combining spatial data benefits and applicator
TRANSCRIPT
AITPM2016_A_R_Ellison
Combining spatial data: benefits and applicationsModelling Workshop, AITPM 2016Sydney, AustraliaDr Adrian B. EllisonDr Richard B. Ellison
The University of SydneyPage #Background
Increasingly large sources of transport and land use dataBiggest benefit comes from combining several sourcesFor modelling, reduces reliance on assumptions
The University of SydneyPage #Background
Existing statistical methods are not well suitedBehavioural data (from GPS, smartcards, etc.) can be noisyNeed to isolate the impact of individuals behaviour from external factors
The University of SydneyPage #
Multilevel factors
The University of SydneyPage #Temporal and Spatial Identifiers (TSI)
The University of SydneyPage #
The University of SydneyPage #Temporal and Spatial Identifiers (TSI)
The University of SydneyPage #From driver behaviour to public transport user behaviour
The University of SydneyPage #From driver behaviour to public transport user behaviour
The University of SydneyPage #Application in transport models MetroScan-TI
The University of SydneyPage #Application in transport models MetroScan-TI
The University of SydneyPage #Application in transport models MetroScan-TI
The University of SydneyPage #Application in transport models MetroScan-TI
The University of SydneyPage #Software
Solution uses free and open source software
R Project (statistical software)Quantum GISPostgreSQL with PostGIS (database)OSRM (routing)
The University of SydneyPage #
Software
Open standards to make combining datasets easier and more robustBenefits from the largest combination of functionalityPackaged deployment possible with distributed and high performance computing
The University of SydneyPage #Combining spatial data: benefits and applicationsModelling Workshop, AITPM 2016Sydney, AustraliaDr Adrian B. [email protected]
Dr Richard B. [email protected]
The University of SydneyPage #