CRCSI Scholarship and Project Students

Mohsen Azadbakht

Processing LiDAR Waveforms to Extract Features Accurately

Mohsen Azadbakht
University
University of Melbourne
Supervisor (Academic)
Dr Joe Leach, Dr Chunsun Zhang & Prof Clive Fraser, University of Melbourne
Supervisor (Industry)
Rohan Potter, AAM
Projects

P2.02 - Feature Extraction

Jannah Baker

Spatial Interactions Between Chronic Diseases, Risk Factor Exploration and Effects of Health Screening

Jannah Baker Conf2012
University
Queensland University of Technology
Supervisor (Academic)
Prof Kerrie Mengersen, QUT
Supervisor (Industry)
A/Prof Peter Baade, Cancer Council Qld
Projects

P4.42 - Spatial Modelling ... [watch Jannah's video]

Thesis Abstract

Postdoctoral Fellow for the CMCRC, NSW Ministry of Health

Michael Borck

Feature Extraction from Multi-modal Mobile Mapping Data

michael borck
University
Curtin University
Supervisor (Academic)
Prof Geoff West & Prof Tele Tan, Curtin University
Supervisor (Industry)
David Elliot & Aaron Thorn, Landgate
Projects

P2.01 - Terrestrial Mapping

Nic Donnelly

Integration of Interferometric Synthetic Aperture Radar into a National Geodectic Datum

Nic Donnelly
University
University of New South Wales
Supervisor (Academic)
Prof Chris Rizos, UNSW
Projects

P1.02 - Next Generation Datum

Employment
Nic Donnelly is the Technical Manager Geodesy, LINZ and is supported by UNSW for his PhD in the Next Generation Datum project (P1.02). Recently Nic’s work relating to Earthquake changes to land boundaries provided a critical part of the technical foundation for a new Bill currently sitting within the New Zealand Parliament. The geodetic modelling technique used in this research is a world first in application to cadastral data over large areas.

Luis Elneser

Industry Expectations for Using a Real-Time, Australia-Wide, Multi-GNSS, PPP-RTK Service for Dynamic Applications

IMG 4745
University
RMIT University
Supervisor (Academic)
Dr Suelynn Choy, RMIT University
Supervisor (Industry)
James Millner, Position Partners
Projects

Further information about Luis’ research can be found here.

Employment
Luis Elneser is a Site and Project Services Consultant with 43pl member Position Partners. His research is focused on comparing and validating RTK with the PPP-RTK method being used in the Positioning Program. Luis is supported by RMIT.

Ben Fitzpatrick

Experimental Designs and Bayesian Spatiotemporal Models for Carbon in Farmscapes

Ben Fitzpatrick Conf2012
University
University of New England
Supervisor (Academic)
Profs Kerrie Mengersen & Peter Grace, QUT & David Lamb, UNE
Projects

Further information about Ben’s research can be found here:

Employment
Ben Fitzpatrick is located at QUT and works on the Biomass Business project (P4.18) on research into experimental designs and Bayesian spatiotemporal models for carbon in farmscapes. He is also a Research Associate in the School of Mathematical Sciences. Ben’s research is in the area of Applied Statistics leveraging rich ensembles of environmental data layers to aid the interpolation of sparse, ground truthed observations. Ben is open to discussions on point referenced, spatial observations to interpolate with the aid of high resolution observations of other related things. His interests lay with points on a map to predict full cover rasters or smooth surfaces. Ben has opensource code to share and is keen to pursue case studies to analyse and write up as journal articles with interested co-authors.

Teuku Aulia Geumpana

Processing LiDAR Waveforms to Extract Features Accurately

TeukuAG
University
University of New South Wales
Supervisor (Academic)
Professor Fethi Rabhi
Supervisor (Industry)
Nathan Quadros
Projects

Information priority model for GIS-based mobile cloud application in disaster emergency response

Employment
Teuku Aulia Geumpana is located at UNSW and is working on the information priority model for GIS-based mobile cloud application in disaster emergency response. He recently the joined the CRCSI student group and is in the early stage of his PhD research which supports the work of Rapid Spatial Analytics.

