Introduction to Remote Sensing
What is remote sensing?
The Experts say "Remote Sensing is...”
 ...a variety of techniques for collecting image or other forms of
data about an object from measurements made at a distance
from the object, and the processing and analysis of the data.
 ...the science (and to some extent, art) of acquiring information
about the Earth's surface without actually being in contact with
it. This is done by sensing and recording reflected or emitted
energy and processing, analysing, and applying that
information.
The not so experts say "Remote Sensing is...”
 Advanced colouring-in.
 Seeing what can't be seen, then convincing
someone that you're right.
 Being as far away from your object of study as
possible and getting the computer to handle the
numbers.
 Legitimised voyeurism….
Remote Sensing
involves the
detection and
measurement of
photons of
differing energies
emanating from
distant materials,
by which these
may be identified
and categorised
by class/type,
substance, and
spatial
distribution.
(this is Oman)
• First aerial photo
credited to
Frenchman Felix
Tournachon,
Bievre Valley,
1858.
• Boston from
balloon (oldest
preserved aerial
photo), 1860, by
James Wallace
Black.
The first aerial
photo taken from a
rocket was made
by the Swede
Alfred Nobel (of
Nobel Prize fame)
in 1897. Here is the
picture he obtained
of the Swedish
landscape
The Bavarian Pigeon
Fleet took this picture
of a Bavarian castle
with an automatic
camera in 1903
• Kites used to take this panorama of San Francisco, 1906.
• Motivation was to see destruction after 1906 Earthquake
• Up to 9 large kites used to carry camera weighing 23kg.
First pictures from “space” taken in
1946 by German V-2 rockets
captured during WW2
Now have multimap,
Google Earth, etc.
Remote sensing applications
 Land-use mapping
 Forest and agriculture applications
 Telecommunication planning
 Environmental applications
 Hydrology and coastal mapping
 Geophysical and geochemical prospecting
 Urban planning
 Emergencies and Hazards
 Global change and Meteorology
Global maps of vegetation amount from MODIS instrument
Global maps of sea surface temperature and land surface
reflectance from MODIS instrument
Why do we use remote sensing?
 Many monitoring issues global or regional
 Drawbacks of in situ measurement (cost, manpower,
accessibility etc.)
 Remote sensing can provide (not always!)
 Spatial information & wide/global coverage

Range of spatial resolutions
 Spectral information
 Related to surface biophysical properties (wavelength
variation of surface reflectance)
 Temporal information
 Consistent, timely, repeat viewing
 Angular information (different view angles)
 Related to surface structure and arrangement of objects
Caveats!
 Remote sensing has many problems
 Can be expensive
 Technically difficult
 NOT direct



