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am WFM 6202: Remote Sensing and GIS in Water Management

Dr. Akm Saiful Islam

[Part-B: Geographic Information System (GIS)]

Lecture-2: Data Model and Structure

December, 2007

Institute of Water and Flood Management (IWFM)Bangladesh University of Engineering and Technology (BUET)

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am 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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am Vector and Raster Model

Vector modelRaster model

256 color more colors

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am Example of vector based model

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Raster model

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.

Cell value - Each cell has a value. Raster model, otherwise known as a raster dataset (image), in its simplest form is a matrix (grid) of cells.

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am Comparison of Raster and Vector Data Model Advantages

Raster model Vector model1. 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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Raster model Vector model1. 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.

Comparison of Raster and Vector Data Model

Disadvantages

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Vector data model:Geometry 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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am 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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am Topological of Vector dataRelationship 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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am The data structure of a point coverage

ID x, y1 2,92 4,43 2,24 6,2

1(2,9)

3(2,2)

2(4,4)

4(6,2)

Point List

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am Building Topology: (See also Figure 3.9)

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100 11 2

101102

104

103

3

1

5

74

12

13 14

6

15

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 1012 100 1023 100 1034 102 1015 103 1026 103 1017 102 104

Polygon # Arc #

101 1,4,6

102 4,2,5,0,7

103 6,5,3

104 7

Arc# x,y coordinates1 (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)

Polygon/Arc List

Arc-coordinate listLeft/right list

Figure 3.9

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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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- 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

Topological features of Raster Data

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Example of Raster boundary

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am 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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am 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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am Overlay of Spatial data layers

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

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am ESRI’s models• Shapefiles – 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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am 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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am Triangulated Irregular Network (TIN)

TIN

TIN & Contour

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.

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am 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 triangle’s 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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am 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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am 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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am Region and polygon -2Another 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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am 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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RouteIn 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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am 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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am 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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am 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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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.

Example of Route Hydrologists and ecologists use linear referencing on

stream networks to locate various types of events

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am 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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am 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.