Spatial Analysis and Modeling - PowerPoint PPT Presentation

About This Presentation
Title:

Spatial Analysis and Modeling

Description:

Spatial Analysis and Modeling GEO 442 – PowerPoint PPT presentation

Number of Views:304
Avg rating:3.0/5.0
Slides: 63
Provided by: FAKUL3
Category:

less

Transcript and Presenter's Notes

Title: Spatial Analysis and Modeling


1
Spatial Analysis and Modeling
  • GEO 442

2
1. What is Analysis?
  • The process of identifying a research question
  • Modeling that question
  • Investigating model results
  • Interpreting the results

3
2. What is Spatial Analysis?
  • Same process but with spatial data
  • Example Topological overlay
  • An analysis procedure for determining the spatial
    coincidence of geographic features

4
3. What is modeling?
  • A representation of reality used to
  • simulate a process
  • understand a situation
  • predict an outcome
  • analyze a problem
  • A model is structured as a set of rules and
    procedures

5
4. What is Spatial Modeling?
  • Use geographic data to
  • describe,
  • simulate,
  • or predict real-world problems or systems.

6
3 categories of spatial modeling
  • these can be applied to geographic features
    within a GIS
  • geometric models, distance between features,
    generating buffers, calculating areas and
    perimeters
  • coincidence models, such as topological overlay
  • adjacency models (pathfinding, redistricting, and
    allocation)

7
5. Two spatial models for storing geographic data
  • Raster data model - matrix of square cells
  • Vector data model - data stored as coordinates.
  • Similar, represent a layer or set of geographic
    features like points, lines, and polygons.
  • Different in the way they model or represent
    spatial data.

8
Vector data model
  • Point, line and polygon objects on a map are
    stored as as a collection of x and y coordinate
    pairs in a table.
  • The x and y coordinates represent the points
    distance from an origin point.
  • Points stored as a single pair of x and y
    coordinates
  • Lines, store the x and y coordinates of the
    beginning point (from node) of the line and the
    end point (to node) of the line.
  • Curves or changes in direction - series of x,y
    coordinate pairs, (vertices), at each direction
    change between the beginning point and end point
    of the line.
  • Area (polygon) - enclose it with a line, making
    the beginning and ending points of the line
    equal.
  • Polygons which share a boundary are called
    adjacent.

9
  • The diagram below shows how real-world objects
    can be represented on a computer monitor by x,y
    coordinates.
  • The coordinate pairs 1,5 3,5 5,7 8,8 and 11,7
    represent a line (road)
  • The coordinate pairs 6,5 7,4 9,5 11,3 8,2 5,3 and
    6,5 represent a polygon (lake).
  • The first and last coordinates of the polygon are
    the same a polygon always closes.

10
To keep track of many
features, each is assigned a unique
identification number or tag. Th
en, the list of coordinates for each feature is
associated with the features tag. The objects
you see in a vector theme are actually saved in
the theme table
11
Raster data model
  • Location is the main focus of representing
    geographic features.
  • Earth is treated as one continuous surface.
  • Each location is represented as a cell.
  • Cells are organized into a matrix or rows and
    columns called a grid.

12
  • Each row contains a group of cells with values
    representing a geographic phenomenon.
  • Cell values are numbers, which represent nominal
    data such as land-use classes or elevation.
  • Cells are identified by their position in the
    grid. Notice that in a grid, cells have eight (8)
    neighbors (except those on the outside edges)
    four at the corners and four at the sides.

13
  • Like the vector data model, the raster data model
    can represent discrete point, line and area
    features.
  • A point feature is represented as a value in a
    single cell, a linear feature as a series of
    connected cells that portray length, and an area
    feature as a group of connected cells portraying
    shape.

14
  • Because the raster data model is a regular grid,
    spatial relationships are implicit. Therefore,
    explicitly storing spatial relationships is not
    required as it is for the vector data model.

