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Dr. Mathias (Mat) Disney UCL Geography Office: 113, Pearson Building Tel: 7670 0592

2009-10 CEGEG046 / GEOG3051 Principles & Practice of Remote Sensing (PPRS) 7: scanning redux, photography, lidar. Dr. Mathias (Mat) Disney UCL Geography Office: 113, Pearson Building Tel: 7670 0592 Email: mdisney@ucl.geog.ac.uk www.geog.ucl.ac.uk/~mdisney. Recap. Last week

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Dr. Mathias (Mat) Disney UCL Geography Office: 113, Pearson Building Tel: 7670 0592

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  1. 2009-10 CEGEG046 / GEOG3051Principles & Practice of Remote Sensing (PPRS)7: scanning redux, photography, lidar Dr. Mathias (Mat) Disney UCL Geography Office: 113, Pearson Building Tel: 7670 0592 Email: mdisney@ucl.geog.ac.uk www.geog.ucl.ac.uk/~mdisney

  2. Recap • Last week • storage/transmission • pre-processing stages (raw data to products) • sensor scanning mechanisms • This week • scanning mechanisms redux • photography • time-resolved signals (e.g. LiDAR)

  3. Scanning mechanisms: examples • Discrete detectors and scanning mirrors • Landsat MSS, TM, ETM+, NOAA GOES, AVHRR, ATSR • Multispectral linear arrays • SPOT (1-3) HRV, HRVIR & SPOT-VGT, IKONOS, ASTER & MISR (both on board NASA Terra) • Imaging spectrometers using linear and area arrays • AVIRIS, CASI, MODIS (on NASA Terra and Aqua) From: http://ceos.cnes.fr:8100/cdrom/ceos1/irsd/pages/datacq4.htm & Jensen (2000)

  4. MODIS scan mirror http://modis.gsfc.nasa.gov/about/scanmirror.php • Continuously rotating and double-sided • SEVIRI (Spinning Enhanced Vis and IR Imager) on board MSG • Whole satellite rotates • Vertical scan plus rotation = image Scanning mechanisms: examples

  5. nr line r Along track pixel Frame Across track Scanning mechanisms: continued • Image frame created by scanning detector footprint • n pixels per line, pixel size r * r • Along track speed v ms-1 so footprint travels distance r in r/v secs •  One line of data must be acquired in <= r/v secs • Typical v? • Orbital period T ~ 100 mins, Earth radius ~ 6.4x103m • v = 2*6.4x103 / 100*60 = 6.7x103ms-1

  6. X-track scan (whiskbroom) Start rv Platform has moved r in rv secs Scanning mechanisms: single detector • Even if we obtain 1 line in r/v secs say..... • Significant along-track displacement from start to end of x-track scan line

  7. Active scan r/2 r flyback Speed, v Scanning mechanisms: single detector • Zig-zag mechanism • active scan lasts r/2v secs • n pixels per line, so “dwell time” (seconds per pixel) is r/2nv secs/pixel • ok for low res e.g. AVHRR, as large r • But problems for mod - high res. • E.g. Landsat MSS, r = 70m, v = 7x103ms-1 n=3000 so dwell time = 70/2*3000*7x103 = 1.7secs (OK for SNR) • BUT with single detector, required length of scan cycle r/v is 10msecs (70/7x103) • = 100 scan cycles per second • TOO FAST!

  8. T = 0 WEST T = 53ms Active scan 474m EAST T = 73.4ms 185km (swath width) Scanning mechanisms: e.g. MSS • MSS has 4x6 array of receptors - 4 bands, 6 receptors per band • 6 lines scanned simultaneously • ‘footprint’ of single receptor follows a zig-zag track • ~30 cycles per second

  9. Active r Active Active Speed, v Scanning mechanisms: boustrophedon • Alternative right  left, left  right • 2 n line pixels scanned in r/v secs •  r/2nv secs/pixel • For TM for e.g. r = 30m v = 20/3 x 103ms-1 n = 6000 •  dwell time 0.38 sec (not long enough for good SNR) • scan cycle ~4.5 msecs (~220 per second) • Way too fast i.e. single detector operation inadequate for TM • use 6 detectors per band (vis), and 16 lines at a time in vis, 4 at a time in thermal • 100 detectors total From: http://rst.gsfc.nasa.gov/Intro/Part2_20.html

