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GEOGG141/ GEOG3051 Principles & Practice of Remote Sensing ( PPRS ) Introduction , EM Radiation (i). Dr. Mathias (Mat) Disney UCL Geography Office: 113, Pearson Building Tel: 7679 0592 Email: [email protected] http :// html

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GEOGG141/ GEOG3051 Principles & Practice of Remote Sensing ( PPRS ) Introduction , EM Radiation (i)

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GEOGG141/ GEOG3051Principles & Practice of Remote Sensing (PPRS)Introduction, EM Radiation (i)

Dr. Mathias (Mat) Disney

UCL Geography

Office: 113, Pearson Building

Tel: 7679 0592

Email: [email protected]


  • Component 1 (GEOGG141 only)

    • Mapping principles (Dowman, Iliffe, Haklay, Backes, Smith, Cross)

    • Understanding the geometry of data acquisition

    • Orbits, geoids and principles of geodesy

  • Component 2 (GEOGG141 & GEOG3051)

    • Radiometric principles (Disney)

    • Understanding the what we measure and how

    • Radiative transfer (GEOGG141 only – Reading Week)

    • Resolution, sampling and practical tradeoffs

    • Pre-processing and ground segment

    • Active remote sensing (LIDAR, RADAR…)


  • Remote Sensing at UCL

    • NERC National Centre for Earth Observation (NCEO)

    • Involvement in several themes at UCL

      • Cryosphere @ Earth Sciences: (Wingham, Laxman et al.)

      • Carbon Theme @ Geography (Lewis, Mat Disney et al.)

      • Solid Earth: COMET @ GE (Ziebart)

    • More generally

      • MSSL: e.g. imaging (Muller), planetary, astro, instruments

  • UK prof. body - Remote Sensing and Photogrammetry Society


Reading and browsing

Remote sensing

Campbell, J.B. (2006) Introduction to Remote Sensing (4th ed),London:Taylor and Francis.

Harris, R. (1987) "Satellite Remote Sensing, An Introduction", Routledge & Kegan Paul.

Jensen, J. R. (2006, 2nd ed) Remote Sensing of the Environment: An Earth Resource Perspective, Prentice Hall, New Jersey. (Excellent on RS but no image processing).

Jensen, J. R. (2005, 3rd ed.) Introductory Digital Image Processing, Prentice Hall, New Jersey. (Companion to above) BUT some available online at

Jones, H. and Vaughan, R. (2010, paperback) Remote Sensing of Vegetation: Principles, Techniques, and Applications, OUP, Oxford. Excellent.

Lillesand, T.M., Kiefer, R.W. and Chipman, J. W. (2004, 5th ed.) Remote Sensing and ImageInterpretation, John Wiley, New York.

Mather, P.M. (2004) Computer Processing of Remotely‑sensedImages, 3rdEdition. John Wiley and Sons, Chichester.

Rees, W. G. (2001, 2nd ed.). Physical Principles of Remote Sensing, Cambridge Univ. Press.

Warner, T. A., Nellis, M. D. and Foody, G. M. eds. (2009) The SAGE Handbook of Remote Sensing (Hardcover). Limited depth, but very wide-ranging – excellent reference book.


Monteith, J. L. and Unsworth, M. H. (1990) ”Principles of Environmental Physics”, 2nd ed. Edward Arnold, London.

Hilborn, R. and Mangel, M. (1997) “The Ecological Detective: Confronting models with data”, Monographs in population biology 28, Princeton University Press, New Jersey, USA.


  • Moodle &

  • Web

  • Tutorials






  • Glossary :

  • Other resources

  • NASA

  • NASAs Visible Earth (source of data):

  • European Space Agency (eg Image of the week….)

  • NOAA


  • QuickBird:


  • General introduction to remote sensing (RS), Earth Observation (EO).......

    • definitions of RS

    • Concepts and terms

      • remote sensing process, end-to-end

  • Radiation I

    • Concepts and terms

      • remote sensing process, end-to-end

What is remote sensing?

The Experts say "Remote Sensing (RS) is...”

  • “The science technology and art of obtaining information about objects or phenomena from a distance (i.e. without being in physical contact with them”

  • But not the whole story:

    • Tend to use Earth Observation (EO). To distinguish from?

    • Domains (atmosphere, terrestrial, ocean, cryosphere, biosphere etc)

    • But also astronomy, planetary remote sensing etc.

What is remote sensing (II)?

