Accessibility Analysis and Modeling in Public Transport Networks - A Raster based Approach

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The document summarizes research on modeling accessibility in public transportation networks using a raster-based approach. The research aimed to create an accessibility indicator for jobs via public transit that had low data requirements to allow transfer to other regions. The study area was the capital region of Denmark. Accessibility was modeled using land use, transportation, and temporal components. The model calculated cost distances from population and job centers using rasterized transportation network data. Results showed variability in accessibility scores and generally aligned with commuting statistics. The raster approach allowed fast calculation with low data needs but did not fully account for travel time or mode changes.

Accessibility Analysis and Modeling in Public Transport Networks - A Raster based Approach Morten Fuglsang 1,2 , Henning Sten Hansen 2 & Bern Münier 1 1 Aarhus University – National Environmental research institute 2 Aalborg University Copenhagen

Structure of presentation Prensentation of topic Introduction to the case region The applied definition of accessibility The conducted modeling Results Evaluation

Project topic For the Pashmina project, CA based land use change modelling is to be conducted using the LUCIA Cellular autometa model. The project outlines policy scenarios for paradigme shifts in transportation for the next 40 year period. Modeling is to be conducted in Denmark and in up to two other European cases.

Project topic One of the ongoing tasks is to create a indicator of accessibility to jobs through public transportation. In order for it to be transferable, the data requirements was to be as simple as possible, to facilitate easy transfere to the other European regions.

Introduction ‘ Outskirt Denmark’ is a popular theme in Danish politics, describing regions with : Declining population Poor number og jobs Low service level in terms of schools, hospital services and public transportation

Study area The capitol region of Denmark 9200 km2 area coverage Large regional differences in terms of jobs and transportation services

Defining accessibility Components of accessibility: Land use component Transportation component Temporal component Individual component (Geurs, K. T & van Wee, B. 2004) We use three of the four components, and a gravity based accessibility measurement.

Data inputs Data used for the modeling: Road dataset Trainlines and stops Buslines and stops Metrolines and stops Centers with population and number of jobs

Cost surface creation Average tavel-speeds was appended to the vector data Out of network travel was set to walking pace

Cost surface creation 2 Data was rasterized to 100m resulution, and the differenet rasters where combined Finally the travelspeed was recalculated to CCT values Juliao, R. P (1999)

GIS modeling Using python, a model was created, that combines the data with the information from the centers, and the coast surface (Coffey, W & Shearmur R. G 2001)

GIS modeling The model creates a cost distance calculation for each center – calculating the centers contribution to the overall indicator. The center contributions are the summarized into one output layer

Result post processing Result showed som inconsitency in two areas with high low coverage and few stations/stops Furthermore the effect of the constraints was removed for the result

Results 285 centers was included in the calculation. High variability in terms of result scores

Results Based upon upon the entire dataset, mean accessibility was calculated Result classified into +/- 1 and 2 std. deviation.

Validation Municipality average was calculated based on the clssification scores Compared to commuting statistics.

Validation 3 The cluster analysis highlights the regions where both accessibility and commuting is generaly low.

Strengs and weaknesses Fast calculation time based on raster math Low data requirements Describes commuting trends In line with commuting statistics Depiction of time in the model does not corrospond to traveltime Change of transportation mode and wait time is not modeled Region should and will be subdivided.

Conclusion Vector methods are much more precise, however this aproach was designed with low data requirements as main goal. The model illustrates the regional differences in service availability and align with commuting statistics Future work will focus on incorporating a more precise prediction of time to the raster based method.

Thank you for your attention… [email_address]

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Smart Cities: New Science for the CitiesBeniamino Murgante

The evolution of spatial analysis and modeling in decision processesBeniamino Murgante

This document discusses the evolution of spatial analysis and modeling in decision processes. It describes how spatial analysis has progressed from early tools like spatial autocorrelation statistics to modern techniques using big data and volunteered geographic information. Examples are provided of using local spatial statistics, satellite imagery, and crowdsourced maps to analyze urban growth and quantify impacts of natural disasters. Overall, the document outlines the increasing role of spatial analysis and modeling in decision-making as tools and data availability have advanced.

Smart City or Urban Science?Beniamino Murgante

Involving citizens in smart energy approaches: the experience of an energy pa...Beniamino Murgante

Programmazione per la governance territoriale in tema di tutela della biodive...Beniamino Murgante

Involving Citizens in a Participation Process for Increasing WalkabilityBeniamino Murgante

Presentation of ICCSA 2019 at the University of Saint petersburg Beniamino Murgante

The document discusses plans to hold the 2019 International Conference on Computational Science and Its Applications (ICCSA 2019) in Saint Petersburg, Russia from June 24-27, 2019. Saint Petersburg is a historic city that was formerly the capital of the Russian Empire and is now a cultural capital of Russia, with many beautiful suburbs and metro stations located in a UNESCO World Heritage Site downtown area.

