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Spatial DataAnalysis

Spatial DataAnalysis

Spatial Data Analysis

¬Distinguishing capabilities of GIS¬For spatial decision making¬Transform and combine spatial data into

useful information

Spatial Data Analysis

¬ Measurement basic spatial measurement x,y distance, area, etc

¬ Spatial Querydata retrieval on both geometric and attribute data

¬ Re(Classification)assign new classification codes

¬ Overlaycombine data layers and derive new information: topological and raster overlay

¬ Neighbourhoodevaluate the charateristics of surrounding area

¬ Network analysisthe connectivity of linear features

¬ 3D analystcalculating volume, generating profiles, determining watershed boundaries

Measurement Operation

¬Only geometric measurements¬Not attribute data measurement¬2D Spatial reference system

LIMITATIONS...

Measurements Operations - Vector

¬Measurement on individual features°Location°Length°Distance°Area size

Measurements Operations - Vector

¬Distance calculation

0,0 Xq Xp

Yq

Yp

X

Y

22 )()(),( qpqp YYXXqpdist −+−=

Measurements Operations - Vector

¬Stored as attributes in the tables¬Automatically updated when geometric

editing occurs, for example, polygon splitting¬Specify map projection and coordinate

systems beforehand¬The measurement is in the spheroid

units when data are in geographic units

Measurements Operations - Raster

¬Simpler because of the regularity of the cells¬Usually by counting the number of cells¬Cell resolution may differ horizontally

and vertically¬The anchor point is georeferenced and

in the lower-left corner of the raster

Spatial Data Analysis

¬ Measurement basic spatial measurement x,y distance, area, etc

¬ Spatial Querydata retrieval on both geometric and attribute data

¬ Re(Classification)assign new classification codes

¬ Overlaycombine data layers and derive new information: topological and raster overlay

¬ Neighbourhoodevaluate the charateristics of surrounding area

¬ Network analysisthe connectivity of linear features

¬ 3D analystcalculating volume, generating profiles, determining watershed boundaries

Spatial selection query

¬Define a query expression¬Execute the query¬Display the results

Basic procedure…

Spatial selection query

¬Specify the data layer¬Define selection objects by pointing or

drawing¬Specify the overlay operations (intersect,

meet, contain, etc.)¬Features within the selection objects are

selected and highlighted¬Display the attributes of the selected objects¬Answer questions: What is at … ?

Interactive spatial selection ...

Spatial selection query

Interactive spatial selection ...

Spatial selection query

¬Define a selection condition on the features attributes in a query language, such as SQL.¬Display the result both on the map and

in the attribute table¬Answers questions: Where are the

features with …?

By attribute condition ...

Spatial selection query

By attribute condition ... Area < 400000

Spatial selection query

¬Using logical connectives to combine atomic conditions into composite conditions:°AND°OR°NOT°Bracket pair ()

Area < 4000000 AND Landuse = 80Area < 4000000 OR Landuse = 80

Combining attribute conditions ...

Spatial selection query

Area < 4000000 ANDLanduse = 80

Combining attribute conditions ...

Spatial query

Basic steps:¬Select one or more features (using either spatial or

attribute selection) – selection objects.

¬Apply one of the spatial relationship operations to select other features¬Display the result both on the map and in the

attribute table

Using topological relationships ...

Spatial Relationships

Spatial query

¬Uses the containment relationships¬Can be applied to certain features types:

Select features inside selection objects ...

Spatial query

Select features...

Select all clinics in district “A”

Spatial query

¬All relationships except disjoint.¬Two polygons intersect if they share a

common area.¬Two line intersect if they share a common line

segment¬A line and a polygon intersect if the line is

partially or completely inside the polygon

Select features that intersect ...

Spatial query

Select features that intersect ...

Select all the roads that are partially or completely located in district “A”

Spatial query

¬Use the MEET relationship.¬Share common

boundaries.¬Apply only to line and

polygon features

Select features adjacent to selection objects ...