Paul Goodhue

Crowd sourcing validation for the Biomass Business 2 Project

PaulGoodhue Photo
University
University of Canterbury
Supervisor (Industry)
Dr Robin Dobos
Projects

Further information about Paul’s research can be found here:

 

Employment
Paul Goodhue, located at the University of Canterbury is working on the Biomass Business 2 project (P4.18). Paul’s research centres on validating the crowdsourcing component of data gathered from the field through agricultural consultants and farmers. His work is integrated into Spatial Infrastructures (Program 3) to improve the trust of crowdsourced geographic information. Paul is interested in crowdsourcing walking and biking track information through apps (android and web) that he has developed as part of his PhD. Paul will use this information to analyse the ability of a conceptualised crowdsourcing model to improve the trust of crowdsourced geographic information.

Elizabeth-Kate Gulland

Improving Usability of Online Health Geovisualisation Tools

WA Curtin E K Gulland
University
Curtin University
Supervisor (Academic)
Em Prof Geoff West & Dr Simon Moncrieff, Curtin University
Projects

Further information about E-K’s research can be found here:

 

Employment
E-K Gulland is supported by Curtin University. Her research crosses two program – Spatial Infrastructures (P3.01) and Health (P4.41) and examines the improvement of usability of online health geovisualisation tools.

Sam Hislop

Processing LiDAR Waveforms to Extract Features Accurately

SamH
University
RMIT University
Supervisor (Academic)
Simon Jones and Mariela Soto-Berelov
Supervisor (Industry)
Andrew Haywood
Projects

Sam recently commenced his PhD at RMIT as part of Project 4.104 — LandFor: Landsat for Forests.

Further information about Sam’s research can be found here:

 

Employment
Sam Hislop is supported by RMIT as part of the LandFor: Landsat for Forests project (P.4.101). The project team is researching methods to take advantage of the extensive archive of Landsat satellite imagery to model and map disturbance in Victorian forests. By creating an ‘image stack’ from almost 30 years of images, the team can analyse change as a function of time on a pixel by pixel basis. Using a combination of machine learning and user trained multiple lines of evidence, large area disturbance histories will be modelled. Sam’s has government experience in spatial mapping in emergency management.
Thesis Abstract

Sam Hislop timeseries

Daniel Hogg

Modelling Spatial Variations in Natural Disaster Impact

NZ Canterbury DanielHogg
University
University of Canterbury
Supervisor (Academic)
Prof Simon Kingham & Dr Thomas Wilson, University of Canterbury
Supervisor (Industry)
Prof Michael Ardagh, Canterbury District Health Board
Projects

P4.45 - Spatial Variations in Natural Disasters

Thesis Abstract

Daniel Hogg and University of Canterbury colleagues Simon Kingham, Thomas M. Wilson, Edward Griffin, and Michael Ardagh published the paper Geographic variation of clinically diagnosed mood and anxiety disorders in Christchurch after the 2010/11 earthquakes in October 2014.

Abstract

The 22 February 2011 Christchurch earthquake killed 185 people, injured over 8000, damaged over 100 000 buildings, and on-going aftershocks maintained high anxiety levels.

This paper examines the dose of exposure effect of earthquake damage assessments, earthquake intensity measures, liquefaction and lateral spreading on mood and anxiety disorders in Christchurch after this event. We hypothesise that such disorders are more likely to develop in people who have experienced greater exposure to these impacts within their neighbourhood than others who have been less exposed, but also live in the city. For this purpose, almost all clinically diagnosed incident and relapsed cases in Christchurch in a 12 month period after the 2011 earthquake were analysed. Spatio-temporal cluster analysis shows that people living in the widely affected central and eastern parts after the 2010/11 earthquakes have a 23% higher risk of developing a mood or anxiety disorder than people living in other parts of the city. Generally, mood and anxiety-related disorders increase with closer proximity to damage from liquefaction and moderate to major lateral spreading, as well as areas that are more likely to suffer from damage in future earthquakes.

The full article can be downloaded here.

Hamish McNair

Integrating crowdsourced data/info/knowledge into supply chains processes.

hdm40 1
University
University of Cantebury
Supervisor (Industry)
Mark Nichols, Trimble
Projects

Further information about Hamish’s research can be found here:

Employment
Hamish McNair is located at the University of Canterbury and supported by 43pl member Trimble. He is working on the Supply Chains project (P3.02). Hamish’s research centres on trusting crowdsourced spatial information throughout a spatial data supply chain. Hamish is investigating how crowdsourcing can be better integrated into processes that utilise spatial information. This research seeks to engage people in more than simply the collection of data so that local knowledge can more directly influence decision-making processes. His current focus is on incorporating local perspective in planning processes by spatially arranging users’ observations and opinions on cycle infrastructure performance.