RISCHIO TERRITORIALE NEL GOVERNO DEL TERRITORIO: Ricerca e formazione nelle s...Beniamino Murgante

Presentation of ICCSA 2017 at the University of triesteBeniamino Murgante

The document discusses the 17th International Conference on Computational Science and Its Applications (ICCSA 2017) that will take place from July 3-6, 2017 in Trieste, Italy. It provides background information on the University of Trieste, including its research centers, rankings, international partnerships, and spin-offs. The conference will bring together researchers in computational science and related fields and showcase the work happening at the University of Trieste and surrounding institutions in the Trieste area.

GEOGRAPHIC INFORMATION – NEED TO KNOW (GI-N2K) Towards a more demand-driven g...Beniamino Murgante

Focussing Energy Consumers’ Behaviour Change towards Energy Efficiency and Lo...Beniamino Murgante

This document discusses a project aimed at improving policy instruments to increase energy efficiency in buildings. The project will focus on three pillars: supplementary services from authorities, innovative cooperation models like public-private partnerships, and smart technologies. It will involve partners from several regions developing action plans over three years to test new policies and share results. The goal is to reduce energy consumption and emissions from buildings, which account for 40% of energy usage and 36% of emissions in the EU.

Socio-Economic Planning profiles: Sciences VS Daily activities in public sector Beniamino Murgante

This document outlines a training program on geographic information systems (GIS) and spatial statistics. The program consists of 11 modules that cover fundamentals of GIS, basics of statistics, socio-economic indicators, demographic indicators, introduction to geostatistics, spatial statistics, and spatial regression. Each module includes multiple lectures on related topics, techniques, and software. The overall aim is to provide education and training to develop a more demand-driven geospatial workforce.

GEOGRAPHIC INFORMATION – NEED TO KNOW (GI-N2K) Towards a more demand-driven g...Beniamino Murgante

Garden in motion. An experience of citizens involvement in public space regen...Beniamino Murgante

Planning and Smartness: the true challengeBeniamino Murgante

1) Beniamino Murgante presented at the "Limits of Formal Planning in Managing the Urban Development" conference in Lodz, Poland on April 10-12, 2014. 2) The presentation discussed the challenges of formal planning and the need for "smartness" in urban development given rapid urbanization and new technologies. 3) Murgante argued that smart cities require connections between sensors, open data, and governance to effectively manage and plan urban development.

GeoSDI: una piattaforma social di dati geografici basata sui principi di INSP...Beniamino Murgante

This document summarizes the activities of the geoSDI laboratory. It discusses how geoSDI started in 2007 as a center of competence for spatial data infrastructures within the Italian government. It has since developed open source geospatial web platforms and provided support for emergency response around the world. Key projects include developing Geo-Platform, an open source framework for building INSPIRE-compliant SDIs, and providing geospatial support during disasters in Italy, Haiti, Chile and elsewhere. GeoSDI continues to develop new widgets and functionality for Geo-Platform while also implementing SDI systems for various government and international organization clients.

Murgante smart energyBeniamino Murgante

The document summarizes a presentation given by Beniamino Murgante at the COST ACTION TU1104 - Smart Energy Regions conference held on November 18-19, 2013 in Rome. The presentation was titled "Cities and Smartness: a critical analysis of opportunities and risks" and discussed the concept of smart cities, including definitions, technologies used such as sensors and open data, and both opportunities and risks of making cities smarter.

Informazione Geografica, Città, Smartness Beniamino Murgante

Tecnologie, Territorio, SmartnessBeniamino Murgante

Fino alla fine degli anni '80 un urbanista che cercava di supportare dei ragionamenti di piano con l'informatica riusciva ad ottenere, nel migliore dei casi, qualche dato statistico sulla popolazione. Con il trascorrere degli anni si è assistito ad un incremento dell'utilizzo delle tecnologie per la costruzione dei quadri conoscitivi a supporto del processo di piano, fino a raggiungere l'attuale Information Explosion Era. Il contenuto dell'intervento si baserà su aspetti teorici ed applicativi a partire dall'esperienza di Ian McHarg fino all'ultima "moda" delle Smart Cities. Introduzione Andreina Maahsen-Milan Università di Bologna Tecnologie, Territorio, Smartness Beniamino Murgante Università della Basilicata Facoltà Ingegneria Edile di Ravenna - Università di Bologna Via Tombesi dall'Ova 55, 48121 Ravenna