GIS Analýza
1. Vyvolání/klasifikace/měření
2. Překryt (koincidence)
3. Sousednost
4. Napojenost
1. Průzkum
• Vyvolání
- Selekce dotazováním
• Klasifikace
- seskupení
- vzory
• Měření
- Délky, plochy, vzdálenosti, hustoty
Retrieval: Selective Search
addresses selected because they fall within circle
Work with areas > 80 acres
Vector Distance Operation: Buffers 0 Setbacks
Buffers
Setbacks
Diagram of sim pie buffers and a setback. NOTE: buffers go outward from lines or areas; setbacks run inside of areas (not
lines).
Image Source: Chrisman, Nicholas.(2002). 2nd Ed. Exploring Geographic Information Systems. p 154. fig. 6-1.
Buffer Creation: Illustrated
To generate a buffer, construct these objects around each segment, overlay all the objects, aggregate to remove duplicate areas.
A Simple Buffer
Method of construction:
Each segment throws out a zone around it (two half circles and one rectangle.)
Result of overlay
Buffer produced by aggregating all the objects. Figure 6-3  Construction method for buffers in a vector representation.
Image Source: Chrisman, Nicholas.(2002). 2nd Ed. Exploring Geographic Information Systems, p 60. fig. 6-3.
2. Overlay Functions
• Aritmetické
- + - * / sin() etc.
• Logické
- and, or, >, <, etc.
• Grid vs. Vektor
- Vektor zachová více informací
- Grid je jednodušší a flexibilnější
Overlay: Combining Attributes
Select attributes of interest for a given location
Given these values of attributes, a combination rule decides the result.
(Raster C vector methods do this differently, but the results are similar)
highest bidder,
#1 Enumeration Rule: Each #2 Dominance Rule: One
Attribute preserved in output value wins
Overlay: 4 Basic Rules
Operations like addition allow each source to contribute to result.
Decisions in each step may differ.
#3 Contributory Rule: each attribute value contributes to
result
#4 Interaction Rule: pair of values contribute to result
Vector based Overlay
• 3 main ty p es of vector overlay
- point-in-polygon
- line-in-polygon
- polygon-on- polygon
Vector based overlay
Met station point map
Forest polygon map
+
p oint-in- p olygon exam ple
Met station point map
Met station attribute table
Point ID	Land use
1	Forest
2	Forest
3	Non-forest
line-in-polygon example
p olygon-in- p olygon exam ple
Raster Overlay: Boolean Combine
Geometric Phase
Common grid framework ensures that each pixel overlays in the same position,
Attribute Phase
Threshold Operation chosen between      (combination rule) suitable and not.      produces result.
Image Source: Chrisman, Nicholas.(2002). 2nd Ed. Exploring Geographic Information Systems, p 125. fig. 5-3.
Raster Overlay: Composite Combine
Geometric Phase
1	1	2	
1	2	3	
2	3	4	
	5		
			
1		
2		■
3		
4		
		
Key to Categories
Attribute Phase
Operation creates new categories for all distinct combinations discovered.
From the composite
categories, any
result can be obtained.
Vector Overlay: Composite Structure
Geometric Phase
First phase discovers all intersections between input linework, creates .topological structure,
/
Second phase identifies al polygons with unique id and link to parent attributes.
Attribute table
Attribute Phase
Using the attribute table, a query can extract combinations of attributes.
Image Source: Chrisman, Nicholas.(2002). 2nd Ed. Exploring Geographic Information Systems, p 127. fig. 5-5.
3. Neighborhood Functions
• Basic Functions
- Average, diversity, majority, minimum/maximum, and total
• Parameters to define:
- Target location(s)
- Sp ecification of neighborhood
- Function to perform on neighborhood elements
3. Neighborhood Function (cont)
• Search O peration
- most common neighborhood o p eration
• Exam pie
- count the number of customers within 2 miles of the grocery store
3. Neighborhood Functions (cont)
• Thiessen Polygons O peration
- defines the individual area of influence around a point
- used to predict values at surrounding p oints from a single p oint observation
- can produce p olygons with sha p es unrelated to phenomenon being ma p p ed
Thiessen Polygons
Neighborhood Functions: Circular Neighborhood Processing
CircüLai neighborhood
Calls included
				I										
														
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			f & ' lil	*«	- \	¥■ J iti r								
			■8	3?ft£			iftVK							
				ft>-fc ! -SP-		ft -Si-f- Ä								
														
