Extracting Urban Land Use from Linked Open Geospatial Data

ISPRS International Journal of Geo-Information

Gloria Re Calegari¹  Emanuela Carlino²  Diego Peroni²  Irene Celino²  Jochen Schiewe² 

[1] ICT Center of Excellence For Research, Innovation, Education and industrial Labs partnerships (CEFRIEL), Politecnico di Milano, via Fucini 2, 20133 Milano, Italy;

关键词: urban land use;    linked open geo-spatial data;    points of interest;    smart cities;   

DOI  :  10.3390/ijgi4042109

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.