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PLAN 281 Final > Lecture 6 - Vector Analysis > Flashcards

Lecture 6 - Vector Analysis Flashcards

1
Q

What is the objective of spatial analysis?

A

To transform data into useful info to satisfy the requirements/objectives of decision-makers at all levels of detail
- helps us identify data trends, create new relationships from data, view complex relationships b/w data sets, make better decisions

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2
Q

What are the components of spatial analysis?

A
  • possible input: tabular attribute data, spatial data/layers, combo of spatial and tabular
  • possible output: maps/map features, charts, table
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3
Q

What are the challenges of geographic analysis?

A
  • lots of data
  • spatial relationships difficult to measure
  • inherent uncertainty due to scale
  • difficult to make data sources compatible
  • multiple objectives
  • quantity vs. quality
  • GIS can address some but not all difficulties
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4
Q

What is a query?

A

The selective display and retrieval of info from a database

- ability to query and retrieve data based on some user-defined criteria necessity in GIS

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5
Q

What are the 2 types of queries?

A
  1. Attribute
  2. Spatial
    - combo: powerful way of exploring data patterns
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6
Q

Explain attribute queries

A
  • select features using attribute data (using SQL)
  • results can be mapped or presented in conventional database form
  • can be used to produce maps of subsets of data or choropleth maps
  • based on unique structure of DBMS (relational is RDBMS)
  • uses external databases (large amounts stored in non-GIS databases)
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7
Q

Explain spatial queries

A
  • allow us to examine locational relationships b/w 2 data sets
  • clicking on features on the map to find out their attribute values
  • GIS can perform geometric queries (ex. by point, circle, rectangle, etc.)
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8
Q

What is SQL?

A

Structured Query Language

  • programming language designed for retrieval and management of data in RDBMS
  • provides tools needed to manage RDBMS (creating tables, adding data, queries/searches)
  • provides a standard for GIS software
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9
Q

Give examples of some SQL commands

A 
ex. used LIKE
Others:
- select, where (query)
- insert, delete, update (editing)
- create table (management)
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10
Q

What are the limitations of attribute-based queries?

A
  • cannot answer important geographical questions (must combine with spatial queries)
  • ex. what land parcels are adjacent to the site with contaminated soil?
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11
Q

Explain Boolean operators

A
  • used to combine search terms to construct more complex searches in a database
  • AND: intersection of two sets (just the overlap) - ex. snow and ice
  • OR: yields union of two sets (all of both sets) - ex. snow or ice
  • NOT: yields exclusion of one set (even overlap is excluded) snow not ice
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12
Q

Explain measurements

A

Different types

  • diff b/w 2 points
  • area

Tedious and inaccurate by hand - use GIS tools
- measurements often made on horizontal projections of objects

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13
Q

What is buffering?

A

A transformation

  • creates new objects/attributes (polygon) based on simple rules (involves simple geometric, arithmetic, or logical rules; may create new fields from existing fields of discrete objects)
  • summarizes distance or proximity by creating distance buffers around selected features (points, lines, or areas)
  • possible in both raster and vector formats
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14
Q

What is overlay?

A
  • series of operations performed on spatial data in different layers (new layers of data produced; most required GIS technique)
  • joins two layers to create a new layer (output contains both the spatial and attribute data from both input layers)
  • map features and associated attributes are integrated to produce new composite maps
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15
Q

What are the 2 aspects of vector overlay?

A
  1. Geometric (shapes of everything)

2. Attribute Management (data merged; resulting table is combo of attributes)

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16
Q

What is a point-on-polygon overlay?

A

Determines whether a point lies inside or outside polygon

  • overlay point objects on areas (“is contained in” relationship)
  • result in new attribute for each point
  • ex. combine wells and planning districts
17
Q

What is a line-on-polygon overlay?

A

Determines what line sections lie within specific polygons

  • overlay line objects on area objects
  • lines are broken at each area object boundary; containing area has new attribute of each output line
  • ex. what rivers and streams portions lie in counties?
18
Q

What is a polygon-on-polygon overlay?

