modeling in gis - gsi.ir

Modeling in GIS

Introduction

What is a model?

Models are expressions of how the world is believed to work (Longley et al. 2005)

In GIS Models are digital or computational (geocomputation)

Models are spatial There is variation across space which is manipulated by

the model The results of the modeling change when the location of

object change

2Geospatial Information [email protected]

Modeling in GIS

Introduction

Modeling There is a wide range of complexity captured in the term

“model”

Editorial comment As stated by Longley et al. (2005) Model is one of the most

overworked terms in the English Language

Don’t let the word “model” scare or intimidate you, the vast majority of models are quite simple

Also always ask yourself - “Does the quality or accuracy of the inputs justify the complexity of the model used?

GIGO - Garbage In Garbage Out


Modeling in GIS

Introduction

So why do we model?

Spatial models can

1. Describe the basic properties of spatial features

2. Describe the relationships between spatial features

3. Describe the processes underpinning spatial features and interactions between them

4. Help us understand spatial forms and behaviors

5. Help us Solve spatial problems of interest


Modeling in GIS

Introduction

Types of GIS Models

One can classify spatial models in a number of ways.

Bolstad (2012) presents a useful classification of spatial models for an introductory GIS course.

He breaks spatial models into three general types

1. Cartographic Models

2. Simple Spatial Models

3. Spatio-temporal Models


Modeling in GIS

Introduction

More General Types of Models Models Based on Purpose

1. Descriptive2. Predictive

Models Based on Methodology1. Stochastic2. Deterministic

Models Based on Logic1. Inductive (Specific Observations General

Understanding)DeMers states that these usually rely on empirical tests of validity and trial/error implementation

2. Deductive (General Understanding Specific Application)


Modeling in GIS

Introduction

Beginning thoughts (De Mers)

Rather than beginning with the components themselves, it is often best to begin by examining the envisioned output from the analysis.

Often called the spatial information product (Marble 1994), a recognition of the required output allows us to break the envisioned output and its model into interacting components.

AKA…Dissect the Problem…


Modeling in GIS

Introduction

A conceptual model for solving spatial problems

Step 1: State the problem

Step 2: Break the problem down

Step 3: Explore input datasets

Step 4: Perform analysis

Step 5: Verify the model result

Step 6: Implement the result


Modeling in GIS

Introduction

Step 1: State the problem To solve a spatial problem, you should first state the problem

you are trying to solve and the goal you are trying to achieve

Example: The problem is to find the best location for siting a new school.


Modeling in GIS

Introduction

The result you seek is a map showing potential sites (ranked best to worst) that could be suitable for building a new school.

This is called a ranked suitability map because it shows a relative range of values indicating how suitable each location is on the map, taking into account the criteria you put into the model.


Modeling in GIS

Introduction

To help you model your spatial problem, draw a diagram of the steps involved.

Start with the statement of the problem.

As you work through the problem, you will expand the diagram to show objectives, process models, and input datasets needed to reach your goal.

Define the goal of the analysis


Modeling in GIS

Introduction

Step 2: Break the problem down

Once the problem is stated, break it down into smaller pieces until you know what steps are required to solve it.

These steps are objectives that you will solve.

When defining objectives, consider how you will measure them.


Modeling in GIS

Introduction

How will you measure what is the best area for the new school?

It is preferable to locate near recreational facilities, as many of the families who have relocated to the town have young children interested in pursuing recreational activities.

It is also important to be away from existing schools to distribute their locations over the town.

The school must also be built on suitable land that is relatively flat.

an area of land that is large enough for the school

its grounds or locating in an area with the highest density of children of an appropriate age


Modeling in GIS

Introduction

To meet these objectives, you want to know the following:

Where are locations with relatively flat land? Is the land use in these locations of a suitable type? Are these locations close enough to recreation sites? Are they far enough away from existing schools?


Modeling in GIS

Introduction

Where are locations with relatively flat land?

To find areas of relatively flat land, you need to create a map displaying the slope of the land.

The process model here involves calculating the slope of the land.

Input dataset needed: Elevation


Modeling in GIS

Introduction

Is the land use in these locations of a suitable type? You need to decide what makes a suitable land-use type on which

to build.

Agricultural land is considered the least costly to build on and, therefore, the most preferable.

Barren land is next, then scrub brush, forest, and lastly, existing built-up areas.

There is no process model involved here, just an identification of the input land-use dataset and which land uses are most preferable to build on.