15
Main component of spatial analyst is the grid
theme (raster data model)
16
6. What is a grid theme?
  • A grid divides geographic space into uniform
    blocks called cells.
  • Used to represent terrain elevation or other
    phenomena that change gradually across a surface.

17
  • Elevation grid looks smooth, but, as the
    zoomed-in graphic at the bottom indicates, it's
    really composed of thousands of small cells. Each
    cell, stores an elevation value for the space it
    covers (about 16,000 square feet per cell for
    this grid.)

18
Two types of grids
  • Integer grids store cell values as integers
  • Floating-point grids store values with decimal
    points

19
7. What is a Surface?
  • Grid themes represent a continuous surface
  • Continuous data, such as elevation or air
    temperature over an area.
  • Surfaces can be represented by models built from
    regularly or irregularly spaced sample points on
    the surface (Interpolation).

20
  • The top graphic below shows a set of sample
    elevation points used to generate a surface
    model.
  • The bottom graphic shows a spatial model actually
    created from the points.

21
8. Using Spatial Analyst Extension
  • Creates, queries, maps and analyzes data that
    form continuous geographic surfaces.
  • Elevation
  • Air temperature
  • Precipitation
  • Chemical concentrations (pollutants)

22
Map Algebra
  • Uses math-like expressions that return numeric
    values to an output grid.
  • Expressions are entered into the Map Calculator
    in the Avenue syntax.

23
Querying Grids
  • Select areas spatially by defining a Boolean
    query based on the values of one or more grid
    themes.
  • Output will be a grid theme with areas that match
    the query given a value of 1 (TRUE) and areas
    that do not match the query given a value of 0
    (FALSE).

24
Classification
  • Ordering a theme's data values into a specified
    number of groups according to a particular
    method.
  • The values in the classified theme are not
    changed in any way.
  • Floating point grid theme - default
    classification method is Equal Interval, can be
    changed to Standard Deviation.
  • Integer grid theme - can be classified by any of
    the five methods available Equal Area, Equal
    Interval, Natural Breaks, Quantile, or Standard
    Deviation.

25
Contours and Surfaces
  • Can create isolines (a line theme) or a
    continuous surface (a grid theme) using a point
    theme of sampled points.
  • Both help analyze continuous change of an
    attribute over space (elevation, temperature,
    soils pH level).

26
Cost surface
  • Grid defining the impedance, friction, or cost to
    move through a cell.
  • Used to determine the least cost path between a
    source and destination (travel time, dollars,
    fuel).

27
Proximity Analysis
  • Analyze the distance between features, find the
    closest feature in another theme
  • Create discreet distance buffers to find features
    within a distance of other features.
  • A buffer is a zone of specified distance around a
    feature.

28
Overlay Analysis
  • Compare two or more themes (layers) to reveal new
    relationships between features in the different
    themes.
  • New grid theme that contains only the features
    that meet the requirements of your query.
  • Map Query - ( Landuse . desc "Agr" ) and (
    Flood Zone 1 )

29
Visualization
  • Visualization techniques are used to create
    topographic and thematic maps, statistical graphs
    and to visually render surfaces.
  • Hillshading - visualization tool to display hills
    and valleys in relief. Calculates the effects of
    illumination on a surface
  • Histograms - another important visualization tool
    available. A histogram is a chart of the
    distribution of cell values in a grid theme.
    Useful to see if the values are skewed to one
    side of the mean or normally distributed.

