Geoinformatics(nce 402)

GEOINFORMATICS(NCE 402)
By- Md Mozaffar Masud
Assistant Professor
Civil Engineering Department
JIT, Barabanki

INTRODUCTION
 Aerial photography is defined as art of taking
photograph from a point in the air for the purpose of
making study on earth surface.
 Aerial photography and its planning includes
selection of types of aero plane and camera, film and
filter combination which is of great importance in
photo interpretation.
 Most of the conventional aerial photography is done
at 1:30000 to 1:60000 scale on a conventional black
and white panchromatic film.

INTRODUCTION
 For more specific and detailed information such as
ground water surveys, land use planning , mineral
exploration, photographs of scale 1:10000 to
1:15000 are most suitable.
 Quality of photographs depend upon-
 flight and weather condition
 Camera lens
 Film and filters
 Developing and printing processes

Basic Terminology
 Focal Length – the distance between the camera lens
and the film
 Flying Height – the height of the plane (and therefore
the camera) above the ground
 Nadir – the point on the ground directly below the
camera
 Flight Line – the path of the airplane over which a
sequence of pictures is taken
 Stereoscope - a device used to view/measure feature
heights and/or landscape elevations using pairs of air
photographs
 Fiducial Marks – marks on photographs used to align
adjacent photos for stereoscopic analysis

Air Photo Scale
 Scale (RF) = [1 : (flying height / focal length)] or (focal
length/flying height)
 Focal length and flying height should be in the same units
 Example:
 Focal length = 6 inches or 0.5 ft
 Flying height = 10,000 ft
 Scale = 0.5 / 10,000 = 1:20,000

Basic Camera
 Everything above “C” is
inside the camera
 The film sits on the film
plane
 f = focal length
 H = Elevation above
ground
 ACB = angle of coverage
 Scale: RF = 1:(H / f)

Types of vantage points to acquire
photographs
 Vertical vantage points
 Low-oblique vantage points
 High-oblique vantage points

Vertical Aerial Photography
San Juan River

Low-oblique Aerial Photography
Bridge on the Congaree river near
Columbia

High-oblique Aerial Photography
Grand Coulee Dam in Washington

Types of film
Black and White
 most often used in photogrammetry
 cheap
Color
 easy to interpret
 fuzzy due to atmospheric scattering
Infrared
Color Infrared (CIR)

CIR and True Color Film Type Examples
CIR True Color

Stereoscopic Parallax
 Stereoscopic Parallax is
caused by a shift in the
position of observation
 Parallax is directly related to
the elevation / height of
features
 Vertical stereo pairs of
aerial photographs are used
to take 3-D measurements
by measuring parallax

Sources of Distortion
 From Collection:
 Yaw – plane fuselage not parallel to flight line
Think about having to steer your car slightly into a strong cross
wind
Leads to pictures not being square with the flight-line
 Pitch – nose or tail higher than the other
Leads to principal point not being at nadir
 Roll – one wing higher than the other
Leads to principal point not being at nadir
 Natural:
 Haze
 Topographic changes
For example, if flying over mountains, the height above the ground
will a) change from picture to picture, and b) not be uniform in a
single picture. Both of these lead to irregularities in the photo
scale

Photo interpretation: Recognition Elements
Shape
Size
Color/Tone
Texture
Pattern
Site
Association
Shadow

 Shape
 cultural features - geometric, distinct boundaries
 natural features - irregular shapes and boundaries
 Shape helps us distinguish old vs. new subdivisions, some tree
species, athletic fields, etc.
The pentagon Meandering river
in Alaska
Interior Alaskan
village (note airstrip
near top of image)

 Size
 relative size is an important clue
 big, wide river vs. smaller river or
slough
 apartments vs. houses
 single lane road vs.
multilane

 Color/Tone
 coniferous vs. deciduous trees
CIR - Spruce forest
(black) with some
deciduous (red)
trees.
CIR – Deciduous
(leafy) vegetation
(red).
CIR- Mixed spruce
And deciduous forest
on hillside with tundra
in valley bottom

 Texture
 coarseness/smoothness caused by variability or
uniformity of image tone or color
 smoothness – tundra, swamps, fields, water, etc.
 coarseness - forest, lava flows, mountains etc.
CIR- Marshy
tundra with many
small ponds
CIR - Bare rounded
Mountains (blue)
surrounded by tundra
and lakes
CIR - Tundra
showing drainage
pattern

Pattern
 overall spatial form of
related features
 repeating patterns tend
to indicate cultural
features - random =
natural
 drainage patterns can
help geologists determine
bedrock type
A dendritic pattern is
characteristic of flat-
lying sedimentary
bedrock

