Post on 13-Jun-2020
transcript
An Introduction to Geomatics
الجيوماتكسخاص بطلبة مساق مقدمة في علم
Prepared by:
Dr. Maher A. El-Hallaq Associate Professor of Surveying – IUG
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Airborne Imagery
Dr. Maher A. El-Hallaq Associate Professor of Surveying The Islamic University of Gaza 2
Part One
Airborne Imagery
Photogrammetry
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Ba
ckg
round
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Background
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Backgro
und
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• Aerial photography has a history dating back to the
mid 1800s, when balloons and even kites were used
as camera platforms.
• In 1908, photographs were taken from early aircraft.
• Aerial photography became accepted technique for
collecting mapping and other ground data from 1930s
to the present.
• Photogrammetry is the science of making
measurements from aerial photographs.
Background
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• Measurements of horizontal distances and elevations
form the backbone of this science.
• These capabilities result in the compilation of
planimetric maps or orthophoto maps showing the
horizontal locations of both natural and cultural
features, and topographic maps showing spot
elevations and contour lines.
• Both black and white panchromatic and color film
are used in aerial photography.
• Color film has three emulsions: blue, green and red
light sensitive.
Background
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Background
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Background
The more recent topic
of airborne imagery
is digital imagery (2000).
The most common detector
is the Charge-Coupled
Device (CCD)
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Background
Old
New 11
Background
Elements of an aerial
mapping camera
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Background
Orthographic versus perspective projection
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Photogrammetric Process
Photogrammetric mapping is achieved through four general
processes :
Imagery Acquisition.
Ground Control Acquisition.
Accurate Adjustment of the Imagery to the Earth.
Feature Collection.
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Photogrammetric Process
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Photogrammetric Process
Imagery Acquisition.
Imagery Types and Uses
Imagery Type General Purposes
Black and White Aerial
Photography Topographic and Planimetric Mapping
Natural Color Aerial
Photography Topographic and Planimetric Mapping
Infrared Aerial Photography Vegetation Analysis, Land use
Satellite Imagery Small Scale Mapping, Vegetation
Analysis, Land use/Land Classification
Microwave Groundwater 16
Photogrammetric Process
Imagery Acquisition.
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Photogrammetric Process
Imagery Acquisition.
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Photogrammetric Process
Imagery Acquisition.
Scale of an aerial photograph 19
Photogrammetric Process
Imagery Acquisition.
Flight Plan
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Photogrammetric Process
Imagery Acquisition.
Flight Plan
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Photogrammetric Process
Example:
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Photogrammetric Process
Example:
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Photogrammetric Process
Example:
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Photogrammetric Process
Ground Control Acquisition.
Ground control methods
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Photogrammetric Process Accurate Adjustment of the Imagery to the Earth.
The process of adjusting the aerial photography to the earth is
critical to the accuracy of final mapping.
most projects are adjusted using aerotriangulation methods.
These methods require fewer ground control points than
conventional adjustment methods
Aerotriangulation methods are accomplished with computer
software. The software is very efficient and allows for quality
control checks throughout the process. 26
Photogrammetric Process
Feature Collection.
Photogrammetric mapping feature collection can
generally be divided into four categories:
1. Topographic Features (DEM and TIN models)
2. Planimetric Features
3. Orthophotography
4. Land use.
These feature types can be collected accurately using
stereo imagery and stereo viewing equipment. 27
Photogrammetric Process
Feature Collection.
3. Orthophotography
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Height Determination
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Height Determination
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Height Determination
Note:
If hB is not known, it is sufficiently accurate to use (havg)
instead of hB especially if H is large.
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Ground Coordinates
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Thank you
Any Question?
Satellite Imagery
Dr. Maher A. El-Hallaq Lecturer of Surveying The Islamic University of Gaza
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Part Two
Satellite Imagery
Remote Sensing
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Background
Remote sensing derives from photography, optics and
spectrometry; its history is deeply entwined with the
domains of electromagnetic spectrum and aeronautics.
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Background
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Background
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• Remote sensing is a broad research field with a wide
range of applications.
• Technically the term means acquisition of
information without being in direct contact with
the object that is studied.
• This will typically imply detection of some kind of
radiation. The detected radiation is either emanating
from the object itself or is reflected by it.
• The remote sensing principle, using waves of the
electromagnetic spectrum.
Background
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Background
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Electromagnetic Spectrum
The radiation propagates through a vacuum with
the speed of light, c, at about 300000 km/second.
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Electromagnetic Spectrum
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Electromagnetic Spectrum
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Ele
ctro
magnetic
Sp
ectru
m
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• Passive remote sensing instruments develop images
of the ground surface as they detect the natural
energy that is either reflected (if the sun is the signal
source) or emitted from the observed target area.
• Active remote sensing instruments (for example,
radar and lidar) transmit their own electromagnetic
waves and then develop images of the earth's surface
as the electromagnetic pulses (known as backscatter)
are reflected back from the target surface.
Techniques of Remote Sensing
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Optical: spectral range in the interval 0.3–15 μm,
typical of passive remote sensing, identified by the
sensors:
– panchromatic: one band including the visible range and in some cases part of the near infrared;
– multispectral: 2–9 spectral bands;
– super-spectral: 10–16 spectral bands;
– hyperspectral: more than 16 spectral bands;
The increase of the number of bands in general improves
the bandwidth (bandwidth is more common) and the
spectral interval.
Spectrum Sensors
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Radar: microwaves ranging from 1 mm to 1 m, typical
active remote sensing tool, that can operate, with single
or multi-polarization and with single or multiple incidence
angle, in:
– single frequency;
– multi-frequency.
