城市土地利用结构的空间模式识别有助于交通和土地利用建模

Seyed Ahad Beykaei, M. Zhong, E. Miller
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引用次数: 4

摘要

交通和土地利用规划者和建模者经常在建模工作中利用区域系统利用现成的社会经济数据。最重要的问题是,分析区规模通常较大,因此在许多情况下无法实现同质或单一类型的土地利用。随后,无法捕获区域内的移动和混合活动分布,并且不得不损害建模的准确性。本研究分析了区域内不同LU的形态和空间结构/格局,发现了LU类型与地块的若干形态属性(建筑高度、建筑面积、建筑周长、建筑密实度、地块面积)及其空间排列指标(Gabriel Line和Gabriel Length)之间的相关性。利用二元logistic模型拟合形态特征和空间指标,提取住宅用地和商业用地。最终结果表明,住宅和商业用地的总体提取准确率分别为98.4%和69.0%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial pattern recognition of the structure of urban land uses useful for transportation and land use modelling
Transportation and land use planners and modelers often use zone systems to take advantage of readily available socio-economic data in their modelling exercises. The most important issue is that analysis zone size is usually large, and therefore, homogeneous or single-type land uses cannot be achieved in many cases. Subsequently, intra-zone travel and mixed activities distribution cannot be captured and modeling accuracy has to be compromised. This study analyzes the form and spatial structure/pattern of different LUs within zone and find correlations between LU types and several morphological properties (building height, building area, building perimeter, building compactness, and parcel area) of parcels and their spatial arrangement indexes (Gabriel Line and Gabriel Length). Binary logistic model is then applied and fitted to the morphological properties and spatial indexes in order to extract residential and commercial LUs. The final Result demonstrates that residential and commercial LUs are extracted with an overall accuracy of 98.4% and 69.0% respectively.
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