Control of spatial discretisation in coastal oil spill modelling

Article

Li, Y. 2007. Control of spatial discretisation in coastal oil spill modelling. International Journal of Applied Earth Observation and Geoinformation. 9 (4), pp. 392-402.
AuthorsLi, Y.
Abstract

Spatial discretisation plays an important role in many numerical environmental models. This paper studies the control of spatial discretisation in coastal oil spill modelling with a view to assure the quality of modelling outputs for given spatial data inputs. Spatial data analysis techniques are effective for investigating and improving the spatial discretisation in different phases of the modelling. Proposed methods are implemented and tested with experimental models. A new “Automatic Search” method based on GIS zone design principles is shown to significantly improve discretisation of bathymetric data and hydrodynamic modelling outputs. The concepts and methods developed in the study are expected to have general relevance for a range of applications in numerical environmental modelling.

KeywordsZone design; Discretisation; Spatial data quality; Coastal oil spill modelling
JournalInternational Journal of Applied Earth Observation and Geoinformation
Journal citation9 (4), pp. 392-402
ISSN0303-2434
Year2007
Accepted author manuscript
License
CC BY-ND
Web address (URL)http://hdl.handle.net/10552 /330
Publication dates
PrintDec 2007
Publication process dates
Deposited14 Oct 2009
Additional information

Citation:
Li, Y. (2007) ‘Control of spatial discretisation in coastal oil spill modelling’ International Journal of Applied Earth Observation and Geoinformation 9 (4) 392-402.

Permalink -

https://repository.uel.ac.uk/item/865y1

Log in to edit

Download files

Accepted author manuscript
Li, Y.(2007) IJAEOG 9 (4) 392-402.pdf
License: CC BY-ND

  • 186
    total views
  • 257
    total downloads
  • 3
    views this month
  • 2
    downloads this month

Export as

Related outputs

AI-Enhanced Prediction of Multi Organ Failure in COVID-19 Patients
Rajakaruna, I., Amirhosseini, M. H., Li, Y. and Arachcillage, D. J. 2024. AI-Enhanced Prediction of Multi Organ Failure in COVID-19 Patients. IS'24: 12th IEEE International Conference on Intelligent Systems. Varna, Bulgaria 29 - 31 Aug 2024 IEEE. https://doi.org/10.1109/IS61756.2024.10705181
What Goes Up……: modelling the Bitcoin rollercoaster ride
Li, Y. 2024. What Goes Up……: modelling the Bitcoin rollercoaster ride. ELEKTRO 2024: 15th International Conference. Zakopane, Poland 20 - 22 May 2024 IEEE. https://doi.org/10.1109/ELEKTRO60337.2024.10557119
Credit Rating Prediction Using Different Machine Learning Techniques. International
Aiyegbeni, G., Li, Y., Annan, J. and Adebayo, F. 2023. Credit Rating Prediction Using Different Machine Learning Techniques. International. International Journal of Data Science and Advanced Analytics. 5 (5), pp. 219-238.
Improving data quality assessment of connected vehicles data with machine learning and statistical methods
Wall, J., Wondie, M. and Li, Y. 2022. Improving data quality assessment of connected vehicles data with machine learning and statistical methods. Pan African Conference on Artifical Intelligence 2022. 04 - 05 Oct 2022
Evidencing the impacts of the Olympic Games: The view from London 2012
Brimicombe, A. and Li, Y. 2020. Evidencing the impacts of the Olympic Games: The view from London 2012. in: Neri, M. (ed.) Evaluating the Local Impacts of the Rio Olympics Routledge.
A New Variable for Spatial Accessibility Measurement in Social Infrastructure Planning
Li, Y. and Brimicombe, A. 2011. A New Variable for Spatial Accessibility Measurement in Social Infrastructure Planning. in: Proceedings of the 11th International Conference on GeoComputation London University College London.
A New Approach on Rapid Appraisal of Green Roof Potential in Urban Area
Li, Y. and Brimicombe, A. 2015. A New Approach on Rapid Appraisal of Green Roof Potential in Urban Area. LIDAR Magazine. 5 (5), pp. 55-57.
Measuring and assessing the impacts of London 2012
Li, Y. 2015. Measuring and assessing the impacts of London 2012. in: Poynter, Gavin, Viehoff, Valerie and Li, Yang (ed.) The London Olympics and Urban Development: The Mega-Event City Abingdon, Oxon. Routledge. pp. 35-47
Spatial Analysis for Equitable Accessibility in Social Infrastructure Planning
Li, Y. 2016. Spatial Analysis for Equitable Accessibility in Social Infrastructure Planning. in: Timmermans, Harry (ed.) Design & Decision Support Systems in Architecture and Urban Planning Eindhoven University of Technology.
Mobile Geographic Information Systems
Li, Y. and Brimicombe, A. 2012. Mobile Geographic Information Systems. in: Chen, Ruizhi (ed.) Ubiquitous Positioning and Mobile Location-Based Services in Smart Phones IGI Global. pp. 230-253
Road traffic accident hotspot identification using modified Voronoi Process
Ladi, S., Wijeyesekera, D.Chitral, Brimicombe, A. and Li, Y. 2009. Road traffic accident hotspot identification using modified Voronoi Process. Proceedings of Advances in Computing and Technology. (AC&T) The School of Computing and Technology 4th Annual Conference University of East London pp. 189-198
Spatial Discretisation Technology in Coastal Oil Spill Modelling
Li, Y. 2008. Spatial Discretisation Technology in Coastal Oil Spill Modelling. Proceedings of Advances in Computing and Technology. (AC&T) The School of Computing and Technology 3rd Annual Conference University of East London pp. 128-136
Improving Geocoding Rates in Preparation for Crime Data Analysis
Brimicombe, A., Brimicombe, Lily C. and Li, Y. 2007. Improving Geocoding Rates in Preparation for Crime Data Analysis. International Journal of Police Science & Management. 9 (1), pp. 80-92.
Scenario-based Small Area Population Modelling for Social Infrastructure Planning
Li, Y. and Brimicombe, A. 2008. Scenario-based Small Area Population Modelling for Social Infrastructure Planning. in: Lambrick, David (ed.) Proceedings of GIS Research UK 16th Annual conference GISRUK 2008 pp. 348-353
Agent-based services for the validation and calibration of multi-agent models
Li, Y., Brimicombe, A. and Chao, Li 2008. Agent-based services for the validation and calibration of multi-agent models. Computers, Environment and Urban Systems. 32 (6), pp. 464-473.