Vector analysis - introduction Spatial data management operations - Assembling datasets for analysis. Data management operations



Transform (reproject)

Merge

Append



Clip

Dissolve

The role of topology in GIS analysis

Vector analysis - introduction

Spatial data management operations

- Assembling datasets for analysis

Data management operations

Transform - ‘reproject’

GIS can project layers ‘on the fly’ for display via the dataframe Analysis usually requires all layers in the same projection

Define and reproject to one standard system

Merge

merge -> new layer

They can be points, lines or polygons but both must be the same feature type

FME – Feature Manipulation Engine can be used to merge data

Merge

Append

append

-> existing layer

They can be points, lines or polygons but both must be the same feature type They could include adding features to an existing dataset

e.g. extra streams, trails to roads….

Like a jig-saw, the pieces must fit (spatially) and the

(picture) attributes match

Ensure you still have the attributes after merge or append … (you may lose them if the parts don’t match)

Example of mismatching attributes: contour lines in feet versus metres (Northern BC – NTDB data) …. only evident in size of elevations

DEM ‘jumps’ across mapsheets

Elevation (Feet) Elevation (Metres)

In attribute table (old map sheet), add a new field, name it new-elev In the field calculator, new-elev = elevation * .3048

Drop (delete) elevation field Rename new-elev to elevation

Raster clip: define rectangle outline Top left, bottom right (coordinates)

‘Cookie cutter’ -

Vector (or raster) clip

Create a new shapefile and draw a hollow polygon – 4 corners, with mouse or enter coordinates

Or use an existing shapefile e.g. park boundary or forest district

http://www.brocku.ca/maplibrary/procedures/Arcmap_clip/arcmap_clip.htm

ArcMap: Clip vectors using zoom and select by location

Dissolve:

Multipart features

Dissolve can result in multipart features being created. A multipart feature is a single feature that contains noncontiguous elements and is represented in the attribute table as one record.

Dissolve lines

Lines may have many ‘pseudo-nodes’ from digitising or appending

Cause: multiple map sheets, digitising sessions, operators Effects: slower processing, partial line distances

– A systematic examination of a problem or

complex entity in order to provide new

information from what is already known

(ESRI – GIS Dictionary)

– Spatial analysis adds value to data, supports

decisions and reveals patterns

(www.mimu.com)

– Spatial analysis is the process by which we turn

raw data into useful information.

• Two broad categories

– Spatial data analysis (= geo-processing)

– Tabular (attribute) data analysis

• Spatial analysis is the cornerstone of a GIS and

separates it from other mapping or CAD systems

• Tabular data analysis can be performed within any

DBMS (Database Management System)

Data analysis

• When performing analysis we are considering one of 5 questions

– Location

• What is at …?

– Condition

• Where is it … ?

– Patterns

• What spatial pattern exists ..?

– Trends

• What has changed since ..?

– Modeling

Tabular / Attribute queries

• Queries involve tools or commands to retrieve

information from a set of objects (layers, tables)

• Within a GIS, there are two basic types of queries

– Selection (Identify) Query

• Select specific records from a set of data

– Definition (Condition) Query

• Selects a more specific set of data by hiding other

features which are in turn excluded from drawing

• Manual selection of data – Shows location

and information about the feature.

• A basic query is performed to select data using

• Logical (relational) Operators:

2. Condition –(where / select by attribute)

= EQ Equal <> NE Not equal > GT Greater than < LT Less than

>= GE Greater than or equal to <= LE Less than or equal to IN {1->200} Between the values of

CN ' ' Contains the character string in the quotes

– “Species” = ‘Earthling’

– “Name” <> ‘Spock’

– “Age” > 120

– “Name” cn ( ‘Spock’, ‘Kirk’, ‘Scotty’)

– “Distance” in 200 and 500

• Can be used to combine conditions …

• Boolean Logic

• Create an expression reducible to a true or false condition

– And (narrows the selection) – Or (expands the selection)

Boolean operators

Boolean logic shown in Venn diagram

Boolean Operators

AND (a AND b) OR (a OR b)

NOT (a NOT b)

XOR (a OR b but not both)

type = pine AND age > 100 ... selects all old growth pine

type = pine OR age > 100 selects all pine and any type older than 100

It may require the use of brackets to avoid ambiguity in complex queries e.g.

type = pine OR type = fir AND age > 100 selects any pine plus old growth fir type = (pine OR type = fir) AND age > 100 selects old growth (pine and fir)

• Selects features from one data set based on

their relationship with another layer

– Are within a distance of

– Are within

– Are completely within

– Share a line segment with

– Intersect

SPATIAL ANALYSIS

Condition – Select by location

• One of the most important concepts in a GIS

- defined as the spatial relationship between entities

– Adjacency (polygons)

– Containment

(e.g. points in polygons)

– Connectivity (lines)

Spatial analysis requires Topology

Vector analysis relies on these topological relationships

data should be ‘topological’ not ‘spaghetti’ (e.g. raw TRIM data)

• Critical in GIS due to the need to explore spatial

relationships between features in the landscape

Examples ….

– Which parcels are adjacent to which

– Which roads are connected to which

– Which wells fall within a certain municipality

– Which streams are in a watershed

Converting lines to polygons

Left bank Right bank

Slivers between polygons