Introduction to Error and uncertainty in Environmental GIS
Prepared by: Kondwani Godwin Munthali & Prof Yuji Murayama Division of Spatial Information Science Graduate School of Life and Environmental Science, University of Tsukuba, Japan
School of Geography Introduction FACULTY OF ENVIRONMENT
Great tools, great reliance… great risk when in
error.
Are GIS tools spared?
What are we talking about? data quality, error and uncertainty error propagation confidence in GIS outputs
Why is error & uncertainty important? Or is it, at
all important?
So that we are careful, aware, and able to communicate
School of Geography Terminology & definition FACULTY OF ENVIRONMENT
Variant forms
Error
Lack of error detail of a data set/value Unreliability!?!?
Accuracy
wrong or mistaken A measure of how inaccurate a value is.
Uncertainty
Error, uncertainty, accuracy, precision, data quality
proximity of measurement results to the true value
Precision
repeatability or reproducibility of the measurement
School of Geography Terminology & definition, cont’d… FACULTY OF ENVIRONMENT
Data quality
measure of excellence - how good the data is Includes error, uncertainty, precision, accuracy
School of Geography Error sources in GIS data FACULTY OF ENVIRONMENT
Map sources: age of data and areal coverage map scale and density of observations
variation and measurement: positional error attribute uncertainty Generalisation
processing errors: numerical computing errors faulty topological analyses interpolation errors
School of Geography Error sources in GIS data, cont’d… FACULTY OF ENVIRONMENT
Digitizing error Manual digitising
Regular shift
significant source of positional error
Source map error scale related generalisation line thickness
Operator error under/overshoot time related boredom factor
Distortion edge effects
Obvious & hidden errors
Systematic and random errors
School of Geography Error sources in GIS data, cont’d… FACULTY OF ENVIRONMENT
Vector to raster conversion coding errors cell size grid orientation
Fine raster
Coarse raster
topological mismatch errors cell size grid orientation
Effects of raster size Original
Tilted
Original raster
Shifted
Effects of grid orientation
School of Geography Attribute uncertainty FACULTY OF ENVIRONMENT
Uncertainty regarding characteristics (descriptors,
attributes, etc.) of geographical entities
Types: imprecise (numeric) or vague (descriptive) mixed up plain wrong!
Sources: source document misinterpretation (human error) database error
School of Geography Generalisation FACULTY OF ENVIRONMENT
Scale-related cartographic generalisation
simplification of reality by cartographer to meet restrictions of: map scale and physical size effective communication and message
can result in: reduction, alteration, omission and simplification of map elements passed on to GIS through digitising
School of Geography Cartographic Generalisation FACULTY OF ENVIRONMENT
1:3 M
1:10,000 1:500,000
1:25,000
City of Sapporo, Japan
Map Source: Carver S.
School of Geography Handling error & uncertainty FACULTY OF ENVIRONMENT
Why cope with error and uncertainty in GIS
applications?
minimise risk of erroneous results minimise risk to life/property/environment
School of Geography Handling error & uncertainty, cont’d… FACULTY OF ENVIRONMENT
Awareness
knowledge of types, sources and effects
Minimisation use of best available data correct choices of data model/method
Communication
to end user! (How?)
School of Geography Quantifying error FACULTY OF ENVIRONMENT
Sensitivity analyses Jacknifing leave-one-out analysis repeat analysis leaving out one data layer test for the significance of each data layer Bootstrapping Monte Carlo simulation adds random noise to data layers Simulates the effect error/uncertainty
School of Geography Conclusion FACULTY OF ENVIRONMENT
Many types and sources of error that we need to be
aware of Environmental data is particularly prone because of high spatio-temporal variability Few GIS tools for handling error and uncertainty… and fewer still in proprietary packages Need to communicate potential error and uncertainty to end users
School of Geography References & further reading FACULTY OF ENVIRONMENT
Bolstad, PV et al., (1990) Positional uncertainty in manually digitised map data. IJGIS 4(4) p.399-412. Brunsdon C. & Carver, S. (1993) The accuracy of digital representations of 2D and 3D geographical objects: a study by simulation. in M.Fischer & P.Nijkamp (eds) Geographic Information Systems, spatial modelling and policy evaluation. Springer-Verlag, Germany, 115-130. Brunsdon, C., Carver, S., Charlton, M. & Openshaw, S. (1990) A review of methods for handling error propagation in GIS. in Proceedings of 1st European Conference on Geographical Information Systems. Amsterdam, Netherlands, April 1990, 106-116. Burrough, P & McDonnell (1998) Principles of geographial information. Oxford University Press, Oxford. [chapters 9 and 10]. Carver, S. (1991) Error modelling in GIS: who cares? in J.Cadoux-Hudson & D.I.Heywood (eds) The Association for Geographic Information Yearbook 1991. Taylor & Francis/Miles Arnold, London, 229-234. Carver, S. & Brunsdon, C. (1994) Vector to raster conversion error and feature complexity: an empirical study using simulated data. in International Journal of Geographical Information Systems. 8(3), 261-272. Chrisman, N. (1989) Modelling error in overlaid categorical maps. In Goodchild, M.F & Gopal, S (eds) (1989) Accuracy of spatial databases. Taylor & Francis, London. Dunn, R., Harrison, A.R. & White, J.C. (1990) Positional accuracy and measurement error in digital databases of land use: an empirical study, in IJGIS, 4, 385-398. Goodchild, M.F. & Gopal, S. (eds) (1989) Accuracy of spatial databases. Taylor & Francis, London. Heuvelink, G. (1998) Error propagation in environmenal modelling. Taylor & Francis, London. Heywood, I., Cornelius, S. & Carver, S. (1998) An Introduction to Geographical Information Systems. Addison Wesley Longman, Harlow. [chapter 10]. Newcomer JA and Szajgin, J. (1984) Accumulation of thematic map errors in digital overlay analysis. The American Cartographer. 11(1), p.58-62. Openshaw, S., Charlton, M. & Carver, S. (1991) Error propagation: a Monte Carlo simulation. in I.Masser & M.Blakemore (eds) Handling geographic information: methodology and potential applications. Longman, London, 78-101. Walsh. SJ., Lightfoot, D.R and Butler, D.R (1987)Recognition and assessment of error in GIS. PE&RS. 53(10) p.1423-1430.
