Yiqun Chen

An intelligent disaster decision support system for increasing the sustainability of transport networks

The increase in extreme weather events arising from climate change is posing serious threats to the sustainability of transport systems, creating the need for improved tools for decision support for more effectively managing natural disasters. There are numerous transport‐related decisions that are required during the response, recovery and preparedness stages of the disaster management cycle. This paper describes the development and application of the Intelligent Disaster Decision Support System (IDDSS), which provides a platform for integrating a vast range of road network, traffic, geographic, economic and meteorological data, as well as dynamic disaster and transport models. Initial applications to the response and planning for floods and fires are presented to illustrate some of its capabilities. The IDDSS can be used to improve disaster management, which in turn will increase the sustainability of transport networks.

A Free, Open-Source Tool for Identifying Urban Agglomerations using Point Data

Abstract This paper describes a software tool for identifying urban agglomerations in low-information settings. The framework outlined in this paper is designed to work using point data. Our tool and all required data are provided free and in open-source format. This paper describes the advantages and disadvantages of using point-based geographies in regional analysis, discusses the practical and ethical challenges of distinguishing urban from rural regions, details the function of our software, and directs the interested reader to the source code. The paper also examines the tools outputs for Sri Lanka and compares them with published United Nations urbanization figures. Our outputs indicate that Sri Lankas urban population is significantly undercounted in official statistics.

From IFC to 3D Tiles: An Integrated Open-Source Solution for Visualising BIMs on Cesium

The 3D Tiles specification, created by Cesium, is designed for streaming massive heterogeneous three-dimensional (3D) geospatial datasets online using WebGL technology. The program has prevailed in the WebGIS community due to its ability to visualise, interact, and style 3D objects for various scenarios, such as 3D cities, indoor environments, and point clouds. It offers a new opportunity to integrate Building Information Models (BIM) in the Industry Foundation Classes (IFC) data format with existing geospatial data in a 3D WebGIS platform with open-source implementation. As no open-source solution for converting IFC models into 3D Tiles for online visualization had yet been found, this paper explores feasible approaches and integrates a range of tools and libraries as an open-source solution for the community.

An Advanced Web API for Isochrones Calculation Using OpenStreetMap Data

This chapter demonstrates a software that finally makes urban reachability analysis free, open-source, and usable for non-technical urban analysts. We aim to provide researchers with a highly-parametric API (Application Programming Interface) for creating isochrones worldwide, meeting various scenario requirements with high accuracy. We start with OpenStreetMap road data that the software cleans by applying a sub-graph algorithm, removing isolated road links. This results in a fully-connected network for isochrones calculation, improving the web API stability. Then, a non-recursive breadth-first-search algorithm runs in parallel to generate isochrone links. The isochrones are then constructed using either link buffers or concave hulls to meet various accuracy requirements. The final outputs, including isochrones polygons, lines, and nodes with traverse distance attributes, can be exported in popular formats. The API supports thousands of isochrone calculations simultaneously, and is fully accessible online. The source code will also be provided for free for anyone to take and modify.

A free, open-source tool for identifying urban agglomerations using polygon data

This paper describes the function of a software tool for identifying urban agglomerations in low-information settings using free, open data. The framework outlined here is designed to work using polygon data. This paper describes the advantages and disadvantages of using polygon-based geographies in regional analysis, discusses the practical and ethical challenges of distinguishing urban from rural regions, and discusses the relevance of this tool in the analysis of global city regions. It also describes the logical structure of our polygon-based software tool and directs interested readers to the source code. We finally examine the agglomeration results for Sri Lanka and compare them with published urbanization figures. We conclude that there are very large disparities between our model’s outputs and the urbanization estimates from the United Nations and that our tools can be used as a less discretionary way to identify actual levels of urbanization. We hope that other analysts will continue to refine the progression toward a less discretionary model of identifying urban regions.

An ontology-based spatial data harmonisation for urban analytics

Abstract Data heterogeneity is one of the most challenging problems in urban data analytics. When obtained from various providers or custodians, datasets for the same domain themes may dramatically differ in formats due to many reasons such as historical legacies, changing definitions or standards across jurisdictions etc. It hinders urban analysts and researchers from understanding and using these data and makes results comparison and interpretation obscure. Ontology, usually created by domain experts, offers a comprehensive representation of knowledge including concepts, relations and properties in a domain. It defines the real world in abstract and offers a universal and stable schema for data harmonisation. This paper proposes a fast, extensible solution for eliminating data heterogeneity by using ontology. Starting from conceptualising domain knowledge to domain ontology, we discuss a two-level mapping mechanism which bonds the nexus between data and ontology using mapping rules. A semantic translation engine is also introduced to automate the data harmonisation process. A real case - urban density indicators computation - also demonstrates the usability of the proposed framework and the results show strong potentials for applying this method to broader urban analytics application scenarios.

Warnvave: Empowering the crowd to exchange emergency information

In recent years, a significant growth in access to smartphones and cellular data services has brought more opportunities to emergency management authorities in order to use crowdsourcing techniques for collecting valuable reports about each individual incident in short time.