Site
site - relationship of a feature to
its environment
differences in vegetation based
on location:
In interior Alaska, black
spruce dominant on the
north side of hills and
deciduous trees on the south
side.
Vegetation is often has
different characteristics by
rivers than away from them
Meandering
Alaskan river
Interior Alaskan
hillside

 Association
 identifying one feature can help identify another -
correlation
The white cloud and
black shadow have the
same shape, they are
related
The long straight airstrip
near the top of the image
indicates that there might
be a village or settlement
nearby

 Shadows
 shadows cast by some
features can aid in
their identification
 some tree types,
storage tanks, bridges
can be identified in
this way
 shadows can
accentuate terrain The mountain ridge on
the right side of this image
is accentuated by shadow

What is remote sensing used for What
is reRemote Sensingmote sensing used
for What is remote sensing used for
 Definitions:
 The acquisition of physical data of an object
without touch or contact .
 The observation of a target by a device some
distance away.
 The use of electromagnetic radiation sensors to
record images of the environment, which can be
interpreted to yield useful information.

Advantages of RS
 Provides a view for the large region
 Offers Geo-referenced information and digital
information
 Most of the remote sensors operate in every season,
every day, every time and even in real tough weather.
 Remote sensing can be either passive or active.
Active systems have their own source of energy
whereas the passive systems depend upon the solar
illumination or self emission for remote sensing

Process of RS Data
 Emission of electromagnetic radiation, or EMR (sun/self-
emission)
 Transmission of energy from the source to the surface of
the earth, as well as absorption and scattering
 Interaction of EMR with the earth's surface: reflection
and emission
 Transmission of energy from the surface to the remote
sensor
 Sensor data output
 Data transmission, processing and analysis

Remote Sensing Satellite
Polar-Orbiting Satellites
A polar orbit is a
satellite which is
located near to above of
poles. This satellite
mostly uses for earth
observation by time.

Remote Sensing Satellite
Geostationary Satellites
A geostationary satellite
is one of the satellites
which is getting remote
sense data and
located satellite at an
altitude of approximately
36000 kilometres and
directly over the equator

Remote Sensing Sensors
 Sensor is a device that gathers energy (EMR or
other), converts it into a signal and presents it in a
form suitable for obtaining information about the
target under investigation. These may be active or
passive depending on the source of energy .
 Sensors used for remote sensing can be broadly
classified as those operating in Optical Infrared (OIR)
region and those operating in the microwave region.
OIR and microwave sensors can further be
subdivided into passive and active.

Active sensors use their own source of energy. Earth
surface is illuminated through energy emitted by its own
source, a part of its reflected by the surface in the
direction of the sensor is received to gather information.
Passive sensors receive solar electromagnetic energy
reflected from the surface or energy emitted by the
surface itself. These sensors do not have their own
source of energy and can not be used at night time,
except thermal sensors. Again, sensors (active or
passive) could either be imaging, like camera, or Sensor
which acquire images of the area and non-imaging types
like non-scanning radiometer or atmospheric sounders.

Resolution
 Resolution is defined as the ability of the system to
render the information at the smallest discretely
separable quantity in terms of distance (spatial),
wavelength band of EMR (spectral), time (temporal)
and/or radiation quantity (radiometric)

Types of Resolution
Spatial resolution
Spectral Resolution
Radiometric Resolution
Temporal Resolution

 Spatial resolution—
 The earth surface area covered by a pixel of an
image is known as spatial resolution
 Large area covered by a pixel means low spatial
resolution and vice versa

 Spectral Resolution –
 Is the ability to resolve spectral features and
bands into their separate components
 More number of bands in a specified bandwidth
means higher spectral resolution and vice versa

Spectral Resolution
Three spectra recorded at low, medium and high spectral
resolution, illustrating how the high resolution mode yields
sharper peaks, and separates close lying peaks, which are
merged together at low resolution

 Radiometric Resolution -
 Sensitivity of the sensor to the magnitude of the
received electromagnetic energy determines the
radiometric resolution
 Finer the radiometric resolution of a sensor, if it is
more sensitive in detecting small differences in
reflected or emitted energy

Radiometric Resolution
6-bit range
0 63
8-bit range
0 255
0
10-bit range
2-bit range
0 4

 Temporal Resolution-
 Frequency at which images are recorded/
captured in a specific place on the earth.
 The more frequently it is captured, the better or
finer the temporal resolution is said to be
 For example, a sensor that captures an image of
an agriculture land twice a day has better
temporal resolution than a sensor that only
captures that same image once a week.