  10. Photography • Largely obsolete due to electromechanical sensors • Still used for • some mapping and monitoring applications • partic. aerial surveys and photogrammetry • BUT requirement to get film back and process it • Pan-chromatic (B&W) and colour (vis and some IR) but limited spectrally • Radial image distortion away from focal point • Relatively easy to correct if camera geometry known

  11. Photography • E.g. Wild RC10 aerial camera + tracker software as used by NERC Airborne Research and Survey Facility • www.nerc.ac.uk/arsf • Software allows pilot to gauge coverage and overlap

  12. Photography • AP of Barton Bendish, Norfolk • Acquired 1997 by NERC aircraft • Scan of original • Note flight info and fiducial marks @ corners

  13. Photography: parameters • Photographic camera uses whole-frame image capture • near instantaneous snapshot of projected field-of view on ground • i.e. IFOV == whole FOV • Imaged region (A) focused by lens/mirror system onto focal plane (C) • Spectral sensitivity from 0.3 to 0.9m i.e. Uv/vis/NIR From: http://www.ccrs.nrcan.gc.ca/ccrs/learn/tutorials/fundam/chapter2/chapter2_7_e.html

  14. Photography: parameters • Large and small apertures in camera system • aperture compared to diameter of lens FROM: http://cdoswell.com/tips2.htm

  15. Photography: parameters • Focal length of photographic system • pros and cons • Amount of light v. depth of field FROM: http://cdoswell.com/tips2.htm

  16. Detector plane Principal plane 23cm 9cm diam mirror f = 82cm Equivalent to a lens of focal length 82cm Optical mechanisms: e.g. MSS • MSS optical system uses reflecting (Cassegrain) telescope • Lens with hole in centre (concave) • Convex focusing mirror

  17. Photography: parameters • Normally adjust 4 parameters • focus - by altering position of focusing lens relative to focal plane • F-stop (f-number), defined as f/d i.e. Focal length / effective diameter of lens opening • Shutter speed • e.g. 1/2000, 1/1000, 1/500 .... 1/2, 1/1, 2/1, 4/1 seconds • Faster shutter = less motion blur, but less light • Film “speed” - exposure level over which film responds (ISO/ASA number) • Faster film responds to lower light BUT poorer spatial resolution • ISO 25-100 (slow), 200-1000 (faster)

  18. Photography: parameters • General film exposure equation • E = exposure in Joules (J) mm-2, s = intrinsic scene brightness, in J mm-2s-1, d = diameter of lens opening in mm, t = time in seconds, f = lens focal length, mm • So E is measure of recorded energy • E increases with d2 , s and t • E decreases with f2 • Note that any lens system diffraction limited i.e. can’t resolve objects smaller than s/D • s = distance of object from object-side focal point; D = demagnification (Altitude/focal length i.e. D = 1/magnification = 1/s/f = f/s)

  19. ? Photography • Historical archives of photography • many military applications now declassified • e.g. Surveillance (U2, Cuba, Bay of Pigs.....) • Vietnam, N. Korea etc. etc. From: Dr. S. Lewis, PhD thesis, 2003 UCL.

  20. Time-resolved signals: LIDAR • Light Detection And Ranging • optical wavelength analogue of RADAR • active remote sensing • used for laser altimetry (height measurement) but also other information • Why use optical??? • Velocity of light ~ 3x108 ms-1 • one light year = 9.46 × 1015 m (10 trillion m) • used for cosmological distances BUT also useful for smaller distances • Light travels ~ 30cm in 1 nanosecond (10-9s)

  21. Time-resolved signals: LIDAR Laser footprint • LIDAR – light detection and ranging - optical equivalent of RADAR • First/last (discrete) return LIDAR • Full waveform LIDAR more information BUT harder to generate & interpret • See Baltsavias paper for lidar equations 21

  22. Waveform LIDAR • If we can resolve more than just first/last return • record shape of returning waveform? • Waveform LIDAR • Contains information about e.g. Vegetation canopy structure • Requires v. accurate timing information • Again, typically green or red  From:http://denali.gsfc.nasa.gov/research/laser/slicer/slicer.html

  23. Time-resolved signals: LIDAR • So for LIDAR • range of target from sensor (and source) is time of round trip for a pulse of light • return pulse very weak (function of surface reflectance) & (usually) spread out • LIDAR • laser light from source (coherent - narrow range of wavelengths) - typically 670-700nm • Spreads out as it is a wave (e.g. 10 to 100m spots on surface) • Roughness variation within spot (IFOV) mean energy returns sooner from some bits than others • Needs short, powerful laser pulses • safety? From: http://www.nasa.gov/offices/oce/appel/knowledge/publications/VCL.html

