Extracting Urban Land Use from Linked Open Geospatial Data

Gloria Calegari,Irene Celino,Emanuela Carlino,Diego Peroni

doi:10.3390/ijgi4042109

Gloria Calegari, Irene Celino + Show 2 more

Open Access

https://doi.org/10.3390/ijgi4042109

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Abstract

The ever-increasing availability of linked open geospatial data provides an unprecedented source of geo-information to describe urban environments. This wealth of data should be turned into actionable knowledge: for example, open data could be used as a proxy or substitute for closed or expensive information. The successful employment of linked open geospatial data can pave the way for innovative solutions to smart city problems. In this paper, we illustrate a set of experiments that, starting from linked open geospatial data, execute a knowledge discovery process to predict urban semantics. More specifically, we leverage geo-information about points of interests as input in a classification model of land use at a moderate spatial resolution (250 meters) over wide urban areas in Europe. We replicate our experiments in different European cities—Milano, München, Barcelona and Brussels—to ensure the repeatability and generality of our approach, and we explain the experimental conditions, as well as the employed datasets to guarantee reproducibility. We extensively report on quantitative and qualitative evaluation results, to judge the validity, as well as the limitations of our proposed approach.

Highlights

Urban space digitization, caused by the ever-increasing pervasiveness of information and communication technologies, has led to a rich ecosystem of information producers and information consumers [1]
The goal of this paper is to experiment on whether free linked open geospatial data related to urban environments can be used as a “proxy” for expensive land use geo-information sources with the meaning explained above, to what [7,8,9,10] did by using social media, mobile phone data or GPS traces
We present our innovative solution for extracting urban land use and support smart cities’ planning activities

Summary

Introduction

Urban space digitization, caused by the ever-increasing pervasiveness of information and communication technologies, has led to a rich ecosystem of information producers and information consumers [1]. This wealth of data, risks hiding the latent added value that the smart management of such information can bring to cities. The open question remains “what is the relevant information to achieve my objective?”: information consumers could be flooded and get lost in big data without solving their tasks In this picture, linked open geospatial data can play an important role, providing rich semantic geo-information related to urban environments. The datasets’ costs are related to the entire data-driven value chain, from production to distribution, from processing to consumption [5]

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