Transcript Slide 1

2009-10 CEGEG046 / GEOG3051
Principles & Practice of Remote Sensing (PPRS)
5: resolution II: angular/temporal
Dr. Mathias (Mat) Disney
UCL Geography
Office: 113, Pearson Building
Tel: 7670 05921
Email: [email protected]
www.geog.ucl.ac.uk/~mdisney
Recap
• Previously introduced
– spatial and spectral resolution
– narrow v broad band tradeoffs....
– signal to noise ratio
• This week
– temporal and angular sampling and/or resolution
– REMEMBER: sampling NOT same as resolution, but
sometimes used interchagngeably
– orbits and sensor swath
– radiometric resolution
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Temporal sampling/resolution
• Single or multiple observations
• How far apart are observations in time?
– One-off, several or many?
• Depends (as usual) on application
– Is it dynamic?
– If so, over what timescale?
Useful link: http://nasascience.nasa.gov/earth-science
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Temporal
• Examples
– Vegetation stress monitoring, weather, rainfall
• hours to days
– Terrestrial carbon, ocean surface temperature
• days to months to years
– Glacier dynamics, ice sheet mass balance, erosion/tectonic
processes
• Months to decades
Useful link: http://nasascience.nasa.gov/earth-science
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What determines temporal sampling?
• Sensor orbit
– geostationary orbit - over same spot
• BUT distance means entire hemisphere is viewed e.g. METEOSAT
– polar orbit can use Earth rotation to view entire surface
• Sensor swath
– Wide swath allows more rapid revisit
• typical of moderate res. instruments for regional/global applications
– Narrow swath == longer revisit times
• typical of higher resolution for regional to local applications
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Orbits and swaths
• Orbital characteristics
– orbital mechanics developed by Johannes Kepler (1571-1630),
German mathematician
– Explained observations of Danish nobleman Tyco Brahe (15461601)
– Kepler favoured elliptical orbits (from Copernicus’ solar-centric
system)
• Properties of ellipse?
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Ellipse
• Flattened circle
–
–
–
–
2 foci and 2 axes: major and minor
Distance r1+r2 = constant = 2a (major axis)
“Flatness” of ellipse defined by eccentricity, e = 1-b2/a2 = c/a
i.e. e is position of the focus as a fraction of the semimajor axis, a
f1
r2
C
f2
2b
minor axis
r1
Increasing eccentricity
•ecircle = 0
2c
2a
major axis
•As e 1, c  a and ellipse
becomes flatter
From http://mathworld.wolfram.com/Ellipse.html
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Kepler’s laws
• Kepler’s Laws
– deduced from Brahe’s data after his death
– see nice Java applet http://www-groups.dcs.stand.ac.uk/~history/Java/Ellipse.html
• Kepler’s 1st law:
– Orbits of planets are elliptical, with sun at one focus
From:http://csep10.phys.utk.edu/astr161/lect/history/kepler.html
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Kepler’s laws
• Kepler’s 2nd law
– line joining planet to sun sweeps out equal areas in equal times
From:http://csep10.phys.utk.edu/astr161/lect/history/kepler.html
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Kepler’s laws
• Kepler’s 3rd law
– “ratio of the squares of the revolutionary periods for two planets (P1,
P2) is equal to the ratio of the cubes of their semimajor axes (R1, R2)”
– P12/P22 = R13/R23
• i.e. orbital period increases dramatically with R
• Convenient unit of distance is average separation of
Earth from Sun = 1 astronomical unit (A.U.)
–
–
–
–
1A.U. = 149,597,870.691 km
in Keplerian form, P(years)2  R(A.U.)3
or P(years)  R(A.U.)3/2
or R(A.U.)  P(years)2/3
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Orbits: examples
• Orbital period for a given instrument and height?
– Gravitational force Fg = GMEms/RsE2
• 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
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Orbits: examples
• Orbital period T of satellite (in s) = 2/
– (remember 2 = one full rotation, 360°, in radians)
– and RsE = RE + h where RE = 6.38x106 m
– So now T = 2[(RE+h)3/GME]1/2
• 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: altitude for geostationary orbit? T = ??
– Rearranging: h = [(GME /42)T2 ]1/3 - RE
– So h = [(6.67x10-11*5.983x1024 /42)(24*60*60)2 ]1/3 - 6.38x106
– h = 42.2x106 - 6.38x106 = 35.8km
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Orbits: aside
• Convenience of using radians
– By definition, angle subtended by an arc  (in radians) = length of
arc/radius of circle i.e.  = l/r
– i.e. length of an arc l = r
– So if we have unit circle (r=1), l = circumference = 2r = 2
– So, 360° = 2 radians
l

r
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Orbital pros and cons
• Geostationary?