Input dataset needed: Land use16Geospatial Information Agent

[email protected]

Modeling in GIS

Introduction

Are these locations close enough to recreation sites? It is preferable to locate the school close to recreational

facilities,

We need to create a map displaying distances to recreation sites to potentially locate the school in areas that are close to them.

The process model here involves calculating distances from recreation sites.

Input dataset needed: Location of recreational facilities


Modeling in GIS

Introduction

Are they far enough away from existing schools?

We want to site the school away from existing schools to avoid encroaching on their catchment areas.

We need to create a map displaying the distance to schools.

Here, the process model involves calculating the distance from existing schools.

Input dataset needed: Location of existing schools


Modeling in GIS

Introduction

Identify the necessary tools and input data


Modeling in GIS

Introduction

Step 3: Exploring input datasets Which attributes within and between datasets are important for

solving the problem and looking for trends in the data.

We can often gain insights about the areas in which you want to locate the school, the weighting for input attributes, and alterations to your modeling process.

We can see the locations of existing schools and recreation sites, and you can tell from the elevation dataset where the higher elevations are.

The land-use dataset tells you what types of land use are in the area and where they are located in relation to the other datasets.


Modeling in GIS

Introduction

Step 4: Performing analysis Creating a suitability map

Creating suitability scales

Ranking the areas close to recreation sites

Ranking the areas away from existing schools

Ranking the areas on relatively flat land

Ranking the areas on suitable land-use types

Combining the suitability maps

Querying your data21Geospatial Information Agent

[email protected]

Modeling in GIS

Introduction

Creating a suitability map

Creating a suitability map enables you to obtain a suitability value for every location on the map.

Each map layer is ranked by how suitable it is as a location for a new school.

For example, assign a value to each class in each layer on a scale of 1 to 10, with 10 being the best.


Modeling in GIS

Introduction

Creating suitability scales There are natural scales that are commonly associated with

some objectives.

Cost is a good example but needs to be defined in sufficient detail.

Many scales are not linear relationships, although they are often presented that way to save time and money or because all options were not considered.

For example, if assigning a scale to travel distance, traveling 1, 5, or 10 kilometers would not be ranked as a suitability of 10, 5, and 1 if you were walking. Some people may think that walking 5 kilometers is only two times as bad as 1 kilometer, while others may think it's 10 times as bad.


Modeling in GIS

Introduction

Ranking the areas close to recreation sites To site the school close to recreational facilities, you need to

know the distance to them.

The result is a raster dataset in which every cell represents the distance to the nearest recreation site.


Modeling in GIS

Introduction

Ranking the areas away from existing schools To avoid the catchment areas of the other schools, you need to

know the distance to them.

The result is a raster dataset in which every cell represents the distance to the nearest school.


Modeling in GIS

Introduction

Ranking the areas on relatively flat land To avoid steep slopes and find areas that are relatively flat to

build on, you need to know the slope of the land

The result is a raster dataset in which every cell represents the maximum rate of change in value from each cell to its neighbors.


Modeling in GIS

Introduction

Ranking the areas on suitable land-use types The easiest way to decide what type of land is preferable for

building on and what is not is to decide on the most preferable and then the least preferable.

Wetlands have been excluded from the analysis, as you cannot build on water and there are restrictions against building on wetlands.


Modeling in GIS

Introduction

Combining the suitability maps Some objectives have more importance in the suitability model

than the other.

Suitability percentages


Modeling in GIS

Introduction

Suitability factors Percent influence Percentages Distance to recreation sites 50% (0.5)Distance to schools 25% (0.25)Slope 12.5% (0.125)Land-use types 12.5% (0.125)

Individual suitability graphs weighted and displayed


Modeling in GIS

Introduction

Output suitability map


Modeling in GIS

Introduction

Querying your data

The alternative way to find suitable locations for the new school (rather than creating a suitability map) is to query your data.


Modeling in GIS

Introduction

all locations on agricultural land with slopes less than 20 degrees, where the distance to

recreation sites is less than 1,000 meters and the distance to schools is greater than 4,000

meters.

Output map from Boolean query


Modeling in GIS

Introduction

Step 5: Verifying the result Once you have your result from any spatial analysis, you should

verify that it is correct.

If possible, this should be done by visiting the potential sites in the field.

Often the result you achieve has not accounted for something important.

