GIS_FDP_Final.pdf

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Introduction to Geospatial Technology

• “Everything is somewhere”
• Spatial Technology: GIS, Remote Sensing & GPS
• Remote Sensing & GPS provide input data to GIS
• GIS adds the spatial dimension to almost any piece of
information
Source : http://www.esri.com/base/gis/abtgis/what_gis.html
Spatial Technology Concepts

• System for capturing, storing, analyzing and managing data
which are referenced spatially with the earth.
What is GIS?

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Enviromatics 2008 - Geographical information systems GIS
Elements of a GIS

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The four-components-model of a GIS

Geographic Information
Technologies
• Global Positioning Systems (GPS)
– a system of earth-orbiting satellites which can provide precise (100
meter to sub-cm.) location on the earth’s surface (in lat/long
coordinates or equiv.)
• Remote Sensing (RS)
– use of satellites or aircraft to capture information about the earth’s
surface
– Digital ortho images a key product (map accurate digital photos)
• Geographic Information Systems (GIS)
– Software systems with capability for input, storage,
manipulation/analysis and output/display of geographic (spatial)
information
GPS and RS are sources of input data for a GIS.
A GIS provides for storing and manipulating GPS and RS data.

How to locate?
7

Coordinates
◼Features on spherical surfaces are not easy to
measure
◼Features on planes are easy to measure and
calculate
◼ distance
◼ angle
◼ area
◼Coordinate systems provide a measurement
framework

Coordinates
◼Lat/long system measures angles on
spherical surfaces
◼60º east of PM
◼55º north of equator

Definition of Latitude, f
(1) Take a point S on the surface of the ellipsoid and define
there the tangent plane, mn
(2) Define the line pq through S and normal to the
tangent plane
(3) Angle pqr which this line makes with the equatorial
plane is the latitude f, of point S
O f
S
m
n
q
p
r

Cutting Plane of a Meridian
P
Meridian
Equator
Prime Meridian

Definition of Longitude, l
0°E, W
90°W
(-90 °)
180°E, W
90°E
(+90 °)
-120°
-30°
-60°
-150°
30°
-60°
120°
150°
l
l = the angle between a cutting plane on the prime meridian
and the cutting plane on the meridian through the point, P
P

Input Data for GIS
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How Satellite Images are Acquired?

Input Data: Remote Sensing Image
Source: https://www.ctahr.hawaii.edu/miuralab/projects/makaha/intro_RS.html

Source: https://eo.belspo.be/en/remote-sensing-images

Source: https://www.ctahr.hawaii.edu/miuralab/projects/makaha/intro_RS.html

Spatial Resolution
Source:
https://link.springer.com/chapter/10.1
007/978-3-030-26626-4_1

Spatial Resolution
Source: https://www.sciencedirect.com/topics/earth-and-planetary-sciences/spatial-resolution

Spatial Resolution
Source: https://link.springer.com/chapter/10.1007/978-3-030-26626-4_1

Spectral Resolution
Source: https://ieeexplore.ieee.org/document/8395228

Spectral Resolution
Source: https://www.semanticscholar.org/paper/Hyperspectral-imaging-solutions-for-brain-tissue-Giannoni-
Lange/bdd263fa9ecc9e1c4a8d5b4e9b5aad206775d6b2

Input Data: GPS
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Input Data: GPS

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Steps in a GIS project
1. Data acquisition (paper maps, digital files, remote sensing
data, satellite data, field work),
2. Data preprocessing (preparation, integration, data
conversion, digitising and/or scanning, edge matching,
rectification),
3. Data management (variable selection, data definition,
table design (performance, usability), CRUD
policies/procedures (create: data entry; retrieve: view;
update: change; delete: remove)),
4. Manipulation and analysis (address matching, network
analysis, terrain modelling: slopes, different aspects),
5. Product generation (tabular reports, graphics: maps,
charts).

GIS can
– create maps,
– integrate information,
– visualise scenarios,
– solve complicated problems,
– present powerful ideas, and
– develop effective solutions
Why Use GIS?

How GIS Works?
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3/13/2023 Ron Briggs, UTDallas, GIS Fundamentals
How GIS Works
• A GIS stores information about the world as
a collection of thematic layers that can
be linked together by geography.
• This simple but extremely powerful and
versatile concept has proven invaluable
for solving many real-world problems from
tracking delivery vehicles, to recording
details of planning applications, to
modeling global atmospheric circulation.