30
9. Extending - Spatial Analyst Chapters
  • 1. Start ArcView
  • 2. Choose spatial analyst extension (file -
    extensions)
  • 3. Notice how ArcView interface changes
  • 2 new menus (Analysis and Surface)
  • Histogram button
  • Contour tool
  • 4. Navigate to extending ArcView datasets
    (c\extend) to begin exercises
  • 5. Answer questions for Chapters 8 - 14

31
Spatial Analysis
  • In order to solve any problem by Geographic
    information System (GIS) modeling a series of
    steps must be followed
  • These steps are typical for addressing any
    problem with some difference in details for each
    problem domain

32
Spatial Analysis
  • Single layer operations (proximity)
  • Multiple layer operations (Union, Intersect)
  • Network analysis (shortest path)
  • Surface analysis (TIN, Aspect, Slope)
  • Grid analysis (flow direction, diffusion)

33
Steps for Spatial Analysis
  • Establish analysis objectives and criteria
  • Prepare data for spatial analysis (spatial
    attribute)
  • Perform spatial operations (buffering, overlay,
    feature extraction)
  • Perform tabular analysis using arithmetic and
    logical operations

34
Reselect
35
Buffer
36
Intersect
37
Erase
38
Flow chart for database
39
Steps for Spatial Analysis- Continue
  • Evaluate and interpret the results (validity and
    checking by producing plots and reports)
  • Refine the analysis by identifying the
    shortcomings and limitations of the analysis
  • Produce final maps and tabular report of the
    results.

40
Example for spatial analysisFinding suitable
dumping site
  • How can I find a suitable
  • dumping site, that is
  • economically,
  • legally, and
  • environmentally
  • sounded?

41
Find a suitable dumpsite using GIS
Factors to be considered
  • Groundwater contamination
  • Surface water contamination
  • Soil contamination
  • Water and air quality
  • Noise pollution
  • Human health due to methane and carbon
  • Marine environment

42
(No Transcript)
43
Data collection
Spatial Attribute data
  • Geology, Groundwater
  • Rivers, Coastal line
  • Soil, Landuse
  • Airport, Roads
  • Settlements, Hotels

44
Steps for data preparation
45
Feature extraction from a GIS database
  • Feature extraction from a GIS database can be
    done using commands such as CLIP, ERASE,
    IDENTITY, and RESELECT.
  • Logic such as SELECT, ASELECT, NSELECT and
    boolean operators ( , lt gt, gt, lt, gt, lt, EQ,
    NE, GT, LT,GE, LE, CN, IN).
  • These commands can be used to identify areas that
    met the desired criteria.

46
Perform spatial operations
  • Feature extraction from a GIS database (Reselect)
  • Map overlay (Intersect, Union, Mapjoin)
  • Proximity searches (Buffering)

47
Geographical objects
48
Example Project Steps
Spread
Recode
Recode
Recode
Recode
OverLay
49
Produce final maps and tabular report of the
results
50
System design
Suitable zones
Intersect suitable zones for each factor
51
User interaction Select suitable layer for
dumping Geology Rainfall Productivity
Land use B1 2420 2500 Getah C2
2440 4000 Kelapa C3
2460 6000 Padi D3 2480 Pekan
D4
52
Data about geology
53
Screening
54
Example for groundwater selection
55
Confirmation of the selection
56
Suitable groundwater zones
57
Unsuitable zones around rivers
58
Spatial Modelling
  • Step 1 State your research question(s). Then
    create a flowchart to organize the data and
    analyses that you will perform to explore/answer
    your research question(s) (I will give you an
    example flowchart).

59
The following is an example of a research project
with a sample flow chart
  • Your city is looking into alternative energy
    sources that will provide clean and inexpensive
    power for residents. The city has decided to look
    into solar power since coal pollutes, oil may run
    short, nuclear is hazardous.
  • Your data set consists of elevation points and
    power lines.
  • You need to generate a list of criteria in aiding
    you in this siting problem.

60
To do so you use this diagram
61
  • The list of criteria you develop define your
    spatial model.
  • Some spatial analysis problems can be very
    complex, involving many data sets and processing
    tasks.
  • It is often helpful to create a flowchart of the
    analysis to organize the data and tasks.

62
The flow chart outlines the solar energy station
siting model that would be performed in this
research project
Write a Comment
User Comments (0)
About PowerShow.com