For example, there may be a chicken ranch upwind of the site that is producing foul odors, or by examining the town hallrecords you may discover a restriction on building on the desired land of which you were not aware.

If either is the case, you will need to add this information to the analysis.


Modeling in GIS

Introduction

Step 6: Implementing the result

The final step in the spatial model is to implement the result, which is to commence the planning and construction of the new school in the chosen location.


Modeling in GIS

Introduction

How Modeling is accomplished

Much modeling cannot be done solely with a Graphical User Interface (GUI)

It requires either

a GIS “scripting or macro language” Today Python. In the old days –

Visual Basic, Avenue or AML

Or external programs or programing languages R ,IDL, Matlab, Splus, SAS, or

user-written code


Modeling in GIS

Introduction

Coupling

Tight Modeling done within a GIS environment

Loose Modeling done outside a GIS environment GIS used to prepare inputs for model GIS used to analyze inputs from model GIS used for visualization purposes


Modeling in GIS

Introduction

Rasters and Modeling

The raster grid structure lends itself to modeling

Modeling can occur within the GIS (Tight coupling) external to the GIS (Loose coupling)

Code used can be commercial public domain user written


Modeling in GIS

Introduction

Cartographic Modeling


Modeling in GIS

Introduction

What is a Cartographic Model?

A cartographic mode! is a set of map layers that are all registered with respect to a common cartographic frame of reference.


Modeling in GIS

Introduction

What is Cartographic Modeling

Cartographic Modeling is the processes of combining individual GIS analytical operations to create complex models to solve a complex problem or aid in the decision making process.


Modeling in GIS

Introduction

I like to think of it as an extension of the Cartographic Overlay process really pioneered by Ian McHarg and brought into GIS by C. Dana Tomlin

Overall the Raster data model has a richer set of functionality than is possible with vector data though vectors were the first GIS data model used in cartographic modeling.

Most cartographic models are temporally static as the inputs represent spatial features at a fixed point in time

In many cases the inputs may actually represent different times as they were generated from data collected at different times.

Cartographic model output is often nominal (suitable, unsuitable) or ordinal (high, medium, low)


Modeling in GIS

Introduction

Ian McHarg

His 1969 book Design with Naturepioneered the concept of ecological planning and is a classic book on landscape architecture and land-use planning.

It also laid out some of the fundamental concepts in GIS


Modeling in GIS

Introduction

The Foundation of Cartographic Overlay ...let us map physiographic factors so that the darker the tone,

the greater the cost.

…let us similarly map social values so that the darker the tone, the higher the value.

…let us make the maps transparent. When these are superimposed, the least-social-cost areas are revealed by the lightest tone.


Modeling in GIS

Introduction

Can be performed in either vector or raster


Modeling in GIS

Introduction


Modeling in GIS

Introduction

Guidelines

1. A cartographic spatial information product is constructed from a set of simpler, more elemental, intermediate, cartographic output guidelines

2. The intermediate cartographic output products are often simpler models themselves and can be broken down into fundamental cartographic and/or numeric elements that cannot be further atomized.

3. The fundamental elements can be thematic maps (raster or vector), thematic or spatial subsets of these, numerical values or variables whose values will change during the course of the modeling exercise.


Modeling in GIS

Introduction

4. Each of the fundamental elements are connected to each other by operators which represent the functional relationship between the elements

5. Elements can be used more than once (e.g. slope may affect more than one process)

6. A model is just a model and should present an opportunity for verification, validation, and decision justification. The “correctness” of a model depends upon our ability to explicitly define and explain all components and their interactions


Modeling in GIS

Introduction

Example Cartographic Model


Modeling in GIS

Introduction

Designing a Cartographic Model Most cartographic models are based on a set of criteria, which

unfortunately, are often specified in qualitative terms.

For example, Ideally my retirement house in Upstate New York would be

on a southward facing slope with soils well suited to a septic system, be not too far from the road due so I will not have plough myself after it snows and has and beautiful views of Cayuga Lake.


Modeling in GIS

Introduction

What has to be done is to take these criteria and convert them into something suitable for a model and prioritize their importance.

The second thing we have to be concerned with is whether or not appropriate GIS information in terms of quality and accessibilityis available to enable to create a suitable cartographic model


Modeling in GIS

Introduction

Rankings and Weightings It is necessary to consider how to create rankings both within

and among the criteria (inputs and intermediate products) used in our model.