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35 Enviromatics 2008 - Geographical information systems GIS
Data Models
• What should a GIS represent?

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Data Models

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Representing Data with Raster and Vector Models
Raster Model
• area is covered by grid with (usually) equal-sized, square cells
• attributes are recorded by assigning each cell a single value based on the
majority feature (attribute) in the cell, such as land use type.
• Image data is a special case of raster data in which the “attribute” is a
reflectance value from the geomagnetic spectrum
– cells in image data often called pixels (picture elements)
• Vector Model
The fundamental concept of vector GIS is that all geographic features in the real
work can be represented either as:
• points or dots (nodes): trees, poles, fire plugs, airports, cities
• lines (arcs): streams, streets, sewers,
• areas (polygons): land parcels, cities, counties, forest, rock type
Because representation depends on shape, ArcView refers to files containing vector data as
shapefiles

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0 1 2 3 4 5 6 7 8 9
0 R T
1 R T
2 H R
3 R
4 R R
5 R
6 R T T H
7 R T T
8 R
9 R
Real World
Vector Representation
Raster Representation
Concept of
Vector and Raster
line
polygon
point

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Vector vs. Raster

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Raster vs. Vector

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Representation of Vector Data as Raster
Data

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The GIS Model: example
roads
hydrology
topography
Here we have three layers or themes:
--roads,
--hydrology (water),
--topography (land elevation)
They can be related because precise geographic
coordinates are recorded for each theme.
longitude
longitude
longitude
Layers are comprised of two data types
•Spatial data which describes location
(where)
•Attribute data specifying what, how
much,when
Layers may be represented in two ways:
•in vector format as points and lines
•in raster(or image) format as pixels
All geographic data has 4 properties:
projection, scale, accuracy and resolution

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Spatial and Attribute Data
• Spatial data (where)
– specifies location
– stored in a shape file, geodatabase or similar geographic file
• Attribute (descriptive) data (what, how much,
when)
– specifies characteristics at that location, natural or human-created
– stored in a data base table
GIS systems traditionally maintain spatial and
attribute data separately, then “join” them for
display or analysis
– for example, in ArcView, the Attributes of … table is used to link a
shapefile (spatial structure) with a data base table containing attribute
information in order to display the attribute data spatially on a map

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Terrain data
Terrain data relates to the 3D configuration of the surface of
the Earth
On the other hand, map data refers to data located on the
surface of the Earth (2D)
The geometry of a terrain is modeled as a 2 ½-dimensional
surface, i.e., a surface in 3D space described by a bivariate
function

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DTMs
In general, a larger
number of sampled
points allows for a
better representation:

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Types of DTMs
• Polyhedral terrain models
• Gridded elevation models
• Contour maps

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TINs
Example of a TIN based on irregularly distributed
data

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RSG: an example

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Digital Contour Maps
A line interporlating points of a contour can be
obtained in different ways
Examples: polygonal chains, or lines described by
higher order equations

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Analyses in GIS

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3/13/2023
RASTER OPERATIONS

RASTER OPERATIONS
➢ A raster GIS must have capabilities for Input of data, various
house keeping functions, operations on layers, output of data and
display layers
Basic Display
➢ Simplest type of values to display are integers
On a colour display , each integer value is assigned a unique
colour (Fig.1)
➢ If the values have a natural order, a sequence of colours is used
(Fig.2)
There must be a legend to explain the meaning of each colour.
Other Types of Display
➢ Display the data as a surface
➢ Contours can be shown through the pixels along the lines of
constant value (Fig.3)
➢ The surface can be shown in oblique-perspective view (Fig.4)

LOCAL OPERATIONS
➢ produce a new layer from one or more input layers
➢ the value of each new pixel is defined by the values
of the same pixel on the input layers(s)
➢ Neighbouring or distant pixels have no effect
➢ Arithmetic operations make no sense unless the
values have appropriate scales of measurement
Regrouping
➢ Is carried out using only one input layer
1. assign a new value to each unique value on the
input layer
➢useful when the number of unique input values is
small