Technical problems of acquisition and representation are
currently being operatively solved, while problems still
exist in understanding the characteristics of these
techniques by decision makers and administrators at
national, regional, provincial and city level.
Spectrum Sensors
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Techniques of Remote Sensing
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Techniques of Remote Sensing
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Techniques of Remote Sensing
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• One important way of discriminating objects in a
remotely sensed scene is by means of examining
their spectral signatures, a spectral response.
• Each material has its own spectral signature
constituting of the spectral distributions of its
emittance and reflectance.
Spectrum Signature
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Spectrum Signature
Spectral signature of some artificial materials 52
Spectrum Signature
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• Electromagnetic sensors are designed to detect only
radiation in a limited wavelength-range; a band.
• The reason for this is that the emitted energy within a
narrow band tells us more about the reflectance of an
object than an average over a wide band
• When the satellite image is received and processed on the
ground, bands from several sensors may be combined.
This will generally simplify the interpretation of a satellite-
scene
Sensor Fusion
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• Some object features stand out in one band while
other features are spotted in another band.
• The combination of information from several sensors
is usually termed sensor fusion.
• The combination or fusion of several bands is similar
to the approach used by the human vision system to
create colors.
Sensor Fusion
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• Satellite systems differ from the human vision system
in that each satellite has its own set of sensors,
constituting a unique set of bands and will thus require
interpreting software specially adapted for it.
Sensor Fusion
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Image Characteristics
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Image Characteristics
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Image Characteristics small equal-sized and shaped areas, called picture
elements or pixels, and
representing the brightness
of each area with a numeric
value or digital number
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• Image Resolution defines the ability of a
sensor to distinguish between spatial
characteristics of objects on the earth’s
surface.
• It can change due to sensor design, detector
size, focal length, satellite altitude and time.
Image Resolution
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• Spatial Resolution
• Spectral Resolution
• Radiometric Resolution
• Temporal Resolution
Image Resolution
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• The greater the altitude of the sensor, the larger the
area seen but the ability to distinguish some detail
may be lost.
• Some sensors have greater ability to see details,
greater spatial resolution.
• The ground sample distance GSD (Pixel Size in
image)
• IFOV: Instantaneous Field Of View
• GSD (m) = IFOV (radians) × Altitude (m)
Spatial Resolution
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Spatial Resolution
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• Surface features can be identified by analyzing the
spectral responses over distinct wavelength changes.
• The higher the spectral resolution of the sensor, the
more distinctions that can be made of surfaces
materials.
• Multispectral vs. hyperspectral sensors.
Spectral Resolution
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• Refers to the sensors ability to detect small changes
in energy and reflects the number of bits available
for each pixel.
• Imagery data are represented by positive digital
numbers like binary format. Each bit records an
exponent of 2.
• 2-bit is 22=4, 8-bit is 28=256, 10-bit is 210=1024
• 8-bit resolution of a region holds finer details than 2-
bit resolution.
• Multispectral vs. hyperspectral sensors.
Radiometric Resolution
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Radiometric Resolution
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• The surface of the earth is always changing, slowly or
rapidly.
• The time period required to achieve repeat coverage
of the same surface is called the revisit time.
• Temporal variations in surface features can be used
to identify some features and to track systematically
the changes in other features.
Temporal Resolution
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Temporal Resolution
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R.S.Satellites
Satellite Launch
Date
Sensor
Data
Altitude
km
Swath
km
Orbit
Type
Orbit
Period
Revisit
time
ERS-2 20/5/95 SAR C band 785 105.5 Near polar; sun
synchronous 100 min 35 days
IKONOS-2 24/9/99 MSS
panchronmatic 681 20
Near polar; sun
synchronous 98 min 2.9 days
IRS 2000 Panchronmatic/
hyperspectral 146 22 days
Landsat 5 1/3/84 TM and MSS 705 185 Near polar; sun
synchronous 99 min 16 days
Landsat 7 15/5/99 ETM MSS 830 185 Near polar; sun
synchronous 99 min 16 days
Radarsat-1 20/12/95 SAR C band 798 50-500 Circular; sun
synchronous
100.7
min 24 days
1 m
30 m
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R.S.Satellites
Satellite Launch
Date
Sensor
Data
Altitude
km
Swath
km
Orbit
Type
Orbit
Period
Revisit
time
QUICKBIRD 2000 MSS
panchronmatic 470
Not sun
synchronous
Less than
5 days
SPOT 1 22/2/86 MSS
panchronmatic 830 60-120
Near polar; sun
synchronous 101 min 26 days
SPOT 2 21/1/90 MSS
panchronmatic 830 60-120
Near polar; sun
synchronous 101 min 26 days
SPOT 4 24/3/98 MSS
panchronmatic 822 60-120
Near polar; sun
synchronous 101 min 26 days
SPOT 5 2001
TERRA 18/12/99 MODIS
ASTER 705 2100
Near polar; sun
synchronous
96.5
min 16 days
0.6 m
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R.S.Satellites
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R.S.Satellites
80 m
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R.S.Satellites
30 m
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R.S.Satellites
20 m 10 m
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R.S.Satellites
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Feature Extraction
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Feature Extraction
• Unsupervised: relies on color and tone as well as statistical
clustering to identify features.
• Supervised: requires comparative examples of imaging for
each ground feature category.
• Hybrid: is a combination of the first two.
• Classification and regression tree: using binary partitioning
software to analyze and arrive eventually at a best estimate
about the ground feature identification.
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Thank you
Any Question?