Spatial Analysis 6th semester

8/2/2019 Spatial Analysis 6th semester

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Foundations for Applied GIS

Spatial Analysis

Geog-3205

Khurram Chohan


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Spatial Analysis

Geographic information analysis is concerned withinvestigating the patterns that arise as a result ofprocesses that may be operating in space.

Representation, Description , Measurement,Comparison , and generation of spatial pattern arethe main techniques / methods to GeographicInformation Analysis.

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Literature Review

Spatial data manipulation, usually in a geographicinformation system (GIS), is often referred to asspatial analysis, particularly in GIS companies'promotional material. Your GIS manuals will give

you a good sense of the scope of these techniques,as will texts by Tomlin (1990) and, more recently,Mitchell (1999).

Buffering

Point in Polygon..Queries

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Literature Review

Spatial data analysis isdescriptiveandexploratory. These are important first steps in allspatial analysis, and often all that can be done withvery large and complex data sets. Books by

geographers such asUnwin (1981), Bailey andGatrell (1995), and Fotheringham et al. (2000)

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Literature Review

Spatial statistical analysis employsstatisticalmethodsto interrogate spatial data to determinewhether or not the data are "typical" or"unexpected" relative to a statistical model.

By Ripley (1981, 1988), niggle (1983), and Cressie(1991).

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Literature Review

Spatial mode involves constructing models topredict spatial outcomes.

In human geography, models are used to predict

flows of people and goods between places or tooptimize the location of facilities (Wilson, 1974,2000)

In environmental science, models may attempt tosimulate the dynamics of natural processes (Ford,1999).

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Spatial Data Types

Raster / Image Data

Vector Data

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Spatial Data Types

Vector View It records locational coordinates of points , Lines, and

areas.

The vector model conforms to an object view of the world,where space is thought of as an empty container occupiedby different sorts of objects.

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Spatial Data Types

Raster / Image View Instead of starting with objects on the ground, a grid of

small units of Earth's surface (called pixels) is defined.

For each pixel, the value, or presence or absenceof something of interest, is then recorded.

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Higher Level Abstraction of Spatial Data Types

An Object

The Object View

The Field View

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The Object View

world is considered as a series of entities located inspace.

Entities are (usually) real

You can touch them, stand in them, perhaps evenmove them around.

Example..Places can be occupied by any number ofobjects. A house can exist in a census tract, which mayalso contain lampposts, bus stops, road segments, parks,and so on.

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The Object View

The object view has advantages when well-definedobjects change in time: for example, the changing

data for a census area object over a series ofpopulation censuses.

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An Object

An object is a digital representation of all or part ofan entity. Objects may be classified into different

object types: for 'example, intopoint objects, lineobjects, and area objects.

Example------woods and fields

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The Field View

In the field view, the world is made up of propertiesvarying continuously across space.

Example-----Earth SurfaceWhere ElevationVaries

Similarly, we can code the ground in a grid cell as

either having a house on it or not. The result is alsoa field, in this case of binary numbers where1=house and 0= no house.

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Raster Data Model is not only the one way torepresent the geographic variations where data arerepresented in regularly shaped Pixels.

An alternative way to represent surface in a meshof non-overlapping triangles called TriangularIrregular Network (TIN)

A good example is a map of soil type. Everywherehas a soil, so we have spatial continuity, and wealso have self-definition by the soil type involved, sothis is a field view.

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16TIN

RASTERSOIL MAP



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Land Use Maps

These types have been given different names: k-color maps , Black and White

K-Color technique, each type is assigned a specificcolor required to show the variation.

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Right Choice to representation of spatial world

Real world is represented in the form of elementsand these elements are stored in database.

Entity Vs. Object

Entity must be identifiable; if you can not see it,you can not record it.

Entity must be relevant, and of interest.

Entity must be describable. Therefore, it must haveattribute / characteristics so that we can record it.

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Right Choice to representation of spatial world

Definition of an Entity: Entity is defined as a phenomenon of interest in reality

that is not further subdivided into phenomena of the samekind.

Examples:

Road Network Vs. Roads

Forest Vs. stands.

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Ri h Ch i f b i f


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What you want to do with the data entered into thecomputer system?

What should be the map design and objectives?

What should be the model to represent real world?

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Right Choice for better representation ofspatial world


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Types of Spatial Objects

Point: an object with no length,L0

Line : an object having the same spatial dimensionas any simple length, that is, L 1.

Area : an object with spatial dimension lengthsquared, or L2

Cartographic conventions.

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Theoretical and Practical Issues

There is a need to separate the representation ofan object from its fundamental spatial

characteristics. Forexample, a line object may beused to mark the edge of an area.

Geographic scale is important.

A railway station may be represented as a point, a set oflines, or an area.