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Processing cell
Neighborhood Functions:
Example
Zone theme: Watersheds Value theme: Elevation Statistic type: Mean
Output:
Mean elevation of each watershed
Neighborhood Functions: 10x10 averaging filter on a DEM
Neighborhood Statistics
4. Connectivity Functions
• Used to accumulate values over an area being navigated
• Parameters to define:
- s pecification of way s p atial elements are connected
- rules that s pecify allowed movement along
interconnections
- a unit of measurement
• Proximity O p eration
- measure of the distance between features
- not restricted to distance; can be noise, time, pollution, etc.
• Parameters to define:
- target location
- unit of measure
- function to calculate proximity (distance/time/noise)
- area to be analyzed
Proximity Operation: Distance From Neighbor
Example: Connectivity (Vector)
Proximity Operation: Buffer Generation
Diagram of sim pie buffers and a setback. NOTE: buffers go outward from lines or areas; setbacks run inside of areas (not lines).
Image Source: Chrisman, Nicholas.(2002). 2nd Ed. Exploring Geographic Information Systems. p 154. fig. 6-1.
• Contiguity O peration
- s p atial units are connected - defines "unbroken area"
• Contiguity measures:
- size of neighboring area(s)
- shortest/longest straight line distance across adjacent
area(s)
- s pecific sha pe of neighboring area(s)
Combines adjacent units together when they share a common attribute
4. Connectivity Functions (cont).
• Network O perations
- set of interconnected lines that re p resent a set of features through which resources flow
• Common network functions
- shortest p ath problem (route o ptimization)
- location-allocation modeling (resource allocation)
- traveling sales person p roblem (route o ptimization
- route tracing (prediction of network loading)
Network Function: Location-Allocation
Spread Functions:
Travel Time - Creating Friction Surface
LAND USE DATA LAYER
TRAVEL TIME DATA LAYER
CROPLAND
ROAD
HAN Citri AND
QUARRY
6	fi	e	fi	fi	fi	6	fi	fi	£	6	fi	6	6
B	6	e		6	6	6	6	6	6	6	6	6	6
6	6	6	6	6	6	6	6	6	6	6	6	C	e
6	6	e	6	G	£	6	8	6	6	6	6	e	6
6	6	e	6	6	G	6	e	6	e	6	f.	e	e
2	2	2	2	2	2		2				L'		2
4	4	4	4	A	4	4	4	+	4	+	4	4	4
4	4	4	4	A	4	4	4		4	+		4	4
4	4	4	4	4	4	4	4	4	4	4	+	+	4
4	4	Ar	4	4	4	4	4	t	4		4	4	4
4	4	4	4	4	4	4	4	4	+	+	4	4	*
TRAVEL TJMES ARE tN kmft*
Spread Functions:
Travel Time - Friction Surface
Friction Surface Data Layer
J      2 2
2      2 2
2      2 2
2 2
>     * 2
Start Point Data Layer
4.8	4	4.8	42	4.8	5.8	
2.8	2	2.8	34	4.4	S.4	Cumulative
2	0	2	3	4	5	Travel Time
2.8	2	2.8	3.4	4.4	5.4	Data Layer
4.8	4	4.8	4.2	4.8	5.8	
Spread Functions: Travel Time - Map
t if ■
9
INCREMENTAL TRAVEL TIME DATA LAYER
START POINTS DATA LAYER
TRAVEL TIME MAP
Emergency Services
Real time tracking, route-finding, best to respond
4. Connectivity Functions (cont).
• Visibility Analysis O perations
- identification of areas of terrain that can be seen
from a articular oint on the surface
• Viewshed O peration
- uses digital elevation model data (DEMs) or.....
- digital terrain model data (DTMs) or......
- triangulated irregular network data (TINs)?
4. Connectivity Functions (cont).
• Visibility Analysis O perations
- identification of areas of terrain that can be seen from a p articular p oint on the surface
• Viewshed O peration
- uses digital elevation model data (DEMs) or.....
- digital terrain model data (DTMs) or......
- triangulated irregular network data (TINs)
Viewshed aka Intervisibility
3D landscape model impact on natural beauty
• Surface functions
- density, contour, interpolation functions
- as pect, slope, hillshade, etc.
- watershed analysis and modeling (flow direction, flow accumulation, flow length, watershed delineation, stream ordering)
- visibility modeling/ma p ping
• determine the area that can be "seen" from the
target location
The 3rd Dimension: Height Analysis
•
•
Contours
Hill shading
S p ot height symbols
Cliff & slo p e symbols
View p oint symbols
• GIS does not always provide exact answers to problems, but by identifying trends based on geogra phy, GIS can reveal p atterns that can help us make informed decisions.
• A GIS can improve decision-making; it cannot
make decisions for us.
3D height data changing water levels-danger areas
Derived Mapping: Data from images
2	2	2	9	1	2	2	2	2	2	2	2	2	2
2	2	9	1	2	2	2	1	2	2	2	2	2	2
2	9	1	2	2	2	1	8	1	2	2	2	2	2
9	1	2	2	2	1	8	3	8	1	2	2	2	2
1	2	2	2	1	8	3	3	3	8	1	2	2	2
2	2	2	1	8	3	3	3	3	3	8	1	2	2
2	2	1	8	3	3	3	3	3	3	3	8	1	2
2	1	8	3	3	3	3	3	3	3	8	1	2	2
2	2	1	8	3	3	3	3	3	8	1	2	2	2
1	2	2	1	8	3	3	3	8	1	2	2	2	2
4	1	2	2	1	8	3	8	1	2	2	2	2	2
7	4	1	2	2	1	8	1	2	2	2	2	2	2
7	7	4	1	2	2	1	2	2	2	2	2	2	2
7	7	7	4	1	2	2	2	2	2	2	2	2	2
Numerical Values
Color Representation
Derived Mapping: Data from images
Derived Mapping: Data from images
Retail: Site Selection
Existing stores, 15 min. drive time, demograhics
Airport Noise Pollution
noise com plaints ma p p ed by address location