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

    (more of the same from

Remote Sensing Examples

  • Kites (still used!) Panorama of San Francisco, 1906.

  • Up to 9 large kites used to carry camera weighing 23kg.

Remote Sensing: scales and platforms

  • Both taken via kite aerial photography






Remote Sensing: scales and platforms

  • Platform depends on application

    • What information do we want?

    • How much detail?

    • What type of detail?


Remote Sensing: scales and platforms

  • Many types of satellite

    • Different orbits, instruments, applications

Remote Sensing Examples

  • Global maps of vegetation from MODIS instrument

IKONOS-2 image of Venice

Why do we use remote sensing?

  • Many monitoring issues global or regional

  • Drawbacksof in situ measurement …..

  • Remote sensing can provide (not always!)

    • Global coverage

      • Range of spatial resolutions

    • Temporal coverage (repeat viewing)

    • Spectral information (wavelength)

    • Angular information (different view angles)

Why do we study/use remote sensing?

  • source of spatial and temporal information (land surface, oceans, atmosphere, ice)

  • monitor and develop understanding of environment (measurement and modelling)

  • information can be accurate, timely, consistent

  • remote access

  • some historical data (1960s/70s+)

  • move to quantitative RS e.g. data for climate

    • some commercial applications (growing?) e.g. weather

    • typically (geo)'physical' information but information widely used (surrogate - tsetse fly mapping)

    • derive data (raster) for input to GIS (land cover, temperature etc.)

EO process in summary.....

  • Collection of data

    • Some type of remotely measured signal

    • Electromagnetic radiation of some form

  • Transformation of signal into something useful

    • Information extraction

    • Use of information to answer a question or confirm/contradict a hypothesis

Passive: solar reflected/emitted

Active:RADAR (backscattered); LiDAR (reflected)

The Remote Sensing Process

  • Collection of information about an object without coming into physical contact with that object

The Remote Sensing Process

  • What are we collecting?

    • Electromagnetic radiation (EMR)

  • What is the source?

    • Solar radiation

      • passive – reflected (vis/NIR), emitted (thermal)

    • OR artificial source

      • active - RADAR, LiDAR even sonar

  • Note various paths

    • Source to sensor direct?

    • Source to surface to sensor

    • Sensor can also be source

Energy transport

  • Conduction

    • transfer of molecular kinetic (motion) energy due to contact

    • heat energy moves from T1 to T2 where T1 > T2

  • Convection

    • movement of hot material from one place to another

    • e.g. Hot air rises

  • Radiation

    • results whenever an electrical charge is accelerated

    • propagates via EM waves, through vacuum & over long distances hence of interest for remote sensing

Electromagnetic radiation: wave model

  • James Clerk Maxwell (1831-1879)

  • Wave model of EM energy

    • Unified theories of electricity and magnetism (via Newton, Faraday, Kelvin, Ampère etc.)

    • Oscillating electric charge produces magnetic field (and vice versa)

    • Can be described by 4 simple (ish) differential equations

    • Calculated speed of EM wave in a vacuum

Electromagnetic radiation

  • EM wave is

  • Electric field (E) perpendicular to magnetic field (M)

  • Travels at velocity, c (3x108 ms-1, in a vacuum)

  • Or does it?? CERN 2011 ….

Wave: terms

  • All waves characterised by:

    • Wavelength,  (m)

    • Amplitude, a (m)

    • Velocity, v (m/s)

    • Frequency, f (s-1 or Hz)

    • Sometimes period, T (time for one oscillation i.e. 1/f)

Wave: terms

  • Velocity, frequency and wavelength related by

  • f proportional to 1/ (constant of proportionality is wave velocity, v i.e.

Wave: terms

  • Note angles in radians (rad)

    • 360° = 2 rad, so 1 rad = 360/2 = 57.3°

    • Rad to deg. (*180/) and deg. to rad (* /180)

1. Gauss’ law for electricity: the electric flux out of any closed surface is proportional to the total charge enclosed within the surface

2. Gauss’ law for magnetism: the net magnetic flux out of any closed surface is zero (i.e. magnetic monopoles do not exist)

3. Faraday’s Law of Induction: line integral of electric field around a closed loop is equal to negative of rate of change of magnetic flux through area enclosed by the loop.

4. Ampere’s Law: for a static electric field, the line integral of the magnetic field around a closed loop is proportional to the electric current flowing through the loop.