– Circular orbit in the equatorial plane, altitude ~36,000km
– Orbital period?
• Advantages
– See whole Earth disk at once due to large distance
– See same spot on the surface all the time i.e. high temporal coverage
– Big advantage for weather monitoring satellites - knowing atmos.
dynamics critical to short-term forecasting and numerical weather
prediction (NWP)
• GOES (Geostationary Orbiting Environmental Satellites), operated by
NOAA (US National Oceanic and Atmospheric Administration)
• http://www.noaa.gov/ and http://www.goes.noaa.gov/
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Geostationary
•
Meteorological satellites - combination of GOES-E, GOES-W, METEOSAT
(Eumetsat), GMS (NASDA), IODC (old Meteosat 5)
– GOES 1st gen. (GOES-1 - ‘75  GOES-7 ‘95); 2nd gen. (GOES-8++ ‘94)
GOES-E 75° W
GOES-W 135°
W
METEOSAT 0° W
IODC 63° E
GMS 140° E
From http://www.sat.dundee.ac.uk/pdusfaq.html
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Geostationary
• METEOSAT - whole earth disk every 15 mins
From http://www.goes.noaa.gov/f_meteo.html
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Geostationary orbits
• Disadvantages
– typically low spatial resolution due to high altitude
– e.g. METEOSAT 2nd Generation (MSG) 1x1km visible, 3x3km IR
(used to be 3x3 and 6x6 respectively)
• MSG has SEVIRI and GERB instruments
• http://www.eumetsat.int/Home/Main/What_We_Do/Satellites/Meteosat_Sec
ond_Generation/Space_Segment/SP_1119959405658?l=en
– Cannot see poles very well (orbit over equator)
• spatial resolution at 60-70° N several times lower
• not much good beyond 60-70°
– NB Geosynchronous orbit same period as Earth, but not equatorial
From http://www.esa.int/SPECIALS/MSG/index.html
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Polar & near polar orbits
• Advantages
– full polar orbit inclined 90 to equator
• typically few degrees off so poles not covered
• orbital period typically 90 - 105mins
– near circular orbit between 300km (low Earth orbit) and 1000km
– typically higher spatial resolution than geostationary
– rotation of Earth under satellite gives (potential) total coverage
• ground track repeat typically 14-16 days
From http://collections.ic.gc.ca/satellites/english/anatomy/orbit/
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(near) Polar orbits: NASA Terra
From http://visibleearth.nasa.gov/cgi-bin/viewrecord?134
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Near-polar orbits: Landsat
– inclination 98.2, T = 98.8mins
–
–
http://www.cscrs.itu.edu.tr/page.en.php?id=51
http://landsat.gsfc.nasa.gov/project/Comparison.html
•ASIDE: repeat time
•Orbital period is 5928s
•So in this time Earth surface moves
l = r = r*(2*5928/(24*60*60))
•So if r = 6.38x106 then l = 2750km
From http://www.iitap.iastate.edu/gccourse/satellite/satellite_lecture_new.html &
http://eosims.cr.usgs.gov:5725/DATASET_DOCS/landsat7_dataset.html
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(near) Polar orbits
• Disadvantages
– need to launch to precise altitude and orbital inclination
– orbital decay
• at LEOs (Low Earth Orbits) < 1000km, drag from atmosphere
• causes orbit to become more eccentric
• Drag increases with increasing solar activity (sun spots) - during solar
maximum (~11yr cycle) drag height increased by 100km!
– Build your own orbit:
http://lectureonline.cl.msu.edu/~mmp/kap7/orbiter/orbit.htm
From http://collections.ic.gc.ca/satellites/english/anatomy/orbit/
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Types of near-polar orbit
• Sun-synchronous
– Passes over same point on surface at approx. same local solar time
each day (e.g. Landsat)
– Characterised by equatorial crossing time (Landsat ~ 10am)
– Gives standard time for observation
– AND gives approx. same sun angle at each observation
• good for consistent illumination of observations over time series (i.e. Observed change
less likely to be due to illumination variations)
• BAD if you need variation of illumination (angular reflectance behaviour)
• Special case is dawn-to-dusk
– e.g. Radarsat 98.6° inclination
– trails the Earth’s shadow (day/night border)
– allows solar panels to be kept in sunlight all the time)
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Near-ish: Equatorial orbit
• Inclination much lower
– orbits close to equatorial
– useful for making observations solely over tropical regions
• Example
– TRMM - Tropical Rainfall Measuring Mission
– Orbital inclination 35.5°, periapsis (near point: 366km), apoapsis (far point:
3881km)
– crosses equator several times daily
– Flyby of Hurrican Frances (24/8/04)
– iso-surface
From http://trmm.gsfc.nasa.gov/
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Orbital location?