John Lewis

Enhancing information systems to support the care of colorectal cancer survivors by GP led primary care services

JohnLewis
University
University of New South Wales
Supervisor (Academic)
Teng Siaw Liaw
Supervisor (Industry)
Pradeep Ray
Projects

Enhancing information systems to support the care of colorectal cancer survivors by GP led primary care services

Employment
John Lewis is located at UNSW and recently joined the CRCSI student group. He is working on enhancing information systems to support the care of colorectal cancer survivors by GP led primary care services.

Charity Mundava

Biomass Assessment Tools to Assist Grazing Management in the Kimberley Region of Western Australia

Charity Mundava
University
Curtin University
Supervisor (Academic)
Drs Rob Corner & Petra Helmholz, Curtin University
Supervisor (Industry)
Richard Stovold, Dr Brendon McAtee & Norman Santich, Landgate
Projects

P4.12 - Biomass Business ... [watch Charity's video]

Levi Mutambo

Spatial Data Infrastructure and Volunteered Geographic Information

levimutambo 145x145
University
University of Canterbury
Projects

Further information about Levi’s research can be found here:

Employment
Levi Mutambo, located at the University of Canterbury is working on the Supply Chains project (P3.02) to explore the potential of crowdsourcing and open source technologies in addressing the challenges of government-driven Spatial Data Infrastructures (SDI) in resource constrained contexts. The global spread of mobile devices with mapping capabilities and the maturing of open source software for SDI development have opened the door of opportunity to research on the possibility of crowdsourcing an SDI in order to reduce costs, speed up delivery, and increase access to location information for better decision-making in regional development. Levi’s research centres on spatial data infrastructure and volunteered geographic information. His current focus will see farmers in Zambia supply real-time crop harvesting data into a purpose built app using smartphones donated by Huawei Technologies Australia. Levi’s proof of concept has been developed and is now ready for field testing. Levi's envisaged research outcomes are an open source framework for a crowd-driven SDI which will include a mobile application and web portal to support the crowd in collecting and managing location information.

Josh Neville

Meeting Housing Demand in Christchurch within the Existing Urban Footprint

josh square compressed DSC 9300 1
University
University of Canterbury
Supervisor (Academic)
Prof Simon Kingham & Prof Eric Pawson, University of Canterbury
Projects

P4.51 - Greening the Greyfields

Trung Nguyen

Trung Nguyen
University
RMIT
Supervisor (Academic)
Simon Jones and Dr Mariela Soto-Berelov, RMIT; Dr Andrew Haywood, EU REDD Facility, EFI
Projects

Further information about Trung’s research can be found here:

Employment
Trung Nguyen is supported by RMIT and is part of the LandFor: Landsat for Forests project (P.4.101). His research is using the Landsat satellite archive and time series analysis to capture biomass dynamics across Victoria. Trung’s work revolves around using time series disturbance mapping and single date forest inventory plot data to capture forest biomass dynamics in forests. He is interested in connecting with land managers and academics interested in forest monitoring using remote sensing (RS) techniques, along with users of time series RS to map and analyse disturbance at the landscape scale.

Richard Palmer

Automated Generalised Methods for the Extraction and Analysis of High Level Information From Mobile Mapping Data

rich palmer
University
Curtin University
Supervisor (Academic)
Em Prof Geoff West & A/Prof Tele Tan, Curtin University
Supervisor (Industry)
David Elliot & Aaron Thorn, Landgate
Projects

Further information about Richard’s research can be found here:


Employment
Richard Palmer is supported by Curtin University on the CliniFace project (P4.406). His specific research relates to the Automated generalised methods for the extraction and analysis of high level information from mobile mapping data.

Tristan Reed

Semantic Search and Discovery of Web-Based Services

Tristen Reed compressed
University
Curtin University
Supervisor (Academic)
Em Prof Geoff West, Dr Simon Moncrieff & Dr David McMeekin, Curtin University
Supervisor (Industry)
Mike Horton, NGIS & Dr Simon Cox, CSIRO
Projects

Further information about Tristan’s research can be found here:

Employment
Tristan Reed is located at Curtin University and works on the Spatial Infrastructures Program (P3.01) with research into the Semantic search and discovery of web-based services. He is supported by 43pl member NGIS. Tristan’s proof of concept is currently being developed.