A

Determines what areas in dataset A lie within specific polygons of dataset B

  • overlays 2 layers of area objects
  • boundaries broken at each intersection
  • number of output areas likely greater than number of input areas
  • ex. input watershed boundaries and county boundaries
19
Q

What are the issues with overlay?

A

Spurious polygons

  • during polygon overlay, many new and smaller polygons are created, some of which may not represent true spatial variations (results from overlaying diff versions of the dame line)
  • able to set a tolerance value for deleting spurious polygons
  • can be confusing and inaccurate
  • ex. road may be part of county boundary but also boundary b/w two fields
20
Q

What is a network?

A

Interconnected arcs that comprise a set of features through which resources flow

21
Q

What is a network analysis?

A

Uses topological relationships to represent and analyze flows along a set of interconnected paths

  • based on connectivity, impedance, and direction of flow on arc
  • ex. road network
22
Q

What interconnecting logical components are network models based on?

A
  • nodes: defines start, end, and intersections
  • chains: line features joining nodes
  • links: join together points to make up a chain
23
Q

What are some examples of network analysis applications?

A
  • routing (buses)
  • flow tracing (pollutant dispersion
  • allocation functions (facility location
  • facilities management (phone, computer network, etc.)
24
Q

What are 3 types of network analyses?

A
  1. Network routing
  2. Route tracing
  3. Network location-allocation
25
Q

Explain network routing

A
  • shortest path b/w 2 points (direction instructions, bus routing, deliveries, etc.)
26
Q

Explain route tracing

A
  • trace flows of goods, people, info through network (especially uni-directional flows)
  • ex. model downstream pollutant
27
Q

Explain network location-allocation

A
  • provision of service to satisfy spatially dispersed demand
  • allocate arcs to nearest supply centre and draw boundaries to define service areas
    Two problems:
  • location: where to put central facilities
  • allocation: which subsets of demand should be served from each site
28
Q

How can we represent field-based (continuous) phenomena/surfaces within vector data model?

A
  1. Sample real world surface

2. Rep field-based surface using vector objects

29
Q

Explain sampling for continuous surface rep.

A
  • sample field variables by recording value at limited number of locations
  • interpolation: estimate new values from neighbouring point locations to create a continuous surface
  • IDW
30
Q

Explain how IDW is used for sampling continuous surfaces

A
  • inverse distance weighing estimates interpolated cell values by averaging values of sample data points in neighbourhood of each processing cell
  • more influence/weight by points closer to estimate cell
  • issue: uneven distribution of sample points, boundaries, etc.
31
Q

Explain representing field-based surfaces in vector GIS

A
  • isolines are lines that connect points of equal value (contour for equal elevation, isotherms for equal temp)
  • interpolate contour lines based on values of point sample
32
Q

What factors are useful in modelling surfaces?

A
  • slope: steepness
  • aspect: compass direction
  • visibility: line of sight b/w 2 points
33
Q

Explain the TIN model

A

Triangulated Irregular Network

  • hybrid vector model (construct elevation surface from set of irregularly spaced data points)
  • created by linking neighbouring points to form an irregular triangular lattice
  • each triangle stores: list of nodes, list of neighbouring triangles, slope & aspect, and able to interpolate elevation within triangle
34
Q

How are TINs generated?

A

Via Delaunay triangles

  • polygons generated from a point layer
  • all sample points connected with 2 nearest neighbours to form triangles
  • divides space between points as evenly as possible
  • elevation, slope, and aspect of triangle calculated from heights of 3 corners
  • DTs as near equiangular as possible, and longest side is as short as possible (minimizes interpolation distances)
35
Q

What are the advantages of the TIN model?

A
  • few data points required
  • records more data for areas of complex relief
  • captures discontinuities well (ex. ridges)
  • slope and aspect easily recorded
36
Q

What are the disadvantages of the TIN model?

A
  • requires significant processing power to generate

- difficult to combine with other map layers via overlay (lots of polygons involved)

PLAN 281 Final (10 decks)

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