• TLEs (two line elements)
– http://www.satobs.org/element.html e.g.
PROBA 1
1 26958U 01049B 04225.33423432 .00000718 00000-0 77853-4 0 2275
2 26958 97.8103 302.9333 0084512 102.5081 258.5604 14.88754129152399
• DORIS, GPS, Galileo etc.
– DORIS: Doppler Orbitography and Radiopositioning Integrated by Satellite
– Tracking system providing range-rate measurements of signals from a dense
network of ground-based beacons (~cm accuracy)
– GPS: Global Positioning System
– http://www.vectorsite.net/ttgps.html
– http://www.edu-observatory.org/gps/tracking.html
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Instrument swath
• Swath describes ground area imaged by instrument
during overpass
direction of
travel
satellite ground
swath
one
sample
two
samples
three
samples
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MODIS on-board Terra
From http://visibleearth.nasa.gov/cgi-bin/viewrecord?130
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Terra instrument swaths compared
From http://visibleearth.nasa.gov/Sensors/Terra/
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Broad swath
• MODIS, POLDER, AVHRR etc.
–
–
–
–
swaths typically several 1000s of km
lower spatial resolution
Wide area coverage
Large overlap obtains many more view and illumination angles
(much better termporal & angular (BRDF) sampling)
– Rapid repeat time
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MODIS: building global view
•
•
•
Note across-track “whiskbroom” type scanning mechanism
swath width of 2330km (250-1000m resolution)
Hence, 1-2 day repeat cycle
From http://visibleearth.nasa.gov/Sensors/Terra/
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AVHRR: global view
•
•
2400km swath, 1.1km pixels at nadir, but > 5km at edge of swath
Repeats 1-2 times per day
From http://edc.usgs.gov/guides/avhrr.html
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POLDER (RIP!): global view
•
Polarisation and Directionality of Earth’s Reflectance
– FOV ±43° along track, ±51° across track, 9 cameras, 2400km swath,
7x6km resn. at nadir
– POLDER I 8 months, POLDER II 7 months....
Each set of points corresponds to
given viewing zenith and
azimuthal angles for nearsimultaneous measurements over
a region defined by lat
0°±0.5° and long of
0°±0.5° (Nov 1996)
Each day, region is sampled from
different viewing directions so
hemisphere is sampled heavily
by compositing measurements
over time
From Loeb et al. (2000) Top-ofAtmosphere Albedo Estimation from
Angular Distribution Models Using
Scene Identification from Satellite
Cloud Property Retrievals, Journal of
Climate, 1269-1285.
From http://www-loa.univ-lille1.fr/~riedi/BROWSES/200304/16/index.html
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Narrow swath
• Landsat TM/MSS/ETM+, IKONOS, QuickBird etc.
–
–
–
–
–
swaths typically few 10s to 100skm
higher spatial resolution
local to regional coverage NOT global
far less overlap (particularly at lower latitudes)
May have to wait weeks/months for revisit
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Landsat: regional to local view
•185km swath width,
hence 16-day repeat cycle
(and spatial res. 25m)
•Contiguous swaths
overlap (sidelap) by 7.3%
at the equator
•Much greater overlap at
higher latitudes (80% at
84°)
From http://visibleearth.nasa.gov/Sensors/Terra/
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IKONOS & QuickBird: very local view!
•IKONOS: 11km swath at nadir, 1m
panchromatic, 4m multispectral
•QuickBird: 16.5km swath at nadir, 61cm!
panchromatic, 2.44m multispectral
•http://www.spaceimaging.com/
•http://www.digitalglobe.com
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Variable repeat patterns
• ERS 1 & 2
– ATSR instruments, RADAR altimeter, Imaging SAR (synthetic aperture
RADAR) etc.
– ERS 1: various mission phases: repeat times of 3 (ice), 35 and 168
(geodyssey) days
– ERS 2: 35 days
From http://earth.esa.int/rootcollection/eeo/ERS1.1.7.html
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So.....angular resolution
• Wide swath instruments have large overlap
– e.g. MODIS 2330km (55), so up to 4 views per day at different
angles!
– AVHRR, SPOT-VGT, POLDER I and II, etc.
– Why do we want good angular sampling?
• Remember BRDF?
• See Barnsley et al (1997) paper
– Information in angular signal we can exploit!
– Or remove BRDF effects when combining observations from different
times/angles
– More samples of viewing/illum. hemisphere gives more info.
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Angular (BRDF) effects
•
•
Can look like noise
over time BUT
plotted as a
function of angle
we see BRDF
effect
So must account
for BRDF if we
want to look at
changes over time
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Angular sampling: broad swath
relative azimuth (view
- solar)
view zenith
Solar principal
plane
•
MODIS and SPOT-VGT: polar plots
–
•
•
Cross solar
principal plane
http://www.soton.ac.uk/~epfs/methods/polarplot.shtml
Reasonable sampling BUT mostly across principal plane (less angular info.)