Patrizia Russo

Understanding Barriers, Bottlenecks and Opportunities for Adoption of Spatial Information Tools in Land use Planning in Australia and New Zealand: A Visual Analytics Usability Approach

Vic UMelb Patrizia Russo
University
University of Melbourne
Supervisor (Academic)
A/Prof Christopher Pettit, University of Melbourne
Supervisor (Industry)
TBC
Projects

P4.53 - Adoption of SI Tools in Planning

Thesis Abstract

Patrizia Russo and her colleagues Maria Francesca Costabile, Rosa Lanzilotti and Christopher J. Pettit published the work Usability of Planning Support Systems: An Evaluation Framework in 2014.

Abstract

Previous research on Planning Support Systems (PSS) showed that low usability of these computer-based tools is one of the reasons why they are not widely used by planning professionals. Few studies for evaluating PSS usability are performed, possibly because developers do not regard it as their task, do not have enough skills to conduct them, and have not been stimulated so far to appreciate their value. In this chapter, a framework is described that aims at guiding usability evaluation of PSS; it is developed on the basis of a more general usability evaluation framework.

The current version of the framework has been applied to evaluate three PSS by performing a test with a small group of land use planners. Results of this user test are discussed, also providing some recommendations for the design of PSS, specifically those addressing Land Suitability Analysis (LSA), capable to generate a positive user experience.

The full article can be downloaded here.

 

Azeem Sadiq

Investigating governance along supply chains and concentrating on provenance

Screen Shot 2014 07 31 at 3 11 44 pm
University
Curtin University
Supervisor (Academic)
Em Prof Geoff West, Dr David McMeekin, Dr Simon Moncrieff and Dr Lesley Arnold
Supervisor (Industry)
Ed Garvin, Omnilink
Projects

Further information about Azeem’s research can be found here:

Employment
Azeem Sadiq is located at Curtin University and supported by 43pl member Omnilink. His research is focused on investigating governance along supply chains and concentrating on provenance in the Spatial Infrastructures Program (P3.02).

Jeremy Siao Him Fa

Federated Data Models

Jeremy Saio compressed
University
Curtin University
Supervisor (Academic)
Em Prof Geoff West, Dr David McMeekin & Dr Simon Moncrieff, Curtin University
Supervisor (Industry)
Sonny Tham, Amristar & Dr Simon Cox, CSIRO
Projects

Further information about Jeremy’s research can be found here: 

Employment
Jeremy Siao Him Fa is located at Curtin University and supported by 43pl member Amristar. He works on the Spatial Infrastructures research (P3.01) and focuses on federated data models. Jeremy’s proof of concept is currently being developed.

Chet Bing Tan

Automated Orchestration of Web Services Using Semantic Web Technologies

chet
University
Curtin University
Supervisor (Academic)
Em Prof Geoff West, Dr David McMeekin & Dr Simon Moncrieff, Curtin University
Projects

Further information about Chet’s research can be found here:

Employment
Chet Bing Tan is supported by Curtin University and works within the Spatial Infrastructures Program (P3.01). His research is focused on Automated orchestration of web services using semantic web technologies.

Ahmad Ridhwanuddin (Nuddin) Tengku

Initiating the Development of a Test Track for Positioning System Validation and Certification

Nuddin Tengku Conf2012
University
University of Melbourne
Supervisor (Academic)
Dr Allison Kealy, University of Melbourne & Dr Phil Collier, CRCSI
Supervisor (Industry)
Simon Fuller, ThinkSpatial
Projects

Further information about Nuddin’s research can be found here: 

Employment
Nuddin Tengku is located at Melbourne University and is supported by 43pl member ThinkSpatial. His research is focused on Initiating the development of a test track for positioning system validation and certification within the Positioning Program (P1.04). Nuddin is interested in connecting with spatial and engineering consultants to learn more about consulting operations and to seek potential employment.

