School of Architecture, Southeast University, Nanjing, Jiangsu 210096, China.
Architects & Engineers Co., Ltd. of Southeast University, Nanjing, Jiangsu 210096, China.
Comput Intell Neurosci. 2022 May 29;2022:1362272. doi: 10.1155/2022/1362272. eCollection 2022.
Landscape morphology is a significant area of landscape architecture research. One of the scientific and technological issues in recent landscape morphology research is the use of quantitative analysis technology driven by morphology indexes and computational models to describe, compare, and analyze form features. This article focuses on the form features of the polder landscape, based on existing theoretical and practical achievements in landscape morphology. First, we choose five landscape morphology indexes based on the morphological constituent units of the landscape (elongation, rectangular compactness, concavity, ellipse compactness, and fractal dimension). Then, using the self-organizing map (SOM), we create an identification model for clustering the types of constituent units. The experimental results show that the identification model can classify polder morphology and analyze the distribution of units using typical polders in the Yangtze River's south bank as study cases. This article presents a technical approach to polder landscape morphology classification as well as a reference and developable quantitative analysis method for landscape morphology research.
景观形态学是景观建筑学研究的一个重要领域。在最近的景观形态学研究中，科学和技术问题之一是使用形态指标和计算模型驱动的定量分析技术来描述、比较和分析形态特征。本文基于景观形态学的现有理论和实践成果，重点研究圩田景观的形态特征。首先，我们选择了五个基于景观形态组成单元的景观形态学指标（伸长率、矩形紧凑度、凹度、椭圆紧凑度和分形维数）。然后，使用自组织映射（SOM）创建一个识别模型，用于对组成单元的类型进行聚类。实验结果表明，该识别模型可以对圩田形态进行分类，并使用长江南岸的典型圩田作为研究案例来分析单元的分布。本文提出了一种圩田景观形态分类的技术方法，以及景观形态学研究的参考和可开发的定量分析方法。