LOCAL OPERATIONS
2. assign new values by assigning pixels to classes or ranges
based on their old values
➢ useful when the old layer has different values in each
cell,
e.g., elevation or satellite images
3. sort the unique values found on the input layer and replace by
the rank of the value
➢ e.g. 0, 1, 4, 6 on input layer become 1, 2, 3, 4 respectively
➢ applications : assigning ranks to computed scores of capability,
suitability etc.
➢ some systems allow a full range of mathematical operations

Overlay Operations
➢ an overlay occurs when the output value
depends on two or more input layers
➢ many systems restrict overlay to two input
layers only (Fig. 5)
Examples :
1. output value equals arithmetic average of
input values
2. output value equals the greatest (or least) of
the input values
3. layers can be combined using arithmetic
operations
4. combination using logical conditions
e.g. if y > 0, then z = 1, otherwise z = 0

Overlay Operations
5. assign a new value to every unique combination of input
values by using cross tables
1 2 3 4
1 1 1 2 2
2 1 1 1 2
3 2 1 1 2

NEIGHBOURHOOD OPEATIONS
The value of a pixel on the new layer is
determined by the local neighbourhood of the
pixel on the old layer
Filtering
A filter operates by moving a "window" across
the entire raster
e.g. many windows are 3x3 cells
➢ the new value for the cell at the middle of the
window is a weighted average of the values in the
window
➢ by changing the weights we can produce
different effects:

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60/80
Convolutions

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61/80
Convolutions
1 0 0 0 0 1
0 1 0 0 1 0
0 0 1 1 0 0
1 0 0 0 1 0
0 1 0 0 1 0
0 0 1 0 1 0
6 x 6 image
1 -1 -1
-1 1 -1
-1 -1 1
Filter 1
-1 1 -1
-1 1 -1
-1 1 -1
Filter 2
…
…
Each filter detects a small
pattern (3 x 3).
Source: https://adeshpande3.github.io/A-
Beginner%27s-Guide-To-Understanding-
Convolutional-Neural-Networks/

NEIGHBORHOOD OPEATIONS
Examples filters:
1.
.11 .11 .11
.11 .11 .11
.11 .11 .11
➢ Replaces each value by the simple unweighted average of it and its
eight neighbouring values
➢ smooths the spatial variation on the layer
2.
0.5 0.5 0.5
0.5 0.6 0.5
0.5 0.5 0.5
➢ slightly smooths the layer
3.
-.1 -.1 -.1
-.1 1.8 -.1
-.1 -.1 -.1
➢ slightly enhances local details by giving neighbours negative
weights

Slopes and aspects
➢ if the values in a layer are elevations, we can compute
the steepness of slopes by looking at the difference
between a pixel's value and those of its adjacent
neighbours
➢ the direction of steepest slope, or the direction in
which the surface is locally "facing", is called its
"aspect“ (Fig. 6)
➢ slope and aspect are useful in analyzing vegetation
patterns, computing energy balances and modeling
erosion or runoff
➢ aspect determines a direction of runoff
➢ it can be used to sketch drainage paths for runoff

OPERATIONS ON EXTENDED
NEIGHBOURHOODS
Distance
➢ calculate the distance of each cell from a cell or the
nearest of several cells
➢ each pixel's value in the new layer is its distance from
the given cell(s)
Buffer zones
➢ buffers around objects and features are very useful GIS
capabilities
➢ e.g. build a buffer of 500 m wide around the road
network
➢ buffer operations can be visualized as spreading the
object spatially by a given distance (Fig. 7)

OPERATIONS ON EXTENDED
NEIGHBORHOODS
➢ the result could be a layer with values :
➢ 1 If in original selected object
➢ 2 If in buffer
➢ 3 If outside object and buffer
➢ Application include noise buffers around roads, safety buffers
around hazardous facilities
➢ In many programs the buffer operation requires the user to first do a
distance operation, then a reclassification of the distance layer
➢ the rate of spreading may be modified by another layer representing
"friction"
➢ the friction layer could represent varying cost of travel. This will
affect the width of the buffer - narrow in areas of high friction, etc.
Visible area or "viewshed“
➢ given a layer of elevation, and one or more viewpoints, compute the
area visible from at least one viewpoint (Fig. 8)
e.g. value = 1 if visible, 0 if not
➢ useful for planning location of facilities such as smokestacks, or
surveillance facilities such as fire towers, or transmission facilities