measure surrogate variables
e.g. reflectance (%), brightness temperature (Wm-2 
oK), backscatter (dB)
RELATE to other, more direct properties.
 Doesn’t always go according to plan.....
Cryosat failure October 2005
Remote sensing basic processes
 Data acquisition (energy propagation, platforms)
 Processing (conversion of energy pattern to
images, digital numbers (DNs))
 Analysis (quantitative and qualitative analysis)
 Accuracy assessment (radiometric and geometric
correction)
 Information distribution to users (hard copy, CDROM, digital data)
A Remote Sensing System
 Energy source
 platform
 sensor
 data recording / transmission
 ground receiving station
 data processing
 expert interpretation / data users
Advantages of remote sensing
 Provides a regional view (large areas)
 Provides repetitive looks at the same area
 Remote sensors "see" over a broader portion of
the spectrum than the human eye
 Sensors can focus in on a very specific
bandwidth in an image or a number of
bandwidths simultaneously
 Provides geo-referenced, digital, data
 Some remote sensors operate in all seasons, at
night, and in bad weather
 Orbits
 geostationary (36 000
km altitude)
 polar orbiting (200-
1000 km altitude)
 Spatial resolution
 10s cm (??) - 100s km
 determined by altitude
of satellite (across
track), altitude and
speed (along track),
viewing angle
Physical Basis for remotes sensing
from satellites
 measurement of electromagnetic radiation
 scattered, reflected, emitted, absorbed
 energy sources
 Sun (scattered, reflected), Earth (emitted)
 Artificial (radar, laser....)
 source properties
 vary in intensity AND across wavelengths
 vary with physical / chemical properties
 can vary with viewing angle
What is EM Energy?
The sun is our primary source of
EM energy...
Wave Model of Electromagnetic Radiation
In the 1860s, James Clerk Maxwell (1831–1879) conceptualised
electromagnetic radiation (EMR) as an electromagnetic wave that travels
through space at the speed of light, c, (3 x 108 ms-1) or 186,282.03 miles s-1.
The electromagnetic wave consists of two fluctuating fields—one electric
and the other magnetic. The two vectors are at right angles (orthogonal) to
one another, and both are perpendicular to the direction of travel.
Wave Model of Electromagnetic Energy
This
cross-section
of
an
electromagnetic wave illustrates
the inverse relationship between
wavelength and frequency. The
longer the wavelength the lower
the frequency; the shorter the
wavelength, the higher the
frequency. The amplitude of an
electromagnetic wave is the
height of the wave crest above the
undisturbed position. Successive
wave crests are numbered 1, 2, 3,
and 4. An observer at the position
of the clock records the number of
crests that pass by in a second.
This frequency is measured in
cycles per second, or hertz.
The Electromagnetic Spectrum
0.4
0.5
0.6
0.7 µm
Visible 
Wavelength (µm)
-6
10
10
Wavelength (µm)
-5
X-Rays
10
-4
10
-3
-2
10
10
Ultraviolet
-1
1
10
10
Infrared
2
10
3
10
4
10
Microwave
5
10
6
10
7
10
TV/Radio
• The visible portion of the EM spectrum is very small...
• EM energy is a continuum which we (somewhat arbitrarily) classify
according to wavelength. Wavelengths extend from very, very short
(cosmic and X rays) to very, very long (thermal, radar, etc...).
8
Response to EM Energy
 Objects, when struck by EM energy, respond by
absorbing, reflecting or transmitting the energy.
Different objects, because of their physical
properties, respond differently to equivalent inputs
of EM energy. This allows us to tell one thing from
another...
On striking the land or ocean surface the sunlight will be partitioned into
three modes of energy-interaction response:
(1) transmittance - some radiation will penetrate into certain surface
media such as water;
(2) absorptance - some radiation will be absorbed through electron or
molecular reactions within the medium encountered; a portion of the
energy incorporated can then be re-emitted (as emittance), largely at
longer wavelengths, so that some of the sun's radiant energy
engages in heating the target giving rise then to a thermal response;
(3) reflectance - some radiation will, in effect, be reflected (and
scattered) away from the target at different angles (depending in part
on surface "roughness" as well as on the angle of the sun's direct
rays relative to surface inclination).
Most remote sensing systems are designed to monitor reflected radiation.
Response to EM Energy
Why does a green tree look green?
• The sun radiates the earth with nearly equal amounts
of blue, green and red wavelength light.
• Because of its physical properties, the tree reflects
and absorbs differing amounts of the incoming light...
Response to EM Energy
Why does a green tree look green?
…and we perceive the
tree as green...
Red 
Green 
Blue 
The tree absorbs much more of the red and blue
wavelengths and reflects much more of the green...
Response to EM Energy
Spectral Response Curves aka Spectral Reflectance Curves,
aka Spectral Signatures...
Graphically, the spectral
reflectance of green vegetation
in the visible wavelengths may
be represented as shown...
0.4
2.6
Near Infrared
Wavelength (µm)
Mid Infrared
Spectral Response Curve of Typical Vegetation From 0.4 to 2.6 µm
0.4
2.6
Near Infrared
Wavelength (µm)
Mid Infrared
Spectral Response Curves
 An object’s Spectral Response Curve is a
representation of the reflected EM energy of that
object across a portion of the EM spectrum, as the
object is exposed to (our Sun’s) EM radiation.
 For most purposes, Spectral Response Curves,
Spectral Reflectance Curves and Spectral
Signatures are synonymous.
Typical Spectral Signatures
Typical Spectral Response Curves in the 0.4 to 2.6 µm Region...
Healthy Vegetation
0.4
Clear Water
Near Infrared
Wavelength ( m )
2.6
Mid Infrared
Spectral information: vegetation
0.5
very high leaf area
NIR, high
reflectance
0.4
very low leaf area
reflectance(%)
0.3
sunlit soil
0.2
Visible green,
higher than red
0.1
Visible red, low
reflectance
0.0
400
600
800
Wavelength, nm
1000
1200
On Earth cannot use all spectrum because of the atmosphere.
Here is a generalised diagram showing relative atmospheric
transmission of radiation of different wavelengths.
Blue zones mark minimal passage of incoming and/or outgoing
radiation whereas white areas denote "atmospheric windows" in
which the radiation experiences much reduced interactions with
various molecular species and hence can penetrate the air with
little or no loss by absorption.
Images over
a wide
spectral range
can be
obtained from
a Multispectral
scanner
Landsat image of western shore of the Keweenaw Peninsula of Michigan
Levels of gray in the resulting image range from black (Digital Number, DN =
0) to white (DN = 255) with shades of dark gray to very light gray associated
with increasing DN values.
 Bands then assigned colours to give “colour composite”
 Colours assigned in such a way as to make image
“recognisable”
Colour Composites: multi-spectral images
‘Real Colour’
composite
Red band on red
Green band on green
Blue band on blue
Approximates “real”
colour (RGB colour
composite)
Landsat TM image
of Swanley, 1988
‘False Colour’ composite
NIR band on red
red band on green
green band on blue
Landsat image of Hawaii
False-colour composite processed to
simulate true colour
False colour
(filter bands 2,
3, 5 in blue,
green, red)
rendition of
mountain
ranges in
southeastern
California into
Nevada.
Salt Lake City
Thermal image: cold = dark
Aerial photo
Space Shuttle photo
1972
2001
Morro Bay, California
Landsat: False colour (left), supervised classification (right
Patagonia, Chile: here, colour is assigned to designate height
Hyperspectral Imaging
 Narrow spectral widths 0.01-0.02 micrometers
 Visible/NIR
 Much more detailed images
 Hills in Nevada
Modern satellite optics give
very high resolution images:
Buckingham Palace
Bloomsbury
Parliament
 London seen from KVR-1000 Russian satellite with 2
metre ground resolution.
UCL in Bloomsbury
Regents Park
British
Museum
Remote sensing platforms: IKONOS
Jefferson Memorial
first images from IKONOS
Hirshorn Museum
Bora Bora
Farming in
Saudi Arabia
Also used to find
mineralisation
(usually via
vegetation types,
etc), geological
features and large
features that are
not easily seen
from ground such
as impacts.
Manicouagan
Crater, Quebec,
Canada
Uses of Remote Sensing in Hazards
and Global Change
 Hazard and risk modeling of tsunamis, hurricanes,