For a single input or criterion layer, it is necessary to determine if the layer should be nominal (e.g. in or out of a floodplain) or if it needs ordinal (high, medium, low or 0-10) or more continuous interval or ratio values.


Modeling in GIS

Introduction


Modeling in GIS

Introduction

It is also necessary to consider how much relative weight needs to be placed on each input layer.

For example is the distance to road more important then the septic system.

It is easiest to do this if all the criteria can be expressed on the same scale, for example the range of values for each input ranges from 0 to 1.

Otherwise it is necessary to take the range of the input values into consideration when combining them.


Modeling in GIS

Introduction

For example if slope ranges from 0-20° and the distance to road 100-1000 meters, how do they compare?

Note how these two different measures are placed on the same scale to facilitate comparability

Linearly scaling an array of numbers to the range 0-1 is simple:


numberscaled = (max – numberorig)

(max – min)

Modeling in GIS

Introduction



Modeling in GIS

Introduction

Finally, it is necessary to assign weights to each of the criterion layers.

There are multiple ways of doing this. One simple method is an “importance ranking.”

Each factor is ranked in importance from most to least and a relative weight is calculated as follows:


Criterion Rank weightA 4 (6-4)+1/21 = 0.143B 2 (6-2)+1/21 = 0.238C 6 (6-6)+1/21 = 0.048D 1 (6-1)+1/21 = 0.286E 3 (6-3)+1/21 = 0.190F 5 (6-5)+1/21 = 0.095

Wi =(n - ri) + 1

nk=1 (n - ri + 1)

Modeling in GIS

Introduction


Modeling in GIS

Introduction

Simple Spatial Models

Quite common. Often a well established model based developed for a single point or for application at a small scale can be “spatialized” using GIS.

The output is often interval or ratio in nature (e.g. a continuous variable) as opposed to a cartographic model where output is often nominal or ordinal in nature.


Modeling in GIS

Introduction

Example: Environmental Temperature Profile


Tem

pera

ture

(°C)

Elevation (m)

0 2000 4000 6000 8000 10000 12000

30

20

10

0

‐10

‐20

‐30

‐40

y = -0.0065x + 28Interpolation

Extrapolation

Modeling in GIS

Introduction

Example


Modeling in GIS

Introduction

Revised Universal Soil Loss Equation (RUSLE) A very commonly used simple spatial model which models the

erosion (mm/year).

R – rainfall factor K – soil erodibility C – crop effects P – management practices L – slope length S – slope steepness

E = R . K . C . P . L . S


Modeling in GIS

Introduction


Modeling in GIS

Introduction

Flowcharting Cartographic Models can be represented graphically by

flowcharts which are useful both to help conceptualize how to approach developing a cartographic model as well as to formally present a model to an audience.

It is often helpful to sketch out a model prior to implementing it in a GIS as a flowchart!


Modeling in GIS

Introduction

An Example Flowchart It should be noted that cartographic modeling can create a large

number of intermediate files that need to be kept


Modeling in GIS

Introduction

Process-Based ModelingSediment Transport

Question: How much sediment is accumulating or eroding from the highlighted grid cell?


Modeling in GIS

Introduction

Step 1:

Determine neighboring cells contributing sediment to cell of interest


Modeling in GIS

Introduction

Step 2:

Determine amount of water flowing into and out of each cell

Flow = f(rainfall, cell area, number of contributing cells)


Modeling in GIS

Introduction

Step 3:

Determine velocity of water flowing into and out each cell

Flow = f(flow, slope)


Modeling in GIS

Introduction

Step 4: Determine sediment transport

sediment = f(flow, velocity, threshold velocity)


If velocity > thresholdsediment = 0.234 *flow2

Modeling in GIS

Introduction

Step 5: Determine if cells are accumulating sediment or area eroding


Erode

Accumulate

If sediment in < sediment out thenerode

elseaccumulate

Modeling in GIS

Introduction

Step 6: Determine net accumulation/erosion

Elevation change = (mass_change / sediment density) / area of cell


+1 m

0 m-1 m-2 m

Modeling in GIS

Introduction

Step 7:

Determine Change in Slope due to lowering or raising of surface


+2

-1.9 to 1.9-2

Modeling in GIS

Introduction

Step 8….N:

Repeat the process over numerous time steps to determine the net gain or loss of mass in the cell (or cells) of interest remembering that the situation in each cell has been altered given what has occurred in the previous steps.


Modeling in GIS

Introduction

modeling in gis - gsi.ir

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