WFM 6202: Remote Sensing and GIS in Water Management

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WFM 6202 Remote Sensing and GIS in Water
Management
Part-B Geographic Information System (GIS)
Lecture-2 Data Model and Structure

• Dr. Akm Saiful Islam

Institute of Water and Flood Management
(IWFM) Bangladesh University of Engineering and
Technology (BUET)
May, 2009
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Data Model

• A set of guidelines to convert the real world
  (called entity) to the digitally and logically
  represented spatial objects consisting of the
  attributes and geometry.
• Types of geometric data model
• Vector Model
• Model uses discrete points, lines and areas
  corresponding to discrete objects with name or
  code number of attributes
• Raster Model
• - Model uses regularly spaced grid cells in
  specific sequence. An element of grid cell is
  called a pixel (picture cell)

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Vector and Raster Model
Vector model
more colors
256 color
Raster model
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Example of vector based model
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Raster model
Raster model, otherwise known as a raster dataset
(image), in its simplest form is a matrix (grid)
of cells.
Cell value - Each cell has a value.
Cell size- Each cell has a width and height and
is a portion of the entire area represented by
the raster
Cell location - The location of each cell is
defined by its row or column location within the
raster matrix.
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Example of raster representation
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Comparison of Raster and Vector Data Model
Advantages
Raster model Vector model
1. It is a simple data structure 1. It provides a more compact data structure that the raster model
2. Overlay operations are easily and efficiently implemented 2. It provides efficiently encoding of topology and as result more efficiently implementation of operation such as network analysis
3. High Spatial variability is efficiently represented in raster format 3. The vector model is better suited to supporting graphics that closely approximate Hand-drawing maps
4. The raster format is more or less required for efficient manipulation and enhancement of digital images
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Comparison of Raster and Vector Data Model
Disadvantages
Raster model Vector model
1. It is less compact therefore data compression techniques can often overcome this problem. 1. It is a mode complex data structure.
2. Topological relationships are more difficult to represent. 2. Overlay operations are more difficult to implement.
3. The output of graphics is less aesthetically pleasing because boundaries tend to have a blocky appearance rather than the smooth lines of hand-drawn maps. 3. The representation of high spatial variability is inefficient.
4. Manipulation and enhancement of digital images cannot be effectively done in vector domain.
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Vector data modelGeometry and Topology

• Geometry
• Spatial objects are classified into
• point object such as meteorological station,
• line object such as highway and
• area object such as agricultural land,
• which are represented geometrically by point,
  line and area respectively
• Topology
• refers to the relationships or connectivity
  between spatial objects

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Geometry of Vector Data

• - is given by point, line and area objects
• Node
• an intersect of more than two lines or strings,
  or start and end point of string with node number
  
• Chain
• a line or a string with chain number, start and
  end node number, left and right neighbored
  polygons
• Polygon
• an area with polygon number, series of chains
  that form the area in clockwise order (minus sign
  is assigned in case of anti-clockwise order).

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Topological of Vector data

• Relationship between nodes and chains, the
  following topology should be built.
• Chain Chain ID, Start Node ID, End Node ID,
  Attributes.
• Node Node ID, (x, y), adjacent chain IDs
  (positive for to node, negative for from node).
• For relationship between polygons the following
  additional topology need to be built
• Chain geometry Chain ID, Start Coordinates,
  Point Coordinates, End Coordinates.
• Chain topology Chain ID, Start Node ID, End
  Node ID, Left Polygon ID, Right Polygon ID,
  (Attributes).
• Polygon topology Polygon ID, Series of Chain
  ID, in clockwise order (Attributes).