Aside: Maxwell’s Equations

  • Note:  is ‘divergence’ operator and x is ‘curl’operator; 0 is permittivity of free space; 0 is permeability of free space


EM Spectrum

  • EM Spectrum

    • Continuous range of EM radiation

    • From very short wavelengths (<300x10-9m)

      • high energy

    • To very long wavelengths (cm, m, km)

      • low energy

    • Energy is related to wavelength (and hence frequency)


  • EM wavelength  is m, but various prefixes

    • cm (10-2m)

    • mm (10-3m)

    • micron or micrometer, m (10-6m)

    • Angstrom, Å (10-8m, used by astronomers mainly)

    • nanometer, nm (10-9)

  • f is waves/second or Hertz (Hz)

  • NB can also use wavenumber, k = 1/ i.e. m-1

  • Energy radiated from sun (or active sensor)

  • Energy  1/wavelength (1/)

    • shorter  (higher f) == higher energy

    • longer  (lower f) == lower energy


EM Spectrum

  • We will see how energy is related to frequency, f (and hence inversely proportional to wavelength, )

  • When radiation passes from one medium to another, speed of light (c) and  change, hence f stays the same

Electromagnetic spectrum: visible

  • Visible part - very small part

    • from visible blue (shorter )

    • to visible red (longer )

    • ~0.4 to ~0.7m

      Violet: 0.4 - 0.446 m

      Blue: 0.446 - 0.500 m

      Green: 0.500 - 0.578 m

      Yellow: 0.578 - 0.592 m

      Orange: 0.592 - 0.620 m

      Red: 0.620 - 0.7 m

Electromagnetic spectrum: IR

  • Longer wavelengths (sub-mm)

  • Lower energy than visible

  • Arbitrary cutoff

  • IR regions covers

    • reflective (shortwave IR, SWIR)

    • region just longer than visible known as near-IR, NIR

    • and emissive (longwave or thermal IR, TIR)

Electromagnetic spectrum: microwave

  • Longer wavelength again

    • RADAR

    • mm to cm

    • various bands used by RADAR instruments

    • long  so low energy, hence need to use own energy source (active wave)


  • All objects above absolute zero (0 K or -273° C) radiate EM energy (due to vibration of atoms)

  • We can use concept of a perfect blackbody

    • Absorbs and re-radiates all radiation incident upon it at maximum possible rate per unit area (Wm-2), at each wavelength, , for a given temperature T (in K)

  • Energy from a blackbody?

Stefan-Boltzmann Law

  • Total emitted radiation from a blackbody, M, in Wm-2, described by Stefan-Boltzmann Law

  • Where T is temperature of the object in K; and  = is Stefan-Boltmann constant = 5.6697x10-8 Wm-2K-4

  • So energy  T4 and as T so does M

    • Tsun 6000K M,sun 73.5 MWm-2

    • TEarth 300K M , Earth  460 Wm-2

Stefan-Boltzmann Law

Stefan-Boltzmann Law

  • Note that peak of sun’s energy around 0.5 m

    • negligible after 4-6m

  • Peak of Earth’s radiant energy around 10 m

    • negligible before ~ 4m

  • Total energy emitted in each case is area under curve

Stefan-Boltzmann Law

  • Generalisation of Stefan-Boltzmann Law

    • radiation  emitted from unit area of any plane surface with emissivity of  (<1) can be written as:

      • = Tn

      • where n is a numerical index

    • For ‘grey’ surface where  is nearly independent of, n =4

    • When radiation emitted predominantly at  < m , n > 4

    • When radiation emitted predominantly at  > m , n < 4

Peak  of emitted radiation: Wien’s Law

  • Wien deduced from thermodynamic principles that energy per unit wavelength E() is function of T and 

  • At what mis maximum radiant energy emitted?

