aliens and geographic things: a GIScience perspective Femke Reitsma

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aliens and geographic things: a GIScience perspective

Femke Reitsma

School of Geosciences, Edinburgh University e-Science Institute 23/07/2007

hmm.....

Randy Stevens – Cocktail Party

Randy Stevens – Cocktail Party

legs cocktail glasses heads

Randy Stevens – Dancers I, II, III

outline

1. standard GIS things

2. spatio-temporal things

3. qualitative challenges

observation → representation

● what should we abstract?

influences explanation first question = what do we want to explain?

standard GIS things

● the geo-atom < x Z z x

1

> point polygon line pixel

point

line

polygon

pixel http://landmap.mimas.ac.uk

data model implications borrowed from esri.com

time + standard GIS things

● snap shots change detection t1 t2 t3 t4 time

time + standard GIS things

Hägerstrand

Space-time path

static GIS due to...

• cartographic origins

• emphasis on attributes & relationships vs. process and change

• presumed priority of objects in human cognition

outline

1. standard GIS things

2. spatio-temporal things

3. qualitative challenges

spatio-temporal things: agents

● agent based modelling

ABM grazing simulation

Water sources

Agent-based animals

Borrowed from Conrad Rider

Even grazing pressure More pressure at water source

Borrowed from Conrad Rider

spatio-temporal things: processes

● represented in dynamic models as sets of equations or rules not represented as output www.answers.com

www.metoffice.gov.uk

process interpolation

● problem of multiple process pathways equifinality f(x) t1 t2 time

process interpolation t1 t2 time

process data model nen = (node,edge,node) nen = process

process data structure x1, y1 attributes x2, y2 spatial location

nen = (x1, y1, x2, y2, t, st, {a1, a2, …an}, {r1, r2, … rn}) temporal location spatio-temporal granularity rules

why?

• query processes

• analyze processes

• better understand model’s spatial behavior

outline

1. standard GIS things

2. spatio-temporal things

3. qualitative challenges

what can't we currently represent in a GIS?

● complex real-world stuff qualitative information image from http://www.corrwillbourn.com/

qualitative information

• can we reduce qualitative information?

• how do we represent it in a GIS?

• qualitative information models?

• first question = what do we want to explain?

qualitative information models?

• data models

• information models

• knowledge models

< x Z z x

1

>

semantic geospatial data models?

● richer data models → information models

< x Z z x

1

>

● how do we inject complexity into our data models?

back to our alien….

thank you

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