A Multiple Subspaces-Based Model: Interpreting Urban Functional Regions with Big Geospatial Data

Jiawei Zhu,Haozhe Huang,Jian Peng,Chao Tao,Li Chen,Xin Lin,Qiongjie Wang

doi:10.3390/ijgi10020066

Abstract

Analyzing the urban spatial structure of a city is a core topic within urban geographical information science that has the ability to assist urban planning, site selection, location recommendation, etc. Among previous studies, comprehending the functionality of places is a central topic and corresponds to understanding how people use places. With the help of big geospatial data which contain affluent information about human mobility and activity, we propose a novel multiple subspaces-based model to interpret the urban functional regions. This model is based on the assumption that the temporal activity patterns of places lie in a high-dimensional space and can be represented by a union of low-dimensional subspaces. These subspaces are obtained through finding sparse representations using the data science method known as sparse subspace clustering (SSC). The paper details how to use this method in the context of detecting functional regions. With these subspaces, we can detect the functionality of urban regions in a designated study area and further explore the characteristics of functional regions. We conducted experiments using real data in Shanghai. The experimental results and outperformance of our proposed model against the single subspace-based method prove the efficacy and feasibility of our model.

Highlights

Analyzing the urban structure of a city is a primary research topic in the urban geographical information sciences
As the similarity between geographical units indicates that they belong to the same functional region, the number of subspaces can be inferred as five based on the number of darker blocks
We proposed a model based on the idea that urban spatial structure could be inferred from human temporal activity with the aid of big geospatial data

Summary

Introduction

Analyzing the urban structure of a city is a primary research topic in the urban geographical information sciences. Therein, understanding different functions and their corresponding spatial distribution, i.e., functional regions, has drawn a lot of interest [1,2,3]. Functional regions describe urban space usage like when and why people visit a place and provide insights for a group of people. It helps decision-makers and researchers to calibrate the urban planning, assess the urban spatial structure, and study social and spatial disparities [4,5,6]. It provides strangers like tourists with a quick understanding of the city and benefits social recommendations [7]. It is necessary to update the knowledge about the urban functional regions in time to capture the urban growth and facilitate better urban planning, site selection, location recommendation, etc

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Conclusion