OPERATIONS ON ZONES (GROUPS OF
PIXELS)
Identifying zones
➢ by comparing adjacent pixels, identify all patches or zones
having the same value
➢ give each such patch or zone a unique number
➢ set each pixel's value to the number of its patch or zone
Areas of zones
➢ measure the area of each zone and assign this value to
each pixel instead of the zone’s number
➢ alternatively output may be in the form of a summary table
Perimeter of Zones
➢ measure the perimeter of each zone and assign this value
to each pixel instead of the zone’s number
➢ alternatively output may be in the form of a summary table
➢ length of perimeter is determined by summing the number
of exterior cell edges in each zone

3/13/2023
PIXELS)
Zonal operations compute a new value for each location of the
existing values from a specified layer that are associated not
(just) with the location itself but with all locations that occur
within its zone on another specified layer (Fig. 9)

PIXELS)
Distance from zone boundary
➢ measure the distance from each pixel to the nearest
part of its zone boundary, and assign this value to the
pixel
➢ boundary is defined as the pixels which are adjacent to
pixels of different values
Shape of zone
➢ measure the shape of the zone and assign this to each
pixel in the zone
➢ one of the most common ways to measure shape is by
comparing the perimeter length of a zone to the square
root of its area
➢ by dividing this number by 3.54 we get a measure
which ranges from 1 for a circle (the most compact
shape possible) to 1.13 for a square to large numbers
for long or thin zones.

COMMANDS TO DESCRIBE CONTENTS OF
LAYERS
One layer
➢ generate statistics on a layer
➢ e.g. mean, median, most common value, other
statistics
More than one layer
➢ compare two maps statistically
➢ e.g. is pattern on one map related to pattern on the
other?
➢ e.g. chi-square test, regression, analysis of variance
Zones on one layer
➢ generate statistics for the zones on a layer
➢ e.g. largest, smallest, number, mean, area

EXAMPLE ANALYSIS USING A RASTER GIS

Objective
Identify erosion prone areas :
An area that satisfies the following criteria:
➢ has high intensity rainfall
➢ has with less soil depth
➢ has less vegetation
➢ has steeper slope
Raster description :
Resolution 100 m, area 0.5 km by 0.5 km
Layer 1 : Slope Map 1 steeper slope 2 lower slope
1 1 1 2 2
1 1 1 2 2
1 1 2 2 2
1 2 2 2 2
1 2 2 2 2

Layer 2 : Soil Depth Map 1 low 2 high
1 1 1 1 2
1 1 1 1 2
1 1 1 2 2
2 2 2 2 2
2 2 2 2 2
Layer 3 : Vegetation Map 1 less 2 more
1 1 1 2 2
1 1 1 2 2
1 1 2 2 2
1 2 2 2 2
1 2 2 2 2
Layer 4 : Rain Fall Map 1 high 2 low
1 1 1 2 2
1 1 2 2 2
1 1 1 2 2
1 1 1 2 2
1 2 2 2 2

ANALYSIS STEPS
Layer 5 : Steep Slope and low soil depth
1 1 1 0 0
1 1 1 0 0
1 1 0 0 0
0 0 0 0 0
0 0 0 0 0
Layer 6 : Low Vegetation and High Rain Fall
1 1 1 0 0
1 1 0 0 0
1 1 0 0 0
1 0 0 0 0
1 0 0 0 0
Layer 7 : Erosion Prone Areas
1 1 1 0 0
1 1 0 0 0
1 1 0 0 0
0 0 0 0 0
0 0 0 0 0

ANALYSIS STEPS
Layer 1:
Slope
Layer 2:
Soil Depth
Layer 3:
Vegetation
Layer 4:
Rain Fall
Layer 5:
Steeper Slope & Low
Soil Depth
Layer 6:
Less Vegetation
& High Rainfall
Layer 7:Erosion Prone Areas
Overlay Overlay
Overlay

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Vector Analysis
▪ Identifies spatial relationship within a layer or
between the spatial layers.
▪ Can be carried out using both spatial and
attribute data.
▪ Vector analysis functions are limited
compared to raster analysis functions.

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Nonspatial Query
▪ Use the attribute data base to select features that
meet certain criteria.
▪ Select the villages in a Block that have at least one
primary school and a bank.
▪ Nonspatial query runs on a single layer.