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The data structure of a point coverage
Point List
ID x, y
1 2,9
2 4,4
3 2,2
4 6,2
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Building Topology (See also Figure 3.9)
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Assignment-1

• Find the of Figure 3.9
• Topology of node
• Topology of chain
• Topology of polygon
• Chain geometry
• Submitted by
• next class

c
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Arc L-poly R-poly
1 100 101
2 100 102
3 100 103
4 102 101
5 103 102
6 103 101
7 102 104
Arc x,y coordinates
1 (1,3) (1,9) (4,9)
2 (4,9) (9,9) (9,6)
3 (9,6) (9,1) (1,1) (1,3)
4 (4,9) (4,7) (5,5) (5,3)
5 (9,6) (7,3) (5,3)
6 (5,3) (1,3)
7 (5,7) (6,8) (7,7) (7,6) (5,6) (5,7)
Arc-coordinate list
Left/right list
Polygon Arc
101 1,4,6
102 4,2,5,0,7
103 6,5,3
104 7
Figure 3.9
Polygon/Arc List
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Topological Relationships between Spatial Objects
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Geometry of Raster Data

• - is given by point, line and area objects
• Point objectsA point is given by point ID,
  coordinates (i, j) and the attributes
• Line objectA line is given by line ID, series of
  coordinates forming the line, and the attributes
• Area objectsAn area segment is given by area ID,
  a group of coordinates forming the area and the
  attributes.

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Topological features of Raster Data

• - One of the weak points in raster model is the
  difficulty in network and spatial analysis as
  compared with vector model.
• Boundary
• Boundary is defined as 2 x 2 pixel window that
  has two different classes
• Node
• A node in polygon model can be defined as a 2 x 2
  window that has more than three different classes

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Example of Raster boundary
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Attributes

• Attributes are often termed "thematic data" or
  "non-spatial data", that are linked with spatial
  data or geometric data.
• An attribute has a defined characteristic of
  entity in the real world.
• Attribute can be categorized as normal, ordinal,
  numerical, conditional and other characteristics.
  
• Attribute values are often listed in attribute
  tables which will establish relationships between
  the attributes and spatial data such as point,
  line and area objects, and also among the
  attributes

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Layers

• Spatial objects in digital representation can be
  grouped into layers.
• For example, a map can be divided into a set of
  map layers consisting of contours, boundaries,
  roads, rivers, houses, forests etc.

Map Layers
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Overlay of Spatial data layers

• Two different object layers can be overlaid which
  can result another layers

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ESRIs models

• Shape files as non-topological data format.
  Shape file treats points are pair of x, y
  coordinates, a line as a series of points and a
  polygon as a series of lines.
• Can be displayed more rapidly on monitors.
• Interoperable among other software.
• Coverage as topological based vector data
  format. A coverage can be point coverage, line
  coverage or polygon coverage.
• Connectivity Arcs connect to each other at
  nodes.
• Area definition An area is defined by a series
  of connected arcs.
• Contiguity Arcs have directions and left and
  right polygons

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Data models for composite features

• TIN Triangulated irregular network data model
  approximates the terrain with a set of
  non-overlapping triangles.
• Regions is defined here as a geographic area
  with similar characteristics. A coverage feature
  class that can represent a single area feature as
  more than one polygon.
• Routes - is a line feature such as highway, a
  bike path, or a stream but unlike other linear
  features, a route has a measurement system that
  allows linear measures to be used on a projected
  coordinate system.

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Triangulated Irregular Network (TIN)

• Triangulated irregular network. A vector data
  structure used to store and display surface
  models.
• A TIN partitions geographic space using a set of
  irregularly spaced data points, each of which has
  an x-, y-, and z-value.
• These points are connected by edges into a set of
  contiguous, non-overlapping triangles, creating a
  continuous surface that represents the terrain.

TIN
TIN Contour
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Components of TIN

• The nodes originate from the points and line
  vertices contained in the input data sources.
  Every node is incorporated in the TIN
  triangulation. Every node in the TIN surface
  model must have a z value.
• Every node is joined with its nearest neighbors
  by edges to form triangles which satisfy the
  Delaunay criterion. Each edge has two nodes, but
  a node may have two or more edges. Because edges
  have a node with a z value at each end, it is
  possible to calculate a slope along the edge from
  one node to the other.
• Each triangular facet describes the behavior of a
  portion of the TIN's surface. The x,y,z
  coordinate values of a triangles three nodes can
  be used to derive information about the facet,
  such as slope, aspect, surface area, and surface
  length.
• The hull of a TIN is formed by one or more
  polygons containing the entire set of data points
  used to construct the TIN. The hull polygons
  define the zone of interpolation of the TIN.
  Inside or on the edge of the hull polygons, it is
  possible to interpolate surface z values, perform
  analysis, and generate surface displays. Outside
  the hull polygons, it is not possible to derive
  information about the surface. The hull of a TIN
  can be formed by one or more polygons which can
  be non-convex.

