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3/13/2017 1 Introduction to Geographic Information Science Spatial Models Geography 4103 / 5103 Updates • Rescheduling: Quiz 2 coming soon Quick review Reading Discussion 3 Reading discussion 2 – some notes The GIS Levels GEOG 4103/5103: Fundamentals of GIS, GEOG 4203/5203: GIS modeling GEOG 4303/5303: GIS programming GEOG 4403/5403 Spatio-temporal Analysis GEOG 4023/5023 Statistical training GEOG 4093/5093 Remote sensing

Introduction to Geographic Information Science - colorado.edu · Introduction to Geographic Information Science Spatial Models ... and their basic concepts ... • Important terminology

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Page 1: Introduction to Geographic Information Science - colorado.edu · Introduction to Geographic Information Science Spatial Models ... and their basic concepts ... • Important terminology

3/13/2017

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Introduction to Geographic Information Science

Spatial Models

Geography 4103 / 5103

Updates

• Rescheduling:

• Quiz 2 coming soon

• Quick review

• Reading Discussion 3

• Reading discussion 2 – some notes

The GIS Levels

• GEOG 4103/5103: Fundamentals of GIS,

• GEOG 4203/5203: GIS modeling

• GEOG 4303/5303: GIS programming

• GEOG 4403/5403 Spatio-temporal Analysis

• GEOG 4023/5023 Statistical training

• GEOG 4093/5093 Remote sensing

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Last Lecture

• We talked about vector operations and their basic concepts

• Understand how spatial data analysisworks

• How to do Measurements• Selection, Classification, & Dissolve• Understanding Buffering• … and spatial Overlay in general

Today‘s Outline

• We will look into spatial modeling

• Talk about different taxonomies of spatial models

• We will focus on Cartographic Modeling and see some examples

• Important terminology to understand criteria, ranks, weights and flowcharts

Learning Objectives

• Learn about key terms and concepts of (spatial) models

• Understand different classifications and the common sense between them

• Understanding Cartographic Modeling and tools for performing it

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Spatial Modeling …?

• ‘Modeling’ per se is one of the most overloaded terms anywhere

• Reason enough to think about what exactly we mean by referring to spatial modeling

• Generally, a model is a (simplified) description of reality (static reproduction, conceptual description)

• Modeling can (or should) be considered as a process …

Modeling Process and its Components

Four important questions (DeMers 1,5):

• What is the model to tell us (explaining, predicting relationships or consequences / evaluating situations for resource uses,…)? Or simply: Do we understand what the problem is?

• What type of data do I need?

• How to create a design to put the model together?

• How to apply existing tools, carefully and appropriately to derive meaningful models?

Validation and verification as important steps

GIS & (Spatial) Modeling?

• Need of a way to “think spatially”• How to represent (abstract) our world in a

GIS?• What are the visible or functional

patterns• What are the spatial relationships and

what can they tell us?• Dozens of definitions and many different

classification schemes

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Spatial and GIS Models I (Bolstad)

• Cartographic models:

temporally static, combined spatial datasets, operations and functions for problem-solving

• Spatio-temporal models

dynamics in space and time, time-driven processes

• Network models:

modeling of resources (flow, accumulation) as limited to networks

Crowd simulation: http://www.youtube.com/playlist?list=PLD56A0C7765234DCDTraffic simulation: http://www.youtube.com/watch?v=q_7cd0Gao6U&list=SP20C69E9F07FF4E20&index=2 (1:50)

Spatial and GIS Models II(Goodchild 2003)

• Data models:Entities and fields as conceptual models

• Static modeling:taking inputs to transform them into outputs using sets of tools and functions

• Dynamic modeling:iterative, sets of initial conditions, apply transformations to obtain a series of predictions at time intervals

Spatial and GIS Models III(DeMers 2005)

• Based on purposedescriptive - passive, description of the study areaprescriptive - active, imposing best solution

• Based on methodologystochastic - based on statistical probabilitiesdeterministic - based on known functional linkages and interactions

• Based on logicinductive - general models based on ind. datadeductive - from general to specific using known factors and relationships

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Combine data sets and operations in a sequenceto answer questions, typically producing an output map from various input maps Based on “criteria”; often as suitability analysis

Examples:- distribution of suitable habitats, viable populations- migration route/corridor studies- water distribution systems, natural and constructed- species invasions- mill site selection- harvest scheduling- pollution response planning

Back to Cartographic Modeling

Cartographic Models

For example, suitability analyses; classification of land according to its utility for a specific use.• Often temporally static (spatial features fixed over time)• Change models may include a temporal component (comparing vegetation in 1990 to vegetation in 2000)

Cartographic Model Example

Intermediate data creationDecision-making process

Suitable park sites based on proximity to roads and lakes and the absence of wetlands

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Criteria Design• Conversion of qualitative terms into quantitative

measures• Different combined criteria could have varying relative

importance• This might require an explicit weighting of “relative

importance” (ranking and weighting) of layers/criteria

“Rankings”Assignment of relative values within the same layer (discrete or continuous)Relationships can be complex and should be justified

“Rankings”

Suitability assignment function

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“Weighting”• Assignment of relative values to different layers

(criteria) (elevation vs. landuse) for example due to importance

• Difficulties due to non-quantifiable measures (decision-maker, expert opinion) - how to do?

Back to our suitability model

Flowcharts to graphically represent the spatial data, operations and their sequence

… and its Flowchart

Now, think about ranks and weights to understand complexity.

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The ModelBuilder Interface

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Some Facts on Model Builder

• Geoprocessing using a graphical representation of model components in a workflow (flow charts)

• Build and test models in personal toolboxes as fully integrated tools in the Geoprocessing Framework using tools from ArcToolbox

• Automation, portability, extensibility, reusability, documentation

Sources of Errors

• Connectivity between input data, processes and output data

• Specification: Parts of the model such as parameters have to be defined

• Accessibility of input data

• Only some basic validation tools

Summary

• We tried to explore what stands behind “spatial model” by looking at definitions, taxonomies and examples

• An understanding of the methods we use (exploring / explaining) and of the problem we face (modeling) are central

• The aim of spatial modeling is to derive a meaningful representation of events, occurrences or processes by making use of the power of spatialanalysis

• Modelbuilder is a good example how to combine functionalities for creating Cartographic Models

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References

• Longley P.A., M. F. Goodchild, D. J. Maguire and D. W. Rhind. 2005. Geographic Information Systems and Science. Second Edition. John Wiley, Chichester, 2005.

• Goodchild, M.F. 2003. Geographic Information Science and Systems for Environmental Management. Annual Review of Environment and Resources. Vol. 28: 493-519.

• Burrough, P.A. and McDonnell, R.A. 1998. Principles of Geographical Information Systems. London: Oxford.

• Goodchild, M F. 1988. Modeling error in objects and fields. Accuracy of Spatial Databases Meeting; Montecito, CA; (USA); Dec. 1988. pp. 107-113. 1990

• Tomlin, C.D. 1991 Cartographic Modeling. In Maguire, D., Goodchild, M.F., and Rhind, D. (Eds.) Geographic Information Systems: Principles and Applications. London: Longman: 361 - 374.

• Goodchild, M. F., 1987, Towards an enumeration and classification of GIS functions. Proceedings, /CIS 87: the Research Agenda, edited by R. T. Aangeenbrug and Y. M. Schiffman (Washington, DC: NASA), 11, 67-77.