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Lecture 3: Spatial Analysis

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INTRODUCTION TO SPATIAL

INTRODUCTION TO SPATIAL

ANALYSIS

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Four fundamental

functions of GIS

fall

under the

manipulation and analysis

component (Martin, 1991):

1. Reclassification operations 2. Overlay operations

3. Distance and connectivity measurements 4. Neighbourhood characterisation

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1.

Reclassification operations

• transform the attribute information associated with a single map coverage. E.g.

• allow the “cause-and-effect” of certain spatial factors be evaluated. E.g.

* population densities classified into classes such

as 'sparsely populated' or 'overcrowded' etc.) * soil types and farmland values

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MAP

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URBAN

RESIDENTIAL INDUSTRIALURBAN

RURAL FOREST

RURAL AGRICULTURE

URBAN

RURAL

ORIGINAL CLASSIFICATION GENERALIZED CLASSIFICATION

classification provides new patterns/relationships

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Classification (cont.)

Classification:

• Land parcels for housing are classed into

• single storey terrace,

• double storey terrace and • bungalow.

Generalisation:

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2. Overlay operations

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Nb rMean of residuals - 500m.shp -0.74 - -0.57 (great est overestimation) -0.57 - -0.35

-0.35 - 0 0 0 - 0.35 0.35 - 0.57

0. 57 - 0.78 (greatest und erestim ation) No Data

Glasgow City Council - UKBORDERS.shp Motorway12km.shp

4 0 4 Miles

N

E W

S

Ordnance Survey Crown Copyright. All rights reserved

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3. Distance and connectivity

measurements

• include both simple measures of inter-point

distance and more complex operations such as the construction of zones of increasing transport cost away from specified locations.

• Distance measurement can be used to calculate straight line and network distance.

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MEASUREMENT MEASUREMENT DISTANCE DISTANCE PARAMETER PARAMETER AREA/SIZE AREA/SIZE A B C D

X 5 KM Y

A- B = 20 = 40% B- C = 20 = 40% C - D= 10 = 20%

2

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DISTANCE (STRAIGHT LINE) MEASUREMENT

A- B: Alor Setar - Kuala Lumpur 360 KM

B- C: Kuala Lumpur - Kuantan 270 KM

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4. Neighbourhood characterisation

• involves ascribing values to location according to characteristics of the surrounding region.

• Such operations may involve both summary and mean measures of a variable.

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Mean selling price (£ per sq km) .shp 20500 - 45939

45939 - 71377 71377 - 96816 96816 - 122255 122255 - 147694 147694 - 173132 173132 - 198571 198571 - 224010 224010 - 249449 No Data

Glasgow City Council - UKBORDERS.shp Motorway12km.shp

4 0 4 Miles

N E W

S

Ordnance Survey Crown Copyright. All rights reserved

Neighbourhood analysis of mean selling prices

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• Anselin (1998) proposes that GIS functions

can be classified as follows

Selection

ManipulationExplorationConfirmation

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GIS

functions

Selection: involves boolean queries and spatial

sampling. This seems similar to the overlay operations function.

Manipulation: may be based on attribute data, map

data, or integration of both, simultaneously. This

means analysing data in an integrated manner where various data as available in the database can be

combined in an analysis.

Exploration: for investigation of spatial structure and

involves description and visualisation. This is relevant to spatial autocorrelation analysis of hedonic models using geo-statistical method

Confirmation: for modelling spatial association and/or

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DATA RECALL

DATA RECALL

• can be invoked on spatial and attribute components

• involves selective search • no new objects created • examples:

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CLASSIFICATION AND GENERALISATION

CLASSIFICATION AND GENERALISATION

• classification - identify a set of characteristics to group together objects.

• in a vector system, classification involves addition of objects characteristics.

• in a raster system, classification involves converting or coding cell values.

• classification examples: Land parcels for housing are classed into single storey terras, double storey terras and bungalow.

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Housing Age

Legend

Before 1900 1901-1930

1931-1950

1951 to 1999

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URBAN

RESIDENTIAL INDUSTRIALURBAN

RURAL FOREST

RURAL AGRICULTURE

URBAN

RURAL

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...

...

• vector data

– converting attribute values for polygon, line and point

• raster data

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MEASUREMENT

• measurement functions includes distance, parameter and area

• example: land parcels larger than 5 hectares

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MEASUREMENT MEASUREMENT DISTANCE DISTANCE PARAMETER PARAMETER AREA/SIZE AREA/SIZE A B C D

X 5 KM Y

A- B = 20 = 40% B- C = 20 = 40% C - D= 10 = 20%

2

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DISTANCE MEASUREMENT

A- B: Alor Setar - Kuala Lumpur 360 KM

B- C: Kuala Lumpur - Kuantan 270 KM

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... MEASUREMENT

... MEASUREMENT

• vector data

– area and parameter is obtained from coordinates of the polygon nodes

– distance is derived from coordinates of starting/ending nodes

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SEARCHING

SEARCHING

• determine values against target object according to a neighbourhood characteristic

• three parameters need to be identified

– targets

– neighbourhood around the targets

– applied neighbourhood function for resultant values

• example: total of households within 1 km of proposed shopping mall

– target-shopping mall

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... SPATIAL SEARCH

... SPATIAL SEARCH

• operated as additional points in polygon, line in polygon and polygon in polygon

• vector data

– point, line or polygon analysed with

neighbourhood polygon using coordinate nodes

– involves complex calculation with overlapping and out-of-boundary neighbourhood

• raster data

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NEIGHBOURHOOD

NEIGHBOURHOOD

• represents ‘distance’ between map features • ‘distance’ unit can be in measurement units

or other units like travelling time, noise level, visibility distance etc.

• requires 4 parameters

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... NEIGHBOURHOOD

... NEIGHBOURHOOD

• used to generate buffer zones

• example: a 2km zone along a proposed

transmission line alignment; zones exceeds 50dB around the airport

• neighbourhood is most often complex and involves data from various layers. For

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R Buffering a Point

eg. All area within one mile of a city

Buffering a Line

eg. All areas within 100 meters of a road

Buffering an Area

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OVERLAY

OVERLAY

• Involves two or more data layers • Produces new layers

• Two types of overlay operation – arithmetic overlay

– logical overlay

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MAP ALGEBRA (MULTIPLICATION)

MAP ALGEBRA (MULTIPLICATION)

OVERLAY BY MULTIPLICATION

DISTRICT

1 2

3 4 X

CROP AREA

1

B B

= 1 2

3 4

OVERLAY BY MAXIMUM VALUE

3 3 4 0 1 0 2 4 6

4 2 2

5 5 5

4 1 1

4 3 4

5 5 5

4 4 6

RAINFALL : RAINFALL: RAINFALL:

1980 1981 1980 - 1981

+ =

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... OVERLAY

... OVERLAY

• vector data are sometimes more

efficient than raster data if data are not dense.

– vector data - operation based on the

selected data only

– raster data - operation on all cells -

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Soil Type

+

Crops Production (ton/ha)

Overlay Result

GIS Technology: Relationship between Land use and Crop Productivity

(40)

Ja lan R

aja A lang

Jalan Abdul Aziz

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Sewerage pond Sewerage pond

Ja lan R

aja A lang

Jalan Abdul Aziz

Ja la n D at uk M al ik Jalan Hamzah

Jalan Ra

ja Uda

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Ja lan R

aja A lang

Jalan Abdul Aziz Jalan Hamzah Jalan Raja Uda

References

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