Nodes
Edges
Triangles
Hull
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Delaunay Triangulation for TIN

• A method of fitting triangles to a set of points.
  The triangles are defined by the condition that
  the circumscribing circle of any triangle does
  not contain any other points of the data except
  the three defining it.
• It is a method which produces triangles with a
  low variance in edge length. The resulting
  triangles may be used as an irregular
  tessellation for interpolation of other points on
  a surface.

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Region and polygon -1

• Polygons do not overlap and completely cover the
  area being represented (do not contain any void
  areas).
• In a region, the polygons representing geographic
  features can be freestanding, they can overlap,
  and they need not exhaust the total area.

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Region and polygon -2

• Another premise of polygons is that each
  geographic feature is represented by one polygon.
  
• This is extended for regions, so that a single
  geographic feature can be represented by several
  polygons.

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Region and polygon -3

• As with points, lines, and polygons, each region
  is given a unique identifier. As with polygons,
  area and perimeter are maintained for each
  region.
• Constructing regions with polygons is similar to
  constructing polygons from arcs. Whereas a
  polygon is a list of arcs, a region is simply a
  list of polygons. One important distinction
  exists the order of the polygons is not
  significant.

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Route
In ArcGIS, the term route refers to any linear
feature, such as a city street, highway, river,
or pipe, that has a unique identifier and a
common measurement system along each linear
feature.
A collection of routes with a common measurement
system is a route feature class. Each route in
the feature class will also have a unique
identifier. Line features with the same unique
identifier are considered to be part of the same
route
Route feature classes are created and managed as
line feature classes in the geodatabase. You can
also use route feature classes from ArcInfo
coverages and polyline shapefiles that include
route identifiers and measured features.
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Point events along Route

• Point events occur at a precise point location
  along a route. Accident locations along highways,
  signals along rail lines, bus stops along bus
  routes, Wells or gauging stations along river
  reaches, pumping stations along pipe lines,
  Manholes along city streets and valves along
  pipes are all examples of point events. Point
  events use a single measure value to describe
  their location.

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Line events along Route

• Line events describe portions of routes. Pavement
  quality, salmon spawning grounds, bus fares, pipe
  widths, and traffic volumes are all examples of
  line events. Line events use two measure values
  to describe their location.

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Polygon events along Route

• Locating polygon features along routes computes
  the route and measure information at the
  geometric intersection of polygon data and route
  data. Once polygon data has been located along
  routes, the resulting event table can be used,
  for example, to calculate the length of route
  that traveled through each polygon.

• Examples
• Soils, spillways, areas of inundation, or hazard
  zones along river reaches
• Wetlands, hazard zones, or town boundaries along
  highways

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Example of Route

• Hydrologists and ecologists use linear
  referencing on stream networks to locate various
  types of events

• The route feature class for streams provides
  measures along the streams using river reach
  mile.
• Point and line event tables record the route ID
  and location along each river reach.
• These event tables can be used to locate point
  and line events.

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Route system

• A collection of routes with a common system of
  measurement is called a route system. Route
  systems usually define linear features with
  similar attributes. For example, a set of all bus
  routes in a county would be a route system.
• Many route systems can exist within a single
  coverage. For example, school bus, truck, and
  ambulance route systems could exist in a coverage
  of a city.
• Route systems are built using arcs, routes, and
  sections, and can accurately model linear
  features without having to modify the underlying
  arc-node topology.
• The route below is defined using four arcs.
  Notice how the route's endpoints fall along the
  arcs. Routes need not begin and end at nodes.
• Sections, as shown below, are the arcs or
  portions of arcs used to define each route. They
  form the infrastructure of the route system.
• The diagram below shows an example of attributes
  containing distance measurements, such as
  milepost numbers or addresses, which can be used
  to locate events, such as accidents or pavement
  quality.

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Dynamic segmentation

• Dynamic segmentation (DynSeg) is the process of
  computing the map location (shape) of events
  stored in an event table.
• Dynamic segmentation is what allows multiple sets
  of attributes to be associated with any portion
  of a linear feature.