Is this “good” sampling of BRDF
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Angular sampling: broad swath
•
•
POLDER I !
Broad swath (2200km) AND
large 2D CCD array gave
huge number of samples
– 43 IFOV along-track and
51 IFOV across-track
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BUT.......
• Is wide swath angular sampling REALLY multi-angular?
– Different samples on different days e.g. MODIS BRDF product is
composite over 16 days
– minimise impact of clouds, maximise number of samples
• “True” multi-angular viewing requires samples at same time
– need to use several looks e.g. ATSR, MISR (& POLDER)
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Angular sampling: narrow swath
•
•
•
ATSR-2 and MISR polar plots
Better sampling in principal plane (more angular info.)
MISR has 9 cameras
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Angular sampling: combinations?
•
•
MODIS AND MISR: better sampling than either individually
Combine observations to sample BRDF more effectively
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So, angular resolution
• Function of swath and IFOV
– e.g. MODIS at nadir ~1km pixel
– remember l = r  so angle (in rads)  = r/l where r this time is 705km
and l ~ 1km so angular res ~ 1.42x10-6 rads at nadir
– at edge of swath ~5km pixel so angular res ~ 7x10-6 rads
• SAMPLING more important/meaningful than resolution in angular
sense (as for temporal)
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Radiometric resolution
• Had spatial, spectral, temporal, angular.....
• Precision with which an instrument records EMR
– i.e. Sensitivity of detector to amount of incoming radiation
– More sensitivity == higher radiometric resolution
• determines smallest slice of EM spectrum we can assign DN to
– BUT higher radiometric resolution means more data
• As is the case for spatial, temporal, angular etc.
• Typically, radiometric resolution refers to digital detectors
– i.e. Number of bits per pixel used to encode signal
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Radiometric resolution
• Analogue
– continuous measurement levels
– film cameras
– radiometric sensitivity of film emulsion
• Digital
– discrete measurement levels
– solid state detectors (e.g. semiconductor CCDs)
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Radiometric resolution
• Bits per pixel
– 1 bit (0,1); 2bits (0, 1, 2, 3); 3 bits (0, 1, 2, 3, 4, 5, 6, 7) etc.
– 8 bits in a byte so 1 byte can record 28 (256) different DNs (0-255)
• 1 to 6 bits (left to right)
– black/white (21) up to 64 graylevels (26) (DN values)
– human eye cannot distinguish more than 20-30 DN levels in grayscale
i.e. ‘radiometric resolution’ of human eye 4-5 bits
From http://ceos.cnes.fr:8100/cdrom/ceos1/irsd/pages/dre4.htm
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Radiometric resolution: examples
• Landsat: MSS 7bits, TM 8bits
• AVHRR: 10-bit (210 = 1024 DN levels)
– TIR channel scaled (calibrated) so that DN 0 = -273°C and DN 1023 ~50°C
• MODIS: 12-bit (212 = 4096 DN levels)
• BUT precision is NOT accuracy
– can be very precise AND very inaccurate
– so more bits doesn’t mean more accuracy
• Radiometric accuracy designed with application and data size in
mind
– more bits == more data to store/transmit/process
47
Summary: angular, temporal resolution
• Coverage (hence angular &/or temporal sampling) due
to combination of orbit and swath
– Mostly swath - many orbits nearly same
• MODIS and Landsat have identical orbital characteristics: inclination
98.2°, h=705km, T = 99mins BUT swaths of 2400km and 185km hence
repeat of 1-2 days and 16 days respectively
– Most EO satellites typically near-polar orbits with repeat tracks
every 16 or so days
– BUT wide swath instrument can view same spot much more
frequently than narrow
• Tradeoffs again, as a function of objectives
48
Summary: radiometric resolution
• Number of bits per pixel
– more bits, more precision (not accuracy)
– but more data to store, transmit, process
– most EO data typically 8-12 bits (in raw form)
• Tradeoffs again, as a function of objectives
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ASIDE: 2nd ESA Explorer launched 2/11/09
• SMOS (Soil Moisture and Ocean Salinity) probe
– Interferometric radiometer
– Global maps of soil moisture every three days within an accuracy
of 4% at a spatial resolution of 50 km
– Global maps of sea-surface salinity down to 0.1 practical salinity
units for a 30-day average over an area of 200×200 km
• http://www.esa.int/SPECIALS/smos/SEMNEYAOE1G_0.html
• AND Proba-2 (PRoject for On-Board Autonomy
• SEMINAR: tomorrow (5th) at 5pm in room 305
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