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Operations Involving Two Layers
➢ Union
➢ Intersect
➢ Symmetrical Difference (XOR)
➢ Identity
➢ Clip
➢ Update
➢ Erase
➢ Split

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Operations Involving Two Layers
(Contd..)
▪ Operations are formed between two different layers
to look at the relationships between them.
▪ As long as these layers share a common coordinate
system, they can be related together.
▪ They can be overlaid and combined to form a new
layer and new table gets generated showing how
these layers are related to each other.

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Point in Polygon Overlay
▪ Input layer is a point layer.
▪ Polygon layer is the overlay layer.
▪ Output layer is a point layer with same input point
features of the input layer but each point is assigned
with attributes of the polygon within which it falls.
1 2
*1
*2
+ A B
=
*1B
*2A

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Line in Polygon Overlay
▪ Input is a line layer.
▪ Overlay layer is a polygon layer.
▪ Output layer contains the same line features as the
input layer but each line feature is dissected by the
polygon boundaries of the overlay layer.
▪ Hence output layer contains more line segments
than the input layer and each line has attributes of
the polygon within which it falls.

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Union
▪ Operates on two layers.
▪ A new polygon layer is created by overlaying
features from two input polygon layers.
▪ Union makes a spatial join.
▪ It is equivalent to ‘or’ Boolean operator.
▪ The output layer contains
➢the contained polygons.
➢attributes of both the layers.
➢Area extent combines the area extents of both input layers

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Union Illustration
1 2
1
2
U 1 2
=
1 2
3 4
Soil2
2
Soil1
1
UID
SID
Slope 2
2
Slope 1
1
UID
SID
Soil 2 & Slope 2
4
Soil 2 & Slope 1
3
Soil 1 & Slope 2
2
Soil 1 & Slope 1
1
Concatenated UID
SID

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▪ It is an overlay operation created by overlaying 2
layers.
▪ A new output layer is created.
▪ Layer 1 can be point or line or polygon layer.
▪ Layer 2 is a polygon layer.
Intersect
Polygon
Polygon
Polygon
Line
Polygon
Line
Point
Polygon
Point
Output Layer
Layer 2
Layer 1

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Intersect Contd.
1
2
1
3
2
4
A
+ =
1B
2A
3A 4A
B
1A
2B
3B

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▪It is equivalent to ‘and’ Boolean operator.
▪The output layer contains only those portions of
features that are in the area occupied by both the
input layers.

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Symmetrical Difference
▪ Operates on two layers.
▪ A new polygon layer is created by overlaying features from
two input polygon layers.
▪ It preserves features that fall within the area extent that is
common to only one of the inputs.
▪ This operator is opposite to intersect in terms of the output’s
area extent. The output is (A U B) - (A ∩ B).
1 2
1 2
1
2
+ A B
=

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Identity
▪ It is an overlay operation created by overlaying 2 layers.
▪ A new output layer is created.
▪ Layer 1 can be point or line or polygon layer.
▪ Layer 2 is a polygon layer.
▪ [(Input layer ∩ Identity layer) U Input Layer].
Polygon
Polygon
Polygon
Line
Polygon
Line
Point
Polygon
Point
Output Layer
Layer 2
Layer 1

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The output layer contains
–all the features of layer 1.
–Those portions of layer 2 features that overlap
layer1 .
Identity Contd.
1
+ =

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Overlay Operations And Topology
▪ All the three operations union, intersect and
identity create new layers and new topology gets
built.
▪ Attribute tables are updated. The attribute table
contains items from both the input layers.
▪ Therefore all items from the input layers’
attribute tables are retained except for the
geometric measures (area and perimeter in the
case of polygon layers).

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Clip
▪ It operates on 2 layers input.
▪ Extracts a part of an input layer that intersects with
the clip layer.
▪ The features of the input layer are retained in the
output layer.

99
Clip Contd.
Input layer Clip layer Output layer
▪The attribute table of the output layer contains
the same attributes as of the input layer.
▪Input layer can be point, line or polygon layer.
▪Clip layer must be a polygon layer.
▪The output layer is of the same feature type as the
input layer.

100
Erase
▪ It operates on 2 layers.
▪ Erase is similar to clip, except that the input layer
features that overlap with erase layer polygons are
erased in the output layer.
▪ Input layer can be point, line or polygon layer.
▪ Erase layer must be a polygon layer.
▪ The output layer is of the same feature type as the
input layer.
▪ When input and erase layers are polygon layers,
interchange of layers give different results.