  24. Lidar signal: single birch tree • More examples at: • http://www2.geog.ucl.ac.uk/~mdisney/3Dmovies/ 24

  25. Lidar signal: single birch tree, materials • More examples at: • http://www2.geog.ucl.ac.uk/~mdisney/3Dmovies/ 25

  26. E.g. First/last return LIDAR data • Structural information from LIDAR • Possibly in situ laser scanning • Information? • Canopy height • Canopy gap fraction and vertical profile of foliage

  27. E.g. Waveform LIDAR data • Canopy height AND density information • intensity of return related to density • from http://ltpwww.gsfc.nasa.gov/eib/projects/airborne_lidar/slicer.html

  28. LIDAR missions? • SLICER • Scanning Lidar Imager of Canopies by Echo Recovery • http://denali.gsfc.nasa.gov/research/laser/slicer/slicer.html • MOLA • Mars Orbital LIDAR altimeter on Mars Global Surveyor • V. Accurate info on Martian topography • Clues to geological formation • GLAS • Geoscience Laser Altimeter System on IceSAT • Altimetry uses only first and last return signal

  29. Geoscience Laser Altimeter System (GLAS) - sole instrument Combinination surface lidar with dual wavelength cloud and aerosol lidar Launched Jan 12, 2003 Jan 15, 2003 Earth pointing Measures ice sheet elevations changes in elevation through time height profiles of clouds and aerosols land elevations vegetation cover approximate sea-ice thickness. ICESat (aka: Laser Altimetry Mision)The Ice, Cloud, and Elevation Satellite Images and info from http://icesat.gsfc.nasa.gov/

  30. Time-resolved signals: LIDAR • VCL didn’t get launched • NASA budget cuts • http://earthobservatory.nasa.gov/Library/VCL/VCL.html • http://www.geog.umd.edu/vcl/vcltext.html • ASCOPE – Proposed ESA Explorer mission (didn’t get selected) • http://www.esa.int/esaCP/SEMHQH9ATME_index_0.html • DESDyni – Deformation, Ecosystem Structure and Dynamics of Ice • L-band interferometric SAR • Canopy lidar • But being applied in airborne projects • rapid way to generate information on standing biomass • Wood volume per hectare • Used in carbon studies • useful for forestry, inventory etc. etc. From: http://earthobservatory.nasa.gov/Library/VCL/VCL_2.html

  31. E.g. Waveform LIDAR modelling • Use Monte Carlo Ray Tracing to model LIDAR signal of GLAS ICEsat • Images courtesy of U. Heyder

  32. Simulating spaceborne LIDAR: ASCOPE Based on field measurements in UK, Sweden, Finland See Disney et al (2009) IEEE TGRSS, ASCOPE paper

  33. Ground-based laser scanning? • Tripod-mounted LIDAR • developed for surveying • BUT has uses for collecting information on forest density and structure • Typically records point cloud from several known locations then use software to reconstruct scene in 3D From: http://www.geospatial-online.com/geospatialsolutions/article/articleDetail.jsp?id=65014&pageID=4

  34. The next generation! ECHIDNA • Scanning (multi-beam) ground-based LIDAR • Developed by Jupp et al. at CSIRO (Aus.) specifically for vegetation From talk by D. Jupp at ISPMSRS, Beijing, October 17-19 2005.

  35. ECHIDNA From talk by D. Jupp at ISPMSRS, Beijing, October 17-19 2005.

  36. ECHIDNA • Generalise hemispherical information • But much more than for photography (discriminate canopy compnents) From talk by D. Jupp at ISPMSRS, Beijing, October 17-19 2005.

  37. ECHIDNA From talk by D. Jupp at ISPMSRS, Beijing, October 17-19 2005.

  38. Simulating ground-based (canopy) LIDAR Hemispherical full waveform terrestrial laser scanner. Generates volumetric canopy data. Abisko, Sweden White Fir, Sierra Nevada (A. Strahler) Echidna: Ground-based full-waveform scanning • Jupp et al. (2009) Estimating forest LAI profiles and structural parameters using a ground-based laser called Echidna, Tree Physiology 29(2) 171-181 38 Steve Hancock EPSRC, NCEOI

  39. LIDAR sounding (up/down) • For studying atmospheric aerosols, clouds etc. • Use backscatter properties of atmosphere • e.g. LITE (1994 Shuttle mission) • Upward looking? e.g. ELF • Coherence of laser gives narrow beam • better azimuthal sampling than thermal, RADAR From:http://alg.umbc.edu/elf/elf.html