Industry area adjacent to the selection polygon

Selection of polygon

Spatial query

Select features based on their distance ...

Which roads are within 200 meters of a clinic

Spatial selection query

¬Also called buffer generation or proximity analysis.

Select features within or beyond a specified ...

#

Point Line Polygon

Spatial query

¬Generate buffer polygons.¬Apply containment relationship

operation to select features inside or outside the buffer polygons¬Display result

Spatial query Roads and banks

Select highway class roads

Create buffer along highway

Select banks within the buffer polygons

Example:Select all the banks within 200 meters from highway class roads

Spatial Data Analysis

¬ Measurement basic spatial measurement x,y distance, area, etc

¬ Spatial Querydata retrieval on both geometric and attribute data

¬ Re(Classification)assign new classification codes

¬ Overlaycombine data layers and derive new information: topological and raster overlay

¬ Neighbourhoodevaluate the characteristics of surrounding area

¬ Network analysisthe connectivity of linear features

¬ 3D analystcalculating volume, generating profiles, determining watershed boundaries

(Re)Classification

¬Assign codes based on specific attributes¬Reduce the number of classes and

eliminate details¬Useful for revealing spatial patterns¬Reclassify data in different systems or

for different purposes

(Re)Classification - procedure

Example:¬Soil types reclassified into soil suitability for

agricultural purpose.¬House hold income classification:°Low°Below average°Average°Above average°High

(Re)Classification - mergeFive classes of house hold income with original polygons intact

Five classes of house hold income with original polygons merged (boundary dissolved) in the same categories

(Re)Classification

¬Differences on vector and raster data

No. because only pixel attributes are change

Yes. For example, two neighbour polygons merged into one

Geometric or topological change

Classification attribute may be nominal, ordinal or interval/ratio

Classification attribute is usually nominal or ordinal

Input data source

RasterVector

(Re)Classification

¬User indicates the classification attribute(s)¬User specified the classification method:°The number of output classes°The correspondence between the original attribute

values and the new attribute values°Called classification table

User controlled classification ...

(Re)Classification

User controlled classification ...

(Re)Classification

¬ User specifies the no. or output classes¬ Computer decides the class break points¬ Equal interval:

class interval = (Vmax – Vmin)/n¬ Equal frequency (quantile):°Maintain equal or nearly equal no. of features in each

category in the output

Automatic classification ...

(Re)Classification - automatic

Equal interval (5 classes)

Equal frequency (5 classes)

(Re)Classification - raster

1.1 1.2 1.4 2.8 8.2

4.1 4.5 5.6 4.3 9.0

4.5 3.5 3.2 2.1 1.3

4.3 5.2 6.0 8.5 8.9

4.3 4.4 1.2 1.1 1.9

(a)

1 1 1 2 8

4 4 5 4 9

4 3 3 2 1

4 5 6 8 8

4 4 1 1 1

(b)

Lower limit

Upper limit

New Category

1.0 1.9 1 2.0 2.9 2 3.0 3.9 3 4.0 4.9 4 5.0 5.9 5 6.0 6.9 6 7.0 7.9 7 8.0 8.9 8 9.0 9.9 9

Spatial Data Analysis

¬ Measurement basic spatial measurement x,y distance, area, etc

¬ Spatial Querydata retrieval on both geometric and attribute data

¬ Re(Classification)assign new classification codes

¬ Overlaycombine data layers and derive new information: topological and raster overlay

¬ Neighbourhoodevaluate the characteristics of surrounding area

¬ Network analysisthe connectivity of linear features

¬ 3D analystcalculating volume, generating profiles, determining watershed boundaries

Overlay functions

¬Combines several data layers into one.¬New spatial elements are usually created¬All map layers must be georeferenced in the

same system¬Both on vector and raster data

Overlay operations – Vector data

¬Topologically overlay¬ Involves complicated geometric calculations

to create new topology¬Spatial features are combined¬New attributes are assigned to each new

feature, such as area, parameters¬The attributes from the input data layers are

kept in the output

Overlay operations

Overlay operations - Union

¬ All the features in the two input data source are kept in the output

¬ Applies only to polygon features

Overlay operations - Intersect

¬ Only the features inside the common area of the two input data are kept in the output.

