Research officer and scholar specialising in computational geography.
Based in the Centre for Computational Geography (CCG),
in the School of Geography (SoG)
at the University of Leeds (UoL),
Andy began working on a series of research projects from October 1997.
Much of this has involved developing and using enhanced research infrastructure and geographical
data processing, and
data visualisation technology.
Andy tutors students, mentors and supervises student led research projects, runs computer practical sessions, convenes learning modules and moderates assessment on the
Geographical Information Systems MSc and
Geography BA programmes. Andy also delivers training for the
Centre for Doctoral Training on Data Analytics & Society and for
Leeds Institute for Data Analytics partners.
Research Ethics Lead for the SoG, Andy is a member of the
Business, Environment and Social Sciences Research Ethics Committee
otherwise known at UoL as the AREA FREC.
Working with the SoG GeoInclusive Task Force, Andy is aiming to:
support functional diversity,
promote cultural diversity,
encourage inclusive practise,
decolonize knowledge, and
support people with less privilege and with exploited heritage more.
Andy has wide ranging geographical research interests and is:
deputy director of the CCG
- an interdisciplinary University centre founded in 1992 and originally led by Stan Openshaw; and,
a member of the four SoG research clusters:
The rest of this Web page is divided into 5 Sections about Andy's work:
- Aims and Objectives
- Primary Research Interests
- Software Development
- Research Projects
1. Aims and Objectives
- Help develop impartial advice, guidance and good practice documentation for research.
- Review and critique policy and promote
- Be inclusive, collaborative and scientific.
- Develop understanding, knowledge, skills and expertise for all to use.
- Ensure that research data is findable, accessible, interoperable and reusable
and promote the
FAIR Guiding Principles for scientific data management and stewardship.
- Advance a
geographical information science based approach to
mapping and understanding our world (particularly the immediate generational threats people and wildlife face, but also considering longer term resilience and sustainablility, and thriving not just surviving).
- Advocate the use and development of
open source software and code for scientific research and research infrastrucutre.
- Encourage and support work aiming to ease the
reproducibility of research results.
- Encourage the use and development of
- Develop and rekindle interdisciplinary research collaborations and contribute to a wide range of scientific endeavor.
Help with the recommissioning of the NERC Environmental Data Service initially by leading a research fellowship aiming to advise on this process.
Develop a partnership between the SoG and
Meanwood Valley Urban Farm.
Develop a Digital Twin Earth and Solar System and put it to good use.
Revisit past research work and try to reproduce research results and make it easier for others to do so, and create updated outputs along the same lines and engage in new research that may or may not lead on from these.
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2. Primary Research Interests
Aggregate data and
(geographically weighted) statistics
environmental degradation and
Land use, land use policy, land use patterns, land use change impacts, land use capability, and land use suitability analysis
Changes and inequalities in: health, wealth, income and access (to places, information, services and welfare)
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4. Software Development
I am developing well tested and documented Java libraries using
ccg-io: input/output utilities (including an effective way to cache data).
ccg-math: a range of mathematical functionality including fixed point and arbitrary precision arithmetic and computing with matrices.
ccg-grids: for storing and processing raster data.
ccg-v2d: for storing and processing 2D vector geometry.
ccg-v3d: for storing and processing 3D vector geometry.
ccg-gws: for Geographically Weighted Statistics.
ccg-chart: for generating charts from data.
ccg-text: for text data processing.
ccg-ukpc: for checking if a sequence of characters might be viable UK unit, sector, district or area postcode and for returning the type (unit/sector/district)
Processing specific data sets:
ccg-data-ukpc: for UK Office for National Statistics Postcode Directory and UK National Statistics Postcode Lookup data processing.
ccg-data-stats19: for STATS19 data processing.
ccg-data-shbe: for UK Single Housing Benefit Extract data processing.
ccg-data-census: for UK Human population Census data processing.
ccg-data-waas: for UK Office for National Statistics Wealth and Assets Survey data processing.
ccg-data-lr: for UK Land Registry corporate land and property ownership data processing.
ccg-data-us: for Understanding Society data processing.
ccg-data-elsa: for English Longitudinal Study of Ageing data processing.
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