Introduction to Raster GIS

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UST/ENV/PAD/PDD 643/743Advanced Geographic
Information Systems
Lecture04 3D GIS and Visualization
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Classification of Surfaces in the GIS World

• DISCRETE SURFACES
• consist of 2.5 dimensions
• only one z-value is associated with each x-y
  location
• spatially discrete with feature boundaries
• faceted transition across geographic space
• abrupt breaks are common
• e.g. parcel boundaries

• CONTINUOUS SURFACES
• consist of 2.5 dimensions
• only one z-value is associated with each x-y
  location
• not spatially discrete
• smooth transition across geographic space
• generally no abrupt breaks seen
• e.g. elevation, income, pH

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Continuous and Discontinuous Surfaces
CONTINUOUS SURFACES each x-y location has the
same Z-value as you approach the location from
any direction
DISCONTINUOUS SURFACES the x-y location has a
different Z-value as you approach the location
from the left or the right
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Surfaces in Raster GIS

• In Raster GISs, since space is quantized into
  discrete units or locations and each raster can
  be associated with a Z-value
• the Z-value is most representative for the
  entire grid cell
• Raster data structures easily represent surface
  data

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Surfaces in Vector GIS

• in Vector GISs, space between features is
  implied
• to define the space explicitly as a surface,
  the space must be quantized in a way that
  retains major changes in Z-values and yet imply
  areas of identical Z-values
• this is done by describing the surface as a set
  of facets that are smooth faces connected by
  points and lines that show changes in the
  structure of the surface
• the surface is therefore modeled by regularly
  or irregularly placed points that act as
  vertices
• each point has an explicit topographic value
• any three points can be connected to form a
  planar surface
• these points form a Triangulated Irregular
  Network or TIN

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Triangulated Irregular Networks (TINs)

• TIN Defined
• a set of adjacent non-overlapping triangles
  computed from irregularly spaced points with x,
  y and z values
• Uses of TINs
• to create, store, analyze and display surface
  data
• to facilitate terrain analyses
• to perform visibility and viewshed analyses
• Z-value interpolation

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Advantages and Disadvantages of TINs

• Advantages of TINs
• varying resolutions in the same TIN file
• higher detail in areas where the surface is
  more complex
• linear features like roads and streams can be
  modeled accurately by constraining them to be
  triangle edges
• good for large-scale, detailed applications
• Disadvantages of TINs
• expensive to build
• time-intensive during processing
• obtaining base data is more cumbersome
• bad for small-scale, regional applications

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TINs Data Structure
P03
P02
T3
T4
P04
T2
P05
P06
T1
T5
T6
T8
T7
P01
P07
P08
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TINs Terminology
Mass Point The individual point of a
triangle Breakline linear feature represented as
a sequence of one or more triangle edges Polygon
features a closed sequence of three or more
triangle edges Replace Polygon boundary and
interior heights will be assigned one constant
Z-value Erase Polygon all areas within polygon
will be ignored in analytical operations Clip
Polygon all areas outside polygon will be
ignored in analytical operations Fill
Polygon all triangles falling inside this
polygon are assigned an integer value Line and
Polygon features can be tagged hard or soft
-- a hard line roads, streams, shorelines
indicates a significant change in slope
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Mass Points in TINs (Graphic)
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Lines in TINs (Graphic)
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Breaklines in TINs (Graphic)
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Rendered Triangles of Facets in TINs (Graphic)
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Close-Up View a TIN with Mass Points, Lines, and
Rendered Facets (Graphic)
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TIN Lines in 3D
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Rendered TIN Faces in 3D
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TINs Capabilities

• Surface Display in perspective or panoramic
  views
• Interpolation of Z-values
• Contour Generation
• Calculation of Slope and Aspect
• Calculation of Surface Area and Surface Length
• Volume and Cut and Fill Analyses
• Profile Generation
• Visibility Analyses
• Analytical Hillshading
• Analysis of Surface Runoff Patterns

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Interpolation of Surface

• Inverse Distance Weighted IDW
• assumes each input point has a local influence
  that diminishes with distance
• points closer to the processing cell are
  weighted heavier
• Spline
• general-purpose interpolation method that fits
  a minimum curvature surface through all the
  input points
• similar to bending a rubber sheet to pass
  through all the points
• good for continuous data like elevation, water
  table, pollution concentrations
• Kriging
• assumes that distance and direction between
  sample points are spatially correlated and can
  be used to explain variation in Z-values
• good for cases where you know that the data is
  definitely correlated
• used in mining and geosciences
• Trend
• fits a mathematical polynomial of specified
  order to all input points
• uses OLS, minimizing variance in relation to
  the input points

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Surfaces and Three Dimensional Visualization
Analytical Surfaces GRIDs and TINs can be used
to form analysis surfaces These surfaces can
then be used to visualize the data in three
dimensions Pollution Concentration or Water
Tables can thus be modeled and visualized across
geographic space Base Surfaces GRIDs and TINs
can also be used to form base surfaces Other
features, usually vector data sets can be
placed on these surfaces Buildings can be
extruded to give them block effects The
extruded buildings can then be placed on the
surface for a better understanding of massing
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Draping Vector Features over Surfaces (Graphic)
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Massing and Visualization Extruded Buildings
over a Surface (Graphic)