FEATURE EXTRACTION METHOD FOR SIMILAR DISTRICTS IN TWO CITIES AND ITS APPLICATION TO OTHER CITIES

In the Case of Tokyo, Kyoto, and Osaka

相似区域的特征提取方法在两个城市及其在其他城市的应用

以东京、京都和大阪为例

AKARI DOI; ATSUSHI TAKIZAWA

KEYWORDS：Spatial data analysis, similarity, feature extraction, enumeration, zero-suppressed binary decision diagram

关键词：空间数据分析，相似性，特征提取，列举法，零压缩二元决策图

本文来自于第十二届空间句法北京会议，文件夹“Urban Morphology”，序号435-1

论文下载链接 http://www.12sssbeijing.com/proceedings/

【浙江工业大学理论课作业】

Abstract

摘要

        Cities include districts with various features, and many studies have attempted to grasp the characteristics of cities by clustering districts with similar features. To date, the spatial clustering target has been a single urban space. However, districts with similar characteristics can be observed in different cities. We propose a feature extraction method that generates common feature functions using geographical data, such as population, industry type, use district, and similar districts in two cities. The usefulness of the proposed method was verified by applying the obtained feature function using Tokyo and Kyoto data to another city Osaka as verification data.

       城市包括具有多种特征的区域，许多研究试图通过聚集具有相似特征的区域来把握城市的特征。迄今为止，空间聚类指标一直是单一的城市空间。然而，在不同的城市也可以观察到具有相似特征的地区。本文提出了一种基于人口、行业类型、使用区域及相似地区等地理数据生成共同特征函数的特征提取方法。利用东京和京都的数据作为验证数据，将得到的特征函数应用到另一个城市大阪，验证了该方法的有效性。

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