¬ One input data can be point, line or polygon feature type, the other must be a polygon data set.

Overlay operations - Identity

¬ All features of the input coverage, as well as those features of the Identity coverage that overlap the input coverage, are preserved in the output coverage.

¬ One input data can be point, line or polygon features type, the other must be a polygon data set.

Overlay operations - CLIP

¬ Extracts those features from an input coverage that overlap with a clip coverage.

¬ No combination of attributes.

Overlay operations - ERASE

¬ Erases the input coverage features that overlap with the erase coverage polygons.

¬ No combinations of attributes.

Overlay operations - UPDATE

¬ Replace the input coverage areas with the update coverage polygons using a cut-and-paste operation.

Overlay operations - RASTER

¬ New cell values are calculated using calculus – map algebra

¬ Performed on cell-by-cell basis¬ No geometric calculation

Output_raster_name := raster_calculus_expression

Overlay operations - RASTER

Arithmetic operators¬ +, -, *, /¬ MOD (modulo division)¬ DIV (integer division)¬ Goniometric operators: sin, con, tan, asin, acos, atan.

Raster2 := Raster1 * 5

Overlay operations - RASTER

Overlay operations - RASTER

¬ Comparison operators° <, <=, =, >=, >, <>

¬ Logical operators° AND, OR, NOT, XOR (exclusive)

a XOR b is true if either a or b is true

¬ The cell values of the output raster is either true or false

Raster3 := Raster1 <> Raster2

Overlay operations - RASTER

Example of logical expressions

Overlay operations - RASTER

Overlay operations - RASTER

Output_raster := IFF(condition, then_expression, else_expression

Conditional expression

Overlay operations - RASTER

Overlay using a decision table• for complicated conditional expression

Spatial Data Analysis

¬ Measurement basic spatial measurement x,y distance, area, etc

¬ Spatial Querydata retrieval on both geometric and attribute data

¬ Re(Classification)assign new classification codes

¬ Overlaycombine data layers and derive new information: topological and raster overlay

¬ Neighbourhoodevaluate the characteristics of surrounding area

¬ Network analysisthe connectivity of linear features

¬ 3D analystcalculating volume, generating profiles, determining watershed boundaries

Neighbourhood functions

Find out the characteristics of the neighbourhood of a location°Proximity computationÜBuffer zone generationÜThiessen polygon generation

°Spread computationÜData retrieval on both geometric and attribute data

°Seek computationÜAssign new classification codes

Neighbourhood functions

Neighbourhood functions

¬ Thiessen polygon generation° Partition the plane into polygons so that each polygon

contains location that are closer to the polygon’s midpoint than to any other midpoints.

° Easier to construct thiessen polygons based on Delanuay triangulation

Neighbourhood functions

¬ Spread computation

Neighbourhood functions

¬ Seek computation

Spatial Data Analysis

¬ Measurement basic spatial measurement x,y distance, area, etc

¬ Spatial Querydata retrieval on both geometric and attribute data

¬ Re(Classification)assign new classification codes

¬ Overlaycombine data layers and derive new information: topological and raster overlay

¬ Neighbourhoodevaluate the characteristics of surrounding area

¬ Network analysisthe connectivity of linear features

¬ 3D analystcalculating volume, generating profiles, determining watershed boundaries

Network analysis

¬Model physical network features, road, river, telecommunication etc.¬Characteristics:°Move resources from one place to another on the

network: goods delivery, electricity power transmission etc.

¬Network problem:°Connectivity°movement

Network analysis – data model

¬ Consists of lines and nodes.¬ A line begins and ends at nodes -from- and to-nodes.

