区域中公共边界长度比例的SCM，在不规则的城市分区环境中效率更高。拟议的模型基于桑坦德市（西班牙）的行政区划，被用于带有不规则分区的LUTI RLC建模的城市案例研究中，并且在经验上比以前的方法更有效。SCM基于连续区域中公共边界长度的比例，在不规则的城市分区环境中效率更高。拟议的模型基于桑坦德市（西班牙）的行政区划，被用于带有不规则分区的LUTI RLC建模的城市案例研究中，并且在经验上比以前的方法更有效。