Temporal Resolution-
Remote Sensing & GIS Applications Directorate
Time
July 1 July 12 July 23 August 3
11 days
16 days
July 2 July 18 August 3

Color Science
 Additive primary colors :
 Blue, Green, and Red
 Subtractive primary colors (or
complementary colors):
 Yellow, Magenta, and Cyan
 Filters (subtract or absorb some colors
before the light reaches the camera):
 Red filter (absorbs green and blue, you can
see red)
 Yellow (or minus-blue) filter (absorbs blue,
allows green and red to be transmitted,
which is yellow)
 Haze filter (absorbs UV)
additive
Subtractive

Normal color False-color infrared

Satellite image
Satellite imagery
consists of photographs
from which collected by
satellites

Global overview
 What does satellite imagery give you?
 Information on land cover, land use, habitats, landscape and
infrastructure
 multiple engagements by time series
 Mapping and monitoring changes and predict future

Image Histograms
The histogram of
an image shows us
the distribution of
grey levels in the
image
Massively useful in
image processing,
especially in
segmentation
Grey Levels
Frequencies

Histogram example contd.
A selection of images and
their histograms
Notice the relationships
between the images and
their histograms
Note that the high contrast
image has the most
evenly spaced histogram

Digital Image
A digital image is
a representation of
a two-dimensional
image as a finite
set of digital
values, called
picture elements
or pixels

Digital Image contd.
 Pixel values typically represent gray levels, colours,
heights, opacities etc
 Remember digitization implies that a digital image is
an approximation of a real scene
1 pixel

Image Enhancement
 Spatial domain techniques
 Point operations
 Histogram equalization and matching
 Applications of histogram-based enhancement
 Frequency domain techniques
 Unsharp masking
 Homomorphic filtering

Land use and Land cover
 Land use – defined by economic terms
 Land cover – visible features
 Both are important and are really inseparable
 We depend on accurate LU/LC data for scientific and
administrative purposes

LU and LC Classification System
 general-purpose classification system
 Land Utilization Survey
 Land Use and Natural Resources Survey
 Special Purpose Classification Systems
 Wetlands Classification

Unsupervised and Supervised Classification
 Supervised learning: discover patterns in the data
that relate data attributes with a target (class)
attribute.
 These patterns are then utilized to predict the
values of the target attribute in future data
instances.
 Unsupervised learning: The data have no target
attribute.
 We want to explore the data to find some intrinsic
structures in them.

Application of RS
Urbanization & Transportation
 Urban planning
 Roads network and
transportation planning
 City expansion
 City boundaries by time
 Wetland delineation

Application of RS
Agriculture
The application of remote sensing in
agriculture include:
-Soil sensing
-Farm classification
- Farm condition assessment
- Agriculture estimation
- Mapping of farm and agricultural
land characteristics
- Mapping of land management
practices
- Compliance monitoring

Application of RS
 Monitoring dynamic changes
 Urban/Rural infrastructure
 Water logging & salinity
 Assessment of spatial
distribution of land resources
 Infrastructure monitoring
 Availability of usable land
 Future planning for better land
management for socio-
economic development
Land use/ land cover mapping

GIS Basic
Geographic Information System
Allows the viewing and analysis of multiple
layers of spatially related information
associated with a geographic region/location
The widespread collection and integration of
imagery into GIS has been made possible
through remote sensing
With the increasing technological
development of remote sensing, the
development of GIS has simultaneously
accelerated

Introduction contd.
 A system to present information and analysis that
has a geographic component.
 A system that uses maps and images to track any
sort of information.
 Both spatial and attribute (tabular) data are
integrated.

The GIS data types
 Discrete geographic features
 points, lines, areas
 the contents of maps
 with associated attributes
 countable
 conceived as tables with associated feature
geometry
 ESRI shape files

GIS Fields
 Geography as a collection of continuous variables
 measured on nominal, ordinal, interval, ratio
scales
 vector fields of direction and magnitude
 exactly one value per point
 z=f(x)
 population density, land ownership, zoning

Field representations
 Raster of rectangular cells
 Raster of uniformly spaced points
 Irregularly spaced points
 Irregular areas (polygons)
 Digitized contours
 Triangular mesh (triangulated irregular network or
TIN)
 ESRI coverages

GIS as a data access mechanism
 The geo library
 place-based search
 integrating information about a place
 making access transparent

Types of GIS
There are a number of Geographical Information Systems
(GIS) (or GIS software) available today. They range from high-
powered analytical software to visual web applications, and
each of those are used for a different purpose.
Due to the vast number of GIS available it is simply not
possible to provide training for each in this course. However,
there are common feature in all GIS. Understanding these
basic features will give you confidence with any GIS system
that you use in the future.
 This course will cover three groups of GIS:
 Web-based GIS: ONS and London Profiler
 Geobrowser: Google Earth
 Desktop GIS: Arc GIS

Web-based GIS
Web-based GIS, or WebGIS, are online GIS
applications which in most cases are excellent data
visualisation tools. Their functionality is limited
compared to software stored on your computer, but
they are user-friendly and particularly useful as
they not required data download.
There are many WebGIS available, but in this
course we will use two of them: the Office of
National Statistics (ONS) Neighbourhood mapping
tool and the London Profiler.