earthquakes and disease pandemics
Models of extreme oceanic, land and atmospheric
phenomena as well as pandemic outbreaks
Remote sensing based early warning systems for natural
disasters such as tsunamis, hurricanes, earthquakes,
floods, etc.
Satellite and/or airborne observations of extreme natural
events in support of disaster response
Damage assessment using satellites and airborne
sensors
Damage and loss estimation
Air Pollution over China: MODIS AOD via Giovanni
July 4th – August 4th, 2008
Beijing Summer 2007
August 5th – August 25th, 2008
Beijing Summer 2008
Diatoms





Most abundant plankton
Nutrient-rich, high latitudes
2-1000 m
autotrophic
chlorophyll in chloroplasts – absorb
red and blue
 Appear yellow-brown (“Golden
Algae”)
Diatom Bloom off mid-Atlantic coast
Coccolithophorids
 Shells composed of calcium coccoliths
– milky white appearance
 Able to thrive in nutrient-poor conditions
TERRA MODIS, 21 JUN 04:
Coccolithophore blooms off of Iceland
50 km
Hurricane Katrina August 2005
Tropical Rainfall Measuring Mission TRMM
• Category 5 hurricane
• Winds at 161 mph
• Instruments include:




Precipitation Radar (PR)
TRMM Microwave Imager (TMI)
Visible Infrared Scanner (VIRS)
Clouds and the Earths Radiant
Energy System (CERES)
 Lightning Imaging Sensor (LIS)
Assessing Tsunami Damage
Flooding in Mozambique (2000)
 This pair of images from Landsat 7 shows the incredible amount of flooding
that occurred in March of 2000 in Mozambique.
 A month of rains and two cyclones caused the Limpopo River to swell to 80 km
wide in places.
 Several hundred people were killed, and over a million were forced from their
homes.
Drought in Australia
Soil moisture distribution in Australia during October 2005 and 2006.
This data acquired by AMSR-E on Aqua. Red indicates low soil
moisture (dry), while blue indicates higher soil moisture (wet). A
drought occurred in south east Australia (Granary area) in 2006.
Earthquake Near Sumatra
ASTER
ASTER
ASTER data showed that Coral reefs off Nias Island, Indonesia were
uplifted following earthquakes near Sumatra, Indonesia
in December 2004 and March, 2005.
Radar Interferometry
 Hector Mine
earthquake in
the Mojave
Desert
 Displacement
strain (10cm
/colour cycle)
Antarctic Sea Ice Thickness
Weddell Sea Ice Thickness from
Multichannel Observations made by SIR-C/X-SAR
Wildfires
Fires in Southern California, October 25, 2003
Observed with MODIS on TERRA.
Now at very high resolution, e.g. Mars:
False colour
shows details
on Europa:
Clouds on
Venus a
challenge!
Magellan
used radar to
see beneath
the clouds.
Venus surface was mapped more comprehensively than the Earth!