This presentation is co-financed by the European Social Fund and the state budget of the Czech Republic
Detection and Visualisations of Ecotones Landscape Pattern under Uncertainty
Jan BRUS
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Uncertaintyour imperfect and inexact knowledge of the world
Datawe are unsure of what exactly we observe or measure in society or nature
Rulewe are unsure of the conclusions we can draw from even perfect data (how we reason with the observations)
Definitions
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Isn’t better to provide geoinformation with some kind of uncertainty?
Isn‘t maps (geovisualizations) with information about data uncertainty confusing?
What‘s the right/good way of uncertainty visualization?
What‘s better in a real decision process?
Is uncertainty visualisation necessary?
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
just about everything varies over space(spatial dependence)
therefore, an estimation of uncertainty is important The estimate can be:
descriptive quantitative
Spatial variability
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Ecotones ecotones are significant part of almost every landscape
structures and have a significant effect on the distribution of species
spatial variability of ecotones has resulted in problematic modelling, analysis and visualization of these landscape forms
ambiguous boundary in the landscape forest – ecotone – field
exploratory analysis based on remote sensing products, historical maps, field mapping
plenty of datasets – different quality – several typesof uncertainty
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
The aim of the project was to analyze spatial boundaries of ecotones and to model dynamics structure of landscape system by an example of watershed of Trkmanka river in time period of 1764─2006 (app. 230 years).
The base model element is landuse category acquired by mapping in scale 1 : 25 000 and by study of historical maps. Individual categories of landuse were analyzed.
The project solved spatial organization and landscape dynamics by the study of boundary of landscape elements – ecotones.
Ecotone project
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
uncertainty of ecotones in the landscape arises from many sources, including complexities inherent in ecosystems and their disturbance processes
collection, analysis and visualization with geodata is more difficult
further decisions are more complicated several sources of uncertainty
accuracy, nature (basis) of a phenomenon, data manipulation etc.
Uncertainty
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Lineage (description of the source material from which the data were derived and the methods of derivation)
Positional accuracy (resolution of the measurement) Attribute accuracy (both measurement accuracy and class
assignment accuracy) Logical consistency (describing the fidelity of relationships
inside data structure) Completness (relationship between the objects represented
and the abstract universe) Currency (time currency, time relevance) Credibility (reliability of information source, experiences) Subjectivity (amount of human judgments in the information) Interrelatedness (source independence)
(Shi, 2010)
Sources of uncertainty
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Approach in visualisation
futureEye-Tracking study
Examples
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Visual variable Description
Location (position) (x,y) position of an element on the visual plane
Size dimensions of an element
Shape combination of size and orientation
Value local amount of black that is perceived
Color local hue and saturation
Orientation local angle of the elements
Texture (grain) local variation in the scale of the elements
Focus power of attraction of an element to the eye
Realism perceptual similarity of an element to a real-world object
Bertin (1983), MacEachren (1992) and McGranaghan (1993)
Visual variables in uncertainty visualisation
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Uncertainty visulalisation of different data types and data quality
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Uncertainty visualisation methods classification
(Senaratne & Gerharz 2011)
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
research on usability studies in uncertainty visualizations have been performed from 1990
many tests on several techniques were conducted Evans (1997) assessed Static Color Bivariate Maps Fisher examined the Flickering Animation method (1993) MacEachren considered Toggling (1992) MacEachren et al. assessed Adjacent Maps (1998) and a
Color Model (2005) the Texture Overlay method was assessed by Kardos et al.
(2003) Sanyal et al. (2009) found that the perception of uncertainty
is not uniform
Usability studies
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Trkmanka River basin left tributary of the Dyje River located in South-east Moravia the river is of lowland characteristics it flows through an open countryside
vegetation cover 72 % agricultural area 18 % forests 10 % vegetation-free area
Area of interest
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
combination of disparate data sets, each of which may have a very different uncertainty structure associated with it
land use biotype mapping of the Czech Republic which was processed
by methodology introduced by NATURA 2000 pedoecological unit (soil-ecological unit, BPEJ in Czech, used
for land appraisal) forest topology and more
How best to represent the data (uncertainty) so that the results best reflect the overall uncertainty?
Representation data
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Landuse of Trkmanka river catchment
WoodsArrable landPasturesOrchardsVineyardsBuildingsWaterTransect
- photointerpretation from historical maps and aerial images
- subjectivity of results
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Land Facet Corridor Tools for ArcGIS
Delineation of ecotones – entropy approach
• can be used for each map layer
• combinantion of entropies
• showing most uncertain
• map algebra
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Entropy visualisations
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Visualisation methods
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Results
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Results
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Uncertainty visualisation of ecotones
d) mosaicc) transparencyb) blura) grid
adjacent method
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
information entropy can be used to visualize uncertainties in the landscape structures
gives an explanation where uncertainties (transition zones as ecotones) may occur.
beyond pure visualization, the measure can be interpreted in a quantitative way
we can clearly distinguish areas with high uncertainty from results
these areas highly correspond with actual presence of ecotones (transitions zones) in the landscape proved by field survey
Results
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Fuzzy – POM demonstrator (Vullings, 2006) Wobling with positional uncertainty – Boundary seer etc…
Usability testing Eye-tracking Developing representation methods for depicting
multiple kinds of uncertainty
Further methods to delinination and research
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
we can deduce that the perception of areas with a low level of uncertainty differs from the perception of places with a high degree of uncertainty
a legend expressing the uncertainty of data is a very important component of the map, this element in maps in most cases attracts significant attention
the difference of correct answers within the same map with and without a legend was 45% in extreme cases. An average difference was around 20%
results also showed that the length of observation did not affect the accuracy of answers in general
Preliminary Eye-tracking results
First InDOG Doctoral Conference, 29th October - 1st November 2012, Olomouc
Thank you for your attention Jan Brus
[email protected] http://geoinformatics.upol.cz/