Rethinking Spatial Tessellation in an Era of the Smart City

Abstract

Smart cities frequently rely on vast sensor networks, such as traffic cameras and ventilation controllers. This requires that we rethink methods of spatial tessellation. As tessellation is becoming more dynamic, we often combine multiple tessellation methods and switch tessellation shapes frequently for different data collection and analytics. In this article, we review how tessellation works with the object and field geographic spatial models. To achieve the “smartness” within cities, this article introduces the dynamic tessellation approach as the initial solution. Key Words: big data, sensor network, smart city, spatial tessellation.

智慧城市的运行通常都离不开一个庞大的传感器网络，比如交通摄像头和通风控制器等。 这就要求我们重新思考空间网格细分方法。随着这种网格细分的变化日益频繁，我们经常要把多种网格细分方法相结合，或者为收集和分析不同的数据，在不同网格细分形状中进行切换。在本文中，我们回顾了如何将网格细分方法与对象和场地理空间模型相结合，还阐述了如何将动态网格切分法作为一个初始解决方案，实现城市内核的“智能”。关键词：大数据，传感器网络，智慧城市，空间网格切分。

Con frecuencia, las ciudades inteligentes dependen de vastas redes de sensores, tales como las cámaras de tráfico y controladores de ventilación. Tal circunstancia exige que repensemos los métodos de teselado espacial. En la medida en que éste se hace más dinámico, a menudo combinamos múltiples métodos de teselado y cambiamos sus formas para diferentes colecciones y análisis de datos. En este artículo, revisamos el modo como el teselado trabaja con el objeto y con los modelos geográficos espaciales de campo. Para lograr la “inteligencia” dentro de las ciudades, este artículo presenta el enfoque del teselado dinámico como la solución inicial. Palabras clave: big data, ciudad inteligente, red de sensores, teselado espacial.

Additional information

Funding

This work was funded by Mitacs, MITACS-IT09684.

Notes on contributors

Jin Xing

JIN XING is Lecturer in Geospatial Analysis in the School of Engineering, Newcastle University, Newcastle Upon Tyne, NE1 7RU, UK. E-mail: [email protected]. His research interests include smart cities, GIScience, remote sensing, and cyberGIS.

Renee Sieber

RENEE SIEBER is Associate Professor in the Department of Geography, McGill University, Montréal, QC, H3A 0B9, Canada. E-mail: [email protected]. She is best known for her research on public participation GIS/participatory GIS.

Stéphane Roche

STÉPHANE ROCHE is Professor at the Institut National de le Recherche Scientifique, Québec City, QC, G1K 9A9, Canada. E-mail: [email protected]. His expertise lies in GIScience, cartography, and land use decision making.