101
Erase Illustration
Input layer Erase layer Output layer

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Update
▪ It operates on 2 polygon layers.
▪ The features of the input layer are updated with the
features of update layer.
▪ When input and update layers are polygon layers,
interchange of layers give different results.

103
Update Illustration
7 8
9
0 1
3
2
4
1 2
3 4
7
8
9
Input layer Update layer Output layer

104
Split
▪ Split is operated on two layers. Split performs a
series of clip operations on the input layer and
creates multiple output layers.
▪ Each output layer contains only those portions of
input layer features which are overlapped by the
specified polygon of the split layer.
▪ Input layer can be points, line or polygons.
▪ Split layer must be a polygon layer.
▪ The split item is used to determine which polygon of
the split layer will be used to split the input layer.

105
Split Illustration
Before Split
Split layer

106
Single Layer Operations
➢Eliminate
➢Dissolve
➢Buffer

107
Eliminate
▪ It operates on a single layer.
▪ Merges selected polygons with neighboring polygons
that have the largest shared border between them,
or that have the largest area.
▪ Often used to remove sliver polygons created during
an overlay operation of 2 layers.
▪ During overlay operation of 2 layers, the layers have
a nearly perfect boundary match, but not exact
match which creates thousands of thin sliver
polygons.

108
Before Elimination After Elimination
Eliminate Illustration
▪Eliminate command removes these very skinny
polygons (Slivers).
▪The sliver is reassigned to the polygon with which it
shares the longest boundary.

109
Dissolve
▪ It operates on a single layer.
▪ Dissolve merges adjacent polygons or lines which
have the same User ID.
▪ In polygon layer, it removes the segment between
adjacent polygons containing same User IDs.
Operation Output

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▪In the case of segment layer, nodes between segments
are dissolved.
▪Dissolve helps to create a simple layer from a complex
layer.
▪Dissolve can be used to undo an Union operation.
▪Dissolve command can be used to generalize the
unioned layer.

111
Buffer
▪ Buffer creates buffer polygons around specified
features in a layer.
▪ Buffer creates a new polygon layer.
▪ Input layer can be point or segment or polygon
layer.
▪ In a segment or polygon layer, one can create inside
or outside or both side buffers.
▪ Using a single buffer distance, it creates buffer zones
of the same width around the selected features.
▪ Incremental buffers are created for a set of distances
around a selected feature.

112
Line Buffer
Point Buffer
Internal Buffer External Buffer
Illustration

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Spatial Modeling
What is spatial modelling?
▪ It is the process of manipulating and analyzing
spatial geographic data to generate useful
information for solving complex problems.
Why?
▪ It finds the relationship that exist among the spatial
features.

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How to do?
▪Identify the problem.
▪Breakdown (simplify) the problem .
▪Organize the data required to solve the problem.
▪Develop clear and logical flow chart using well
defined operations.
▪Run the model and modify it if necessary.

115
Software for GIS

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Software for GIS
• ArcInfo (Originated commercial GIS, clear market leader),
• Intergraph (Strong in design and facilities mapping, running hard
to match ArcInfo, its main modular GIS environment evolved from
its older CAD products, development of a new generation product
of ist own code named Jupiter based on NT and object technology)
• Bentley Systems (Originally developed the PC-based Micro-
Station product GeoGraphics in cooperation with Bentley Systems,
but split in 1995, have very successfully continued to develop and
sell MicroStation GeoGraphics)
• Autodesk’s AutoCAD Map (Dominant CAD supplier and
software company, fully topological AutoCAD Map since 1996,
illustrates convergence of CAD/GIS, many industrial applications
of AutoCAD for mapping)

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Software for GIS
• Graphic Data Systems (Originated as McDonnel-Douglas in-house
system, industrial applications, visualisation of technical products, now
mapping the environment)
• ERDAS/Imagine, ER MAPPER, PCI, Envi (Origins in remote sensing
raster and vector data, new satellite data products, ER MAPPER
originating in Australia, PCI originating in Canada)
• GRASS (Public domain software, raster oriented with some vector
routines, but 1996 end of development and support announced),
• SICAD (Comparable with ArcInfo, powerful GIS with a lot of
functionalities for raster and vector data, object oriented database)
• IDRISI (Comparable with ArcInfo, but not so powerful),
• MapInfo (Small GIS, useful for planning purposes, easy to handle)

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GIS_FDP_Final.pdf

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