  40. Ground-based: GPR • Ground penetrating RADAR • gives v. accurate information on sub-surface density and structure • Use for surveying hidden pipes for e.g. • Archaeology • Hidden graves • dinosaur tracks! • Geophysics • ice and snow density & movement • Hidden objects? • Landmines... From:www.geomodel.com && http://www.du.edu/~lconyer/picketwire_canyonlands_dinosaur_.htm

  41. Summary • Sensor scanning mechanisms • Limitations (dwell-time/SNR, scan rate) • Striping of detector lines and arrays • CCD • Photography • Becoming less widely-used but still some applications • Time-resolved: LiDAR • For altimetry AND imaging (veg. structure) – higher vertical resolution than RADAR • Ground-based • Upward-looking for atmospheric studies • GPR for sub-surface surveying: archaeology, geophysical dynamics

  42. REVISION MISCELLANEOUS EXAMPLES, TOPICS

  43. Revision: orbits and swaths • Example: polar orbiter period, if h = 705x103m • T = 2[(6.38x106 +705x103)3 / (6.67x10-11*5.983x1024)]1/2 • T = 5930.6s = 98.8mins • Example: show separation of successive ground tracks ~3000km • Earth angular rotation = 2/24*60*60 = 7.27x10-5rads s-1 • So in 98.8 mins, point on surface moves 98.8*60*7.27x10-5 = .431 rads • Remember l =r* for arc of circle radius r &  in radians • So l = (Earth radius + sat. altitude)*  • = (6.38x106 +705x103)* 0.431 = 3054km

  44. Revision: Planck’s Law • 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 http://www.tmeg.com/esp/e_orbit/orbit.htm

  45. Revision: Planck’s Law • Explains/predicts shape of blackbody curve • Use to predict how much energy lies between given  • Crucial for remote sensing http://hyperphysics.phy-astr.gsu.edu/hbase/bbrc.html#c1

  46. Atmospheric windows Atmospheric “windows” • As a result of strong dependence of absorption • Some  totally unsuitable for remote sensing as most radiation absorbed

  47. Revision: the atmosphere • SCATTERING: caused by presence of particles (soot, salt, etc.) and/or large gas molecules present in the atmosphere • Rayleigh, Mie, Non-selective • ABSORPTION: gaseous components (CO2, CO, CH4, H2O etc) • Very strong function of wavelength • Atmospheric windows

  48. Revision: the surface: BRDF • Reflectance of most real surfaces is a function of not only , but viewing and illumination angles • Described by the Bi-Directional Reflectance Distribution Function (BRDF) • BRDF of area A defined as: ratio of incremental radiance, dLe, leaving surface through an infinitesimal solid angle in direction (v, v), to incremental irradiance, dEi, from illumination direction ’(i, i) i.e. •  is viewing vector (v, v) are view zenith and azimuth angles; ’ is illum. vector (i, i) are illum. zenith and azimuth angles • So in sun-sensor example,  is position of sensor and ’ is position of sun After: Jensen, J. (2000) Remote sensing of the environment: an Earth Resources Perspective.

  49. viewer incident diffuse radiation direct irradiance (Ei) vector  exitant solid angle  incident solid angle  v i 2-v i surface area A surface tangent vector Configuration of viewing and illumination vectors in the viewing hemisphere, with respect to an element of surface area, A. Revision: the surface: BRDF • Note that BRDF defined over infinitesimally small solid angles , ’ and  interval, so cannot measure directly • In practice measure over some finite angle and  and assume valid From: http://www.geog.ucl.ac.uk/~mdisney/phd.bak/final_version/final_pdf/chapter2a.pdf

  50. Revision: examples • Planck function • Gravitational force Fg = GMEms/RsE2 • where G is universal gravitational constant (6.67x10-11 Nm2kg2); ME is Earth mass (5.983x1024kg); ms is satellite mass (?) and RsE is distance from Earth centre to satellite i.e. 6.38x106 + h where h is satellite altitude • Centripetal (not centrifugal!) force Fc = msvs2/RsE • where vs is linear speed of satellite (=sRsE where  is the satellite angular velocity, rad s-1) • for stable (constant radius) orbit Fc = Fg • GMEms/RsE2 = msvs2/RsE = ms s2RsE2 /RsE • so s2 = GME /RsE3 From:http://csep10.phys.utk.edu/astr161/lect/history/kepler.html

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