  • Comparing blackbodies at different T, note mT is constant, k = 2897mK i.e. m = k/T

    • m, sun = 0.48m

    • m, Earth = 9.66m

Increasing , lower energy

Wien’s Law

  • AKA Wien’s Displacement Law

  • Increase (displacement) in mas T reduces

  • Straight line in log-log space

Particle model of radiation

  • Hooke (1668) proposed wave theory of light propagation (EMR) (Huygens, Euler, Young, Fresnel…)

  • Newton (~1700) proposed corpuscular theory of light (after al-Haytham, Avicenna ~11th C, Gassendi ~ early17th C)

    • observation of light separating into spectrum

  • Einstein explained photoelectric effect by proposing photon theory of light

    • Photons: individual packets (quanta) of energy possessing energy and momentum

  • Light has both wave- and particle-like properties

    • Wave-particle duality

Particle model of radiation

  • EMR intimately related to atomic structure and energy

  • Atom: +ve charged nucleus (protons +neutrons) & -ve charged electrons bound in orbits

    • Electron orbits are fixed at certain levels, each level corresponding to a particular electron energy

    • Change of orbit either requires energy (work done), or releases energy

    • Minimum energy required to move electron up a full energy level (can’t have shift of 1/2 an energy level)

    • Once shifted to higher energy state, atom is excited, and possesses potential energy

    • Released as electron falls back to lower energy level

Particle model of radiation

  • As electron falls back, quantum of EMR (photons) emitted

    • electron energy levels are unevenly spaced and characteristic of a particular element (basis of spectroscopy)

  • Bohr and Planck recognised discrete nature of transitions

  • Relationship between frequency of radiation (wave theory) of emitted photon (particle theory)

  • E is energy of a quantum in Joules (J); h is Planck constant (6.626x10-34Js) and f is frequency of radiation

Particle model of radiation

  • If we remember that velocity v = f and in this case v is actually c, speed of light then

  • Energy of emitted radiation is inversely proportional to 

    • longer (larger)  == lower energy

    • shorter (smaller)  == higher energy

  • Implication for remote sensing: harder to detect longer radiation (thermal for e.g.) as it has lower energy

Particle model of radiation


Particle model of radiation: atomic shells

Planck’s Law of blackbody radiation

  • Planck was able to explain energy spectrum of blackbody

  • Based on quantum theory rather than classical mechanics

  • dE()/d gives constant of Wien’s Law

  • E() over all  results in Stefan-Boltzmann relation

  • Blackbody energy function of , and T

Planck’s Law

  • Explains/predicts shape of blackbody curve

  • Use to predict how much energy lies between given 

    • Crucial for remote sensing

Consequences of Planck’s Law: plant pigments

  • Chlorophyll a,b absorption spectra

  • Photosynthetic pigments

    • Driver of (nearly) all life on Earth!

    • Source of all fossil fuel

Consequences of Planck’s Law: human vision

Cones: selective sensitivity

Rods : monochromatic sensitivity

Radiant energy from 0 to 

Total radiant energy for = 0 to  = 

Applications of Planck’s Law

  • Fractional energy from 0 to  i.e. F0? Integrate Planck function

  • Note Eb(,T), emissive power of bbody at , is function of product T only, so....





T (

mK x10

































Applications of Planck’s Law: example

  • Q: what fraction of the total power radiated by a black body at 5770 K fall, in the UV (0 < 0.38µm)?

    • Need table of integral values of F0

    • So, T = 0.38m * 5770K = 2193mK

    • Or 2.193x103mK i.e. between 2 and 3

    • Interpolate between F0(2x103) and F0(3x103)

  • Finally, F00.38 =0.193*(0.273-0.067)+0.067=0.11

  • i.e. ~11% of total solar energy lies in UV between 0 and 0.38 m





T (

mK x10

































Applications of Planck’s Law: exercise

  • Show that ~38% of total energy radiated by the sun lies in the visible region (0.38µm < 0.7µm) assuming that solar T = 5770K

    • Hint: we already know F(0.38m), so calculate F(0.7m) and interpolate

Electromagnetic spectrum

  • Interaction with the atmosphere

    • transmission NOT even across the spectrum

    • need to choose bands carefully!

Departure from BB assumption?


  • Objects can be approximated as blackbodies

    • Radiant energy  T4

  • EM spectrum from sun a continuum peaking at ~0.48m

    • ~39% energy between 0.38 and 0.7 in visible region

  • Planck’s Law - shape of power spectrum for given T (Wm-2 m-1)

    • Integrate over all  to get total radiant power emitted by BB per unit area

      • Stefan-Boltzmann Law M = T4 (Wm-2)

    • Differentiate to get Wien’s law

      • Location of max = k/T where k = 2898mK


  • 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.

Example biophysical variables

After Jensen, p. 9

Example biophysical variables

Good discussion of spectral information extraction:

After Jensen, p. 9

Interesting stuff…..

  • IKONOS image gallery index:

  • Quickbird, Worldview 1 & 2 image gallery:

  • Eg Japan earthquake and tsunami:

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