Geobrowser
A Geobrowser is better explained with reference to
an internet browser, i.e. Internet Explorer. In short, a
geobrowser can be understood as an Internet Explorer
for geographic information. Like the internet it allows
the combination of many types of geographic data from
many different sources. The biggest difference between
the World Wide Web and the geographic web however
is that everything within the latter is spatially
referenced.
Google Earth is the most popular geobrowser
available and will be the one used for this course.

Desktop GIS
A GIS, or GIS software, allows you to interactively
work with spatial data. A desktop GIS is a mapping
software that needs to be installed onto and runs on a
personal computer.
In this course, we will use ArcGIS, which is developed
by ESRI. ArcGIS is what ESRI refer to as a suite of
products which can be tailored to your need. ArcGIS is
used for a vast range of activities, covering both
commercial and educational uses.
The basic version of ArcGIS is what we will be using in
this course and is all the majority of GIS users will ever
need.

Spatial Data
 Spatial data
 information about phenomena organized in a
spatial frame
 the geographic frame
 Methods applied to spatial data that
 add value
 reveal patterns and anomalies
 support decisions

Spatial Analysis
 Methods whose results depend on the locations of
phenomena in the frame
 are not invariant under relocation
 Some types of relocation may not affect social
processes
 rotation
 relocation
 inversion

Spatial analysis as a collaboration
 The computer as butler to the human mind
 Are maps “mere”?
 Humans as sources of context
 cross-sectional data are already rich in context

Taxonomies of spatial analysis
 Thousands of methods
 every one a command, menu item, icon, …
 Based on data type
 point pattern analysis
 area (polygon) analysis
 analysis of interactions

A six-way conceptual classification
Query and reasoning
Measurement
Transformation
Descriptive summary
Optimization
Hypothesis testing

Query and reasoning
 Real-time answers to geographic questions
 Where is…?
 What is this?
 How do I get from here to here?
 Based on alternative views of a database

Measurement
 Area
 Distance
 Length
 Perimeter
 Slope, aspect
 Shape

Transformations
 Buffering
 Points in polygons
 Polygon overlay
 Spatial interpolation
 Density estimation

Descriptive summary
 Centers
 Measures of spatial dispersion
 Spatial dependence
 Fragmentation
 Fractional dimension

Optimization
 Design to achieve specific objectives
 Location of central point-like facilities to serve
dispersed demand
 Location of linear facilities
 Design of boundaries for elections

Hypothesis testing
 Geographic objects as a sample from a population
 what is the population?
 The independence assumption
 the First Law of Geography
 failure to find spatial dependence is always a Type
II error
 hell is a place with no spatial dependence

Application
 Change Detection
 Disaster Assessment
 2004 Tsunami
 Atmospheric Modeling
 aerosols
 air pollution
 climate change
 Ocean
 topography
 currents

GPS
 Stands for Global Positioning System
 GPS is used to get an exact location on or above the
surface of the earth (1cm to 100m accuracy).
 Developed by DoD (Department of Defense, U.S.)
and made available to public in 1983.
 GPS is a very important data input source.
 GPS is one of two (soon to be more) GNSS – Global
Navigation Satellite System

GNSS
 NAVSTAR – U.S. DoD (“GPS”)
 GLONASS – Russian system
 Galileo – European system (online in 2019?)
 Compass/BeiDou-2 – Chinese system in
development (operational with 10 satellites as of
December, 2011; 35 planned)
 GPS and GLONASS are free to use!

Segments of GPS
Control Segment
Space Segment
User Segment
Ground
Antennas
Master Station
Monitor Station

Data Models
 Raster Model
 The first GIS model developed
 Based on grids of cells that are assigned values
and grouped into layers
 Vector Model
 Uses points, lines, and polygons define data
classes
 Grouped into themes

GNSS Comparison
 GLONASS
 24 satellites (100% deployed)
 3 orbital planes
 GPS
 31 satellites (>100% deployed)
 6 orbital planes

System Components
 Receiver
 Receives satellite signals
 Compiles location info, ephemeris info, clock
calibration, constellation configuration (PDOP)
 Calculates position, velocity, heading, etc…
 Data Collector
 Stores positions (x,y,z,t)
 Attribute data tagged to position
 Software
 Facilitates file transfer to PC and back
 Performs differential correction (post-processing)
 Displays data and

Differential GPS
 Real Time
 Post Process

GPS Applications
 GPS uses into five categories
 Location – positioning things in space
 Navigation – getting from point a to point b
 Tracking - monitoring movements
 Mapping– creating maps based on those positions
 Timing – precision global timing

GPS Applications
 Agriculture
 Surveying
 Navigation (air, sea, land)
 Engineering
 Military operations
 Unmanned vehicle guidance
 Mapping

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