Premalatha (Latha) Varadharajulu

Spatial Data Supply Chain Modelling in Australia and New Zealand

Premalatha Varadharajulu compressed
University
Curtin University
Supervisor (Academic)
Em Prof Geoff West, Dr David McMeekin, Dr Simon Moncrieff & Dr Lesley Arnold, Curtin University
Supervisor (Industry)
Landgate
Projects

Further information about Latha’s research can be found here:

 

Employment
Latha Varadharajulu is located at Curtin University and supported by Landgate. Her research focus is Spatial data supply chain modelling in Australia and New Zealand through the Spatial Infrastructures Program (P3.02). Earlier this year, Latha received the Best Student Paper Award presented to the 2nd International Conference on Geographical Information Systems Theory, Application and Management, held in Rome, Italy. Latha’s proof of concept has been developed and is being tested by Landgate.

Yongchao Wang

QZSS/BDS Precise Orbit Determination Using Triple Frequency Code and Phase Measurements

Qld QUT Yongchao Wang
University
Queensland University of Technology
Supervisor (Academic)
Prof Yanming Feng, QUT & Dr John Hayes, QUT
Supervisor (Industry)
TBC

Phil Wilkes

Scale Variance as Applied to Woody Attribution of Eucalypt Forests

Phil Wilkes Conf2012
University
RMIT University
Supervisor (Academic)
Simon Jones, RMIT
Supervisor (Industry)
Andrew Haywood, DEPI Vic
Projects

P2.07 - Woody Vegetation

Arjan Wilkie

Processing LiDAR Waveforms to Extract Features Accurately

Arjan
University
University of New England
Supervisor (Academic)
Associate Prof Brian Wilson
Supervisor (Industry)
Greg Summerell
Projects

P4.103Improved measurement and estimation of Biomass and Soil Carbon in diverse landscapes using high-resolution remote-sensing

Employment
Arjan Wilkie is located at UNE and is working on the just started Improved high-resolution carbon accounting project (P4.103) and the improved measurement and estimation of Biomass and Soil Carbon in diverse landscapes using high-resolution remote sensing.

Cynthia (Qian) Yu

Semantic and syntactic methods to match real world data to models for change detection and recognition

Qian Yu
University
Curtin University
Supervisor (Academic)
Dr Petra Helmholtz, Dr David Belton & Em Prof Geoff West, Curtin University
Supervisor (Industry)
Tom Werner, AAM
Projects

P2.01 - Mobile Mapping

Thesis Abstract

Cynthia Yu along with Curtin University colleagues Petra Helmholz, David Belton and Geoff West, published the paper Grammer-based automatic 3D model reconstruction from terrestrial laser scanning data in the May issue of The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-4, 2014.

Abstract

The automatic reconstruction of 3D buildings has been an important research topic during the last years. In this paper, a novel method is proposed to automatically reconstruct the 3D building models from segmented data based on pre-defined formal grammar and rules.

Such segmented data can be extracted e.g. from terrestrial or mobile laser scanning devices. Two steps are considered in detail. The first step is to transform the segmented data into 3D shapes, for instance using the DXF (Drawing Exchange Format) format which is a CAD data file format used for data interchange between AutoCAD and other program. Second, we develop a formal grammar to describe the building model structure and integrate the pre-defined grammars into the reconstruction process. Depending on the different segmented data, the selected grammar and rules are applied to drive the reconstruction process in an automatic manner. Compared with other existing approaches, our proposed method allows the model reconstruction directly from 3D shapes and takes the whole building into account.

The full article can be downloaded here.

Feiyan Yu

Automatic data conflation using semantic web technologies

Feiyan Yu
University
Curtin University
Supervisor (Academic)
Em Prof Geoff West, Curtin University
Supervisor (Industry)
Ed Garvin, Omnilink
Projects

Further information about Feiyan’s research can be found here:

 

Employment
Feiyan Yu is located at Curtin University and supported by Omnilink. Her research, Automatic data conflation using semantic web technologies, supports the Spatial Infrastructures Program (P3.02).

Peiyuan Zhou

Lonospheric Delay Variance Modelling

NSW UNSW Peiyuan Zhou
University
University of NSW
Supervisor (Academic)
Dr Jinling Wang, University of NSW
Projects

P1.01 - Precise Positioning

Employment
Peiyuan Zhou is located at UNSW and works on Precise Positioning (P1.01) and the lonospheric Delay Variance Modelling. His research will support the Positioning Program.