1. Remote Sensing and Image Processing: 3 Dr. Hassan J. Eghbali

2. Back to the process.... What sort of parameters are of interest? Variables describing Earth system.... Dr. Hassan J. Eghbali

3. EO and the Earth “System” External forcing Hydrosphere Atmosphere Geosphere Cryosphere Biosphere Dr. Hassan J. Eghbali

4. Example biophysical variables Dr. Hassan J. Eghbali

5. Example biophysical variables Good discussion of spectral information extraction: http://dynamo.ecn.purdue.edu/~landgreb/Principles.pdf Dr. Hassan J. Eghbali

6. Remote Sensing Examples Dr. Hassan J. Eghbali

7. Information extraction process Image interpretation Tone, colour, stereo parallax Size, shape, texture, pattern, fractal dimension Height/shadow Site, association Primary elements Spatial arrangements Secondary elements Context Analogue image processing Multi: spectral, spatial, temporal, angular, scale, disciplinary Visualisation Ancillary info.: field and lab measurements, literature etc. Presentation of information Multi: spectral, spatial, temporal, angular, scale, disciplinary Statistical/rule- based patterns Hyperspectral Modelling and simulation Dr. Hassan J. Eghbali

8. Example: Vegetation canopy modelling Develop detailed 3D models Simulate canopy scattering behaviour Compare with observations Dr. Hassan J. Eghbali

9. Core principles of electromagnetic radiation (EMR) –solar radiation –blackbody concept and radiation laws EMR and remote sensing –wave and particle models of radiation –regions of EM spectrum –interaction with atmosphere –interaction with surface Measurement of radiation Electromagnetic (EM) Spectrum Dr. Hassan J. Eghbali

10. This is what we measure in remote sensing Terms, units, definitions Provide basis for understanding type of information that can be retrieved Why we choose given regions of the EM spectrum in which to make measurements EM spectrum: so what? Dr. Hassan J. Eghbali

11. Remote sensing process: recap Dr. Hassan J. Eghbali

12. Note various paths –Source to sensor direct? –Source to surface to sensor –Sensor can also be source RADAR, LiDAR, SONAR i.e. “active” remote sensing Reflected and emitted components –What do these mean? Several components of final signal captured at sensor Remote sensing process: recap Dr. Hassan J. Eghbali

13. Conduction –transfer of molecular kinetic (motion) energy due to contact –heat energy moves from T 1 to T 2 where T 1 > T 2 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 Energy transport Dr. Hassan J. Eghbali

14. EM Spectrum Continuous range of EM radiation From very short wavelengths (<300x10 -9 m) high energy To very long wavelengths (cm, m, km) low energy Energy is related to wavelength (and hence frequency) Dr. Hassan J. Eghbali

15. Energy radiated from sun (or active sensor) Energy  1/wavelength (1/ ) –shorter (higher f) == higher energy –longer (lower f) == lower energy Dr. Hassan J. Eghbali

16. Units EM wavelength is m, but various prefixes cm (10 -2 m) mm (10 -3 m) micron or micrometer,  m (10 -6 m) Angstrom, Å (10 -8 m, 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 Dr. Hassan J. Eghbali

17. 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 Dr. Hassan J. Eghbali

18. 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 Dr. Hassan J. Eghbali

19. Electromagnetic spectrum: IR Longer wavelengths (sub- mm) Lower energy than visible Arbitrary cutoff IR regions covers –reflective (shortwave IR, SWIR) –and emissive (longwave or thermal IR, TIR) –region just longer than visible known as near-IR, NIR. Dr. Hassan J. Eghbali

20. 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) Dr. Hassan J. Eghbali

21. Electromagnetic spectrum Interaction with the atmosphere –transmission NOT even across the spectrum –need to choose bands carefully to coincide with regions where transmission high (atmospheric windows – see later) Dr. Hassan J. Eghbali

22. “Blackbody” concept 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) No real object is blackbody but it is v. useful assumption Energy from a blackbody? Dr. Hassan J. Eghbali

23. 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-Boltzmann constant = 5.6697x10 -8 Wm -2 K -4 So energy  T 4 and as T  so does M T sun  6000K M,sun  73.5 MWm -2 T Earth  300K M, Earth  460 Wm -2 Dr. Hassan J. Eghbali

24. Stefan-Boltzmann Law Dr. Hassan J. Eghbali

25. 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 in each case is area under curve Dr. Hassan J. Eghbali

26. 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 m is maximum radiant energy emitted? Comparing blackbodies at different T, note m T is constant, k = 2897  mK i.e. m = k/T m, sun = 0.48  m m, Earth = 9.66  m Dr. Hassan J. Eghbali

27. Wien’s Law AKA Wien’s Displacement Law Increase (displacement) in m as T reduces Straight line in log- log space Increasing Dr. Hassan J. Eghbali

28. 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 Dr. Hassan J. Eghbali

29. Planck’s Law Explains/predicts shape of blackbody curve Use to predict how much energy lies between given Crucial for remote sensing Dr. Hassan J. Eghbali

30. Consequences of Planck’s Law Chlorophyll a,b absorption spectra Photosynthetic pigments Driver of (nearly) all life on Earth! Source of all fossil fuel Allows us to explain radiant energy distribution of any object (e.g. sun) Predict at what peak energy is emitted and so choose our spectral bands accordingly Dr. Hassan J. Eghbali

31. Recap Physical properties we might measure –E.g. reflectance, temperature, height etc. EM radiation is what we measure in RS Blackbody concept used to explain energy distribution of sun / Earth –Stefan-Boltzmann law explains total energy –Wien’s law explains shift of max with decreasing T –Planck’s Law explains shape of BB energy distribution –BUT remember, no object is really a blackbody – only an approximation Dr. Hassan J. Eghbali

32. MODIS: building global picture Dr. Hassan J. Eghbali

33. IKONOS & QuickBird: very local view! QuickBird: 16.5km swath at nadir, 61cm! panchromatic, 2.44m multispectral http://www.digitalglobe.com IKONOS: 11km swath at nadir, 1m panchromatic, 4m multispectral http://www.spaceimaging.com/ Dr. Hassan J. Eghbali

34. Ikonos: high res. commercial http://www.spaceimaging.com/gallery/spacepics/khaolak_side_by_side.jpg Dr. Hassan J. Eghbali

35. Ikonos: high res. commercial http://www.euspaceimaging.com/sime.asp?page= Gallery Dr. Hassan J. Eghbali