Network analysis – data model

¬Point features°If it is not located directly on a line or a

node, it is snapped to the nearest node or line.°In the case of line, the line is split and a

new node is added

Network analysis – data model

¬Line direction°Every line has a direction.°It’s defined in from-node (start-node) to to-

node (end-node) direction.°Line direction is an important element in

network analysis, specially in defining different attributes for different directions of the lines

Network analysis – data model

¬Planar network data model°Every intersection between line has a

node. Line has a direction.°Difficult in modeling some applications,

such as multiple-grade crossing (underpass/overpass)°Non-planar network data model is more

suitable for network analysis.

Network analysis – data model

¬Connectivity°Two lines are directly connected if they

share a common node.°Two lines are indirectly connected if a path

can be found that connects the two lines.°Two lines are not connected if no path can

be generated between them.°Concerns not only the geometric topology,

but also semantic relationships.

Network analysis

¬Optimum path finding: generates a least cost-path on a network between a pair of predefined locations based on both geometric and attribute data¬Network partitioning: assigns network

elements (nodes and the whole or a portion of lines) to different locations based on predefined criteria

Network analysis

¬ Required data° A set of network elements (line segments and nodes) and

topological structure that defined the connectivity, for example, a water supply network

° The types and the capacity of the resources to be transported, for example, the amount of water that can be produced at the water plant and distributed through a network

° The location of the start and the end points of the movement, for example, the location of the water plant as the supply point and the locations of customers as the consumption points of the water along the water pipes.

° The constraints associated with the resources movement, for example, the minimum pressure level of water supply, traffic speed limit, no right or left turn restrictions on road intersections, the maximum volume of run-off water in a sewage system, etc.

Network analysis – Path finding

¬Establish the least-cost path between two nodes¬Define a sequence of lines for traverse that

cost min. compared to any other alternative path

Network analysis

¬Cost factors°Also called impedance.°One of the attributes in the feature attribute table.°Length, travel time, etc.°The least-cost path is the one that has the minimal

value of the total cost between two nodes.

Network analysis

¬ Cost factors° The cost can be defined on both lines and nodes.° For line, the cost can be same or different along and against

the line direction.° The cost on nodes is used to define the turns

Network analysis

¬ Minimum-cost path° In principle, it should calculate the total costs for all the

possible paths between the origin and the destination points. Then select the minimum-cost path.

° To reduce the computation time, different algorithms are applied, such as Dijkstra’s.

Network analysis

¬Ordered path finding°User defines the origin, the destination and the

order in which the intermediate stops to be visited.

¬Non-ordered path finding°User defines the origin, the destination and the

location of the intermediate stops to be visited°The computer determines the order in which the

intermediate stops to be visited

Optimal path finding Non-ordered path finding

Network analysis - partitioning

¬Assign portion of network elements to a location¬A set of criteria or constrains must be defined

to decide if° An element is assigned to a location° To which location it should be assigned

¬Two types of partitioning° Allocation° Trace

Network analysis - partitioning

¬Allocation° Assigns a portion of network to a resource center° The resource center has certain capacity to be distributed

around° The network elements (lines and nodes) have an attribute

representing the consumption of the resource° The resource center is modeled as node and its capacity is

represented as an attribute

¬ Examples:°Water plants and distribution network.° Schools and the service area

Network analysis - partitioning

¬Allocation°The result of allocation is a portion of connected

network dispersed from the center°The extent is defined when all the capacity of the

center is exhausted°User many specify a max. amount of consumption

for each branch of the network paths.

Network analysis - partitioning

Allocation – an example

Network analysis - partitioning

¬Trace°Determines which portion of network is connected

to a trace origin°The line direction is important

Network analysis - partitioning

¬Accessibility°Determine how easily a location can access the

facilities around it°Each activity center is assign an index to reflect its

attraction level°The accessibility operation calculates the

accessibility a location by taking into consideration of both the distance to and the index of each activity center

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