The objects discussed are often two-dimensional

Need to represent Elevation / Depth22


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This view of the world is a static one. This is fine for some problems, but in many applications

our main interest is in how things evolve and change overtime.

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Scales for attribute description

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It is understood that reality represented in point,line, polygon.

Geometric entities are embedded with aspatial

data. The range of possible attribute is huge: Color, age

,use, ownership, and so on.

Attributes can be classified into types based ontheir level of measurements.

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Nominal Scale Each value is a distinct category, serving only to

label or name the phenomenon.

We call certain buildings "shops" and there is noloss of information if these are called "category 2"instead.

Categories must be inclusive / Mutually exclusive

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Ordinal Scale Nominal scale does not imply relationships between

classes.

Ordinal scale rank classes according to somecriterion.

Classification of land according to its agriculture potential

Note: Attributes measured on the nominal and ordinal scales

are often referred to collectively as categorical data. 27

Ordinal (Ranks)

Good Better

Best


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Interval Scale: The interval level of measurement has the property

that differences or distances between categories

are defined using fixed equal units.

interval scales lack an inherent zero

Thermometers typically measure on an interval scale,ensuring that the difference between, say, 25 and 35"C is

the same as that between 75.5F and 85.5F. 28

Interval (numeric)

Age

Income


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Ratio Scale

Example

If place A is 10 km (6.2137 miles) from B and 20 km(12.4274 miles) from C, the ratio of the distances is

distance AB /distance AC = 10 / 20

= 1/2

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Ratio (scale)

Length

Area


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Spatial Data Types In Everyday Life

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Spatial Data Manipulation and Analysis

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Mapping and Visualization Geometric Intersections, Buffering, and

Point-in-Polygon Tests

Map Overlay

Linking GIS and Spatial Anaysis

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Spatial Data Manipulation and Analysis


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Mapping and Visualization

maps have been used for centuries as a datastorage and access mechanism for topographic andcadastral (land ownership) information.

Thematic Maps are being used to display statisticdata and result of other systematic surveys.

Maps created specifically to highlight the distribution of aparticular phenomenon or theme are called Thematic

Maps

a

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Population change in the United States, by county,from 1990 to 2000.(Data from 1990 & 2000 decennial censuses).

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A "dot density" map that depicts count data.Cartography by Geoff Hatchard.

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A "proportional circle" map that depicts count data.Cartography by Geoff Hatchard.

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A "pie chart " map that depicts rate data.Cartography by Geoff Hatchard.

A pie chart is a circular chart

which is divided into sectors,

illustrating proportion

In a pie chart, the arc length

of each sector is proportional

to the quantity it represents

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A "bar/column chart" map that depicts rate data.Cartography by Geoff Hatchard.

A bar chart or bar graph is a

chart with rectangular bars

with lengths proportional to the

values that they represent.

The bars can be plotted

vertically or horizontally.

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A "graduated color" (choropleth) map that depictsdensity data. Cartography by Geoff Hatchard.

A choropleth map is a thematic map

in which areas are shaded

or patterned in proportion

to the measurement of

the statistical variable

being displayed on the

map, such as population

density or per-capita income.

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A "unique values" map that depicts density data. Notethat the legend, which in the original shows onecategory for each state, is trimmed off. Cartography byGeoff Hatchard.

Logically or not, peopleprefer colorful maps.

For this reason some

might be tempted to

choose Arc Map's Unique Values

option to map rates, densities,

or even counts.

This option assigns a unique

color to each data value 41


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Broad Street cholera outbreak in Soho, London 1854.

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Geometric Intersections, Buffering, and point-


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Geometric Intersections, Buffering, and pointin-polygon Tests

Is a measure of the distance between features. It is most commonly measured in units of length but

can be measured in other units.

Such as travel time or noise level

Four parameters must be specified to measure

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Parameters Parameters (Examples)

Target Location A Road, A hospital, or A park

A unit of measure Distance in meters

Function to calculate proximity. Straight line distance, travel time.

The area to be analyzed The area to be analyzed

Geometric Intersections, Buffering, and point-


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we can easily determine how many cases of adisease occur within various distances of certainkinds of factory or other facility.

We need geocoded data for cases of the diseaseand also for the facilities.

Point-in-polygon operations allow us to determinehow many cases of the disease occur in the

relevant buffer areas

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Geometric Intersections, Buffering, and pointin-polygon Tests


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4/6/201

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Map Overlay

In a map overlay two or more layers are overlaid inorder to produce a new layer.

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Map Overlay


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Map Overlay


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Linking GIS and spatial analysis

The GIB view of spatial data and that of spatialanalysis are different.

Spatial analysis is not widely understood.

The spatial analysis perspective can sometimesobscure the advantages of GIS.

